AI Hardware & Edge AI Summit 2023 Agenda | Kisaco Research

AI Hardware & Edge AI Summit 2023 Agenda

AI Hardware & Edge AI Summit 2023
12-14 September, 2023
Santa Clara Marriott, CA

Stay tuned for plenty more sessions, sponsors, keynotes, workshops and speakers to announce in the coming weeks. To see the agenda for the Efficient Generative AI Summit, please click here

Please note, the filterable options will be coming soon. 

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Tuesday, 12 Sep, 2023
DAY 1 - SERVER TO EDGE: TRAINING + HARDWARE & SYSTEMS DESIGN
09:00 AM
REGISTRATION & MORNING NETWORKING
LUMINARY KEYNOTE

Abstract coming soon...

Author:

Andrew Ng

Founder & CEO
Landing AI

Dr. Andrew Ng is a globally recognized leader in AI (Artificial Intelligence). He is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman & Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.

In 2011, he led the development of Stanford University's main MOOC (Massive Open Online Courses) platform and taught an online Machine Learning course that was offered to over 100,000 students leading to the founding of Coursera where he is currently Chairman and Co-founder.

Previously, he was Chief Scientist at Baidu, where he led the company’s ~1300 person AI Group and was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team.

As a pioneer in machine learning and online education, Dr. Ng has changed countless lives through his work in AI, and has authored or co-authored over 200 research papers in machine learning, robotics and related fields. In 2013, he was named to the Time 100 list of the most influential persons in the world. He holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.

 

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Andrew Ng

Founder & CEO
Landing AI

Dr. Andrew Ng is a globally recognized leader in AI (Artificial Intelligence). He is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman & Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.

In 2011, he led the development of Stanford University's main MOOC (Massive Open Online Courses) platform and taught an online Machine Learning course that was offered to over 100,000 students leading to the founding of Coursera where he is currently Chairman and Co-founder.

Previously, he was Chief Scientist at Baidu, where he led the company’s ~1300 person AI Group and was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team.

As a pioneer in machine learning and online education, Dr. Ng has changed countless lives through his work in AI, and has authored or co-authored over 200 research papers in machine learning, robotics and related fields. In 2013, he was named to the Time 100 list of the most influential persons in the world. He holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.

 

KEYNOTE

Abstract coming soon...

Author:

Marc Tremblay

VP & Distinguished Engineer
Microsoft

Marc Tremblay is a distinguished engineer at Microsoft. Prior to joining Microsoft in April 2009, he was senior vice president and chief technology officer of the microelectronics business unit at Sun Microsystems. He was instrumental in the design of various microprocessors at Sun, including the UltraSPARC, UltraSPARC II, MAJC, UltraSPARC T1, and the cancelled Rock processor. In the process, he was awarded more patents than any other Sun employee.

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Marc Tremblay

VP & Distinguished Engineer
Microsoft

Marc Tremblay is a distinguished engineer at Microsoft. Prior to joining Microsoft in April 2009, he was senior vice president and chief technology officer of the microelectronics business unit at Sun Microsystems. He was instrumental in the design of various microprocessors at Sun, including the UltraSPARC, UltraSPARC II, MAJC, UltraSPARC T1, and the cancelled Rock processor. In the process, he was awarded more patents than any other Sun employee.

HEADLINE PARTNER KEYNOTE

Abstract coming soon...

LUMINARY KEYNOTE

Abstract coming soon...

Author:

Jim Keller

CEO
Tenstorrent

Jim Keller is the CEO of Tenstorrent and a veteran hardware engineer. Prior to joining Tenstorrent, he served two years as Senior Vice President of Intel's Silicon Engineering Group. He has held roles as Tesla's Vice President of Autopilot and Low Voltage Hardware, Corporate Vice President and Chief Cores Architect at AMD, and Vice President of Engineering and Chief Architect at P.A. Semi, which was acquired by Apple Inc. Jim has led multiple successful silicon designs over the decades, from the DEC Alpha processors, to AMD K7/K8/K12, HyperTransport and the AMD Zen family, the Apple A4/A5 processors, and Tesla's self-driving car chip.

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Jim Keller

CEO
Tenstorrent

Jim Keller is the CEO of Tenstorrent and a veteran hardware engineer. Prior to joining Tenstorrent, he served two years as Senior Vice President of Intel's Silicon Engineering Group. He has held roles as Tesla's Vice President of Autopilot and Low Voltage Hardware, Corporate Vice President and Chief Cores Architect at AMD, and Vice President of Engineering and Chief Architect at P.A. Semi, which was acquired by Apple Inc. Jim has led multiple successful silicon designs over the decades, from the DEC Alpha processors, to AMD K7/K8/K12, HyperTransport and the AMD Zen family, the Apple A4/A5 processors, and Tesla's self-driving car chip.

NETWORKING LUNCH
PRESENTATION

Abstract coming soon...

Author:

Soojung Ryu

CEO
SAPEON

As a well-known expert in AI processors, Soojung Ryu is in charge of SAPEON in order to accelerate the company’s growth in the global AI market. She brings more than 25 years of extensive experience in leading various projects related to NPU and GPU.

Before she joined SK Telecom as the head of the AI accelerator office, Ryu was a University-Industry Collaboration Professor at Seoul National University, where she conducted R&D in the NPU and PIM. When she served as the Vice President of Samsung Group's R&D hub, she undertook diverse projects related to GPU. Ryu received her Ph.D. degree in Electrical & Computer Engineering from Georgia Institute of Technology.

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Soojung Ryu

CEO
SAPEON

As a well-known expert in AI processors, Soojung Ryu is in charge of SAPEON in order to accelerate the company’s growth in the global AI market. She brings more than 25 years of extensive experience in leading various projects related to NPU and GPU.

Before she joined SK Telecom as the head of the AI accelerator office, Ryu was a University-Industry Collaboration Professor at Seoul National University, where she conducted R&D in the NPU and PIM. When she served as the Vice President of Samsung Group's R&D hub, she undertook diverse projects related to GPU. Ryu received her Ph.D. degree in Electrical & Computer Engineering from Georgia Institute of Technology.

Abstract coming soon...

Author:

Cheng Wang

Co-Founder & SVP, Architecture & Engineering
Flex Logix

Originally from Shanghai, PRC.  Cheng has led the architecture, silicon implementation and software development for eFPGA over multiple generations from 180nm-16nm and now AI inferencing development at Flex Logix. Two years as VLSI designer at Zoran. BSEECS, UC Berkeley.  MSEE, EE PhD UCLA: designed 5 FPGA chips from 90nm to 40nm. 2013 Distinguished PhD Dissertation Award. 2014 ISSCC Lewis Winner Award for Outstanding Paper. Multiple patents at UCLA and Flex Logix.

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Cheng Wang

Co-Founder & SVP, Architecture & Engineering
Flex Logix

Originally from Shanghai, PRC.  Cheng has led the architecture, silicon implementation and software development for eFPGA over multiple generations from 180nm-16nm and now AI inferencing development at Flex Logix. Two years as VLSI designer at Zoran. BSEECS, UC Berkeley.  MSEE, EE PhD UCLA: designed 5 FPGA chips from 90nm to 40nm. 2013 Distinguished PhD Dissertation Award. 2014 ISSCC Lewis Winner Award for Outstanding Paper. Multiple patents at UCLA and Flex Logix.

PRESENTATION

Abstract coming soon...

Author:

Jia Li

Co-founder, Chief AI Officer and President of a Stealth Generative AI Startup & Co-founder and Chairperson
HealthUnity Corporation

Jia is Co-founder, Chief AI Officer and President of a Stealth Generative AI Startup. She is elected as IEEE Fellow for Leadership in Large Scale AI. She is co-teaching the inaugural course of Generative AI and Medicine at Stanford University, where she has served multiple roles including Advisory Board Committee to Nourish, Chief AI Fellow, RWE for Sleep Health and Adjunct Professor at the School of Medicine in the past. She was the Founding Head of R&D at Google Cloud AI. At Google, she oversaw the development of the full stack of AI products on Google Cloud to power solutions for diverse industries. With the passion to make more impact to our everyday life, she later became an entrepreneur, building and advising companies with award-winning platforms to solve today's greatest challenges in life. She has served as Mentor and Professor-in-Residence at StartX, advising founders/companies from Stanford/Alumni. She is the Co-founder and Chairperson of HealthUnity Corporation, a 501(c)3 nonprofit organization. She served briefly at Accenture as a part-time Chief AI Follow for the Generative AI strategy. She also serves as an advisor to the United Nations Children's Fund (UNICEF). She is a board member of the Children's Discovery Museum of San Jose. She was selected as a World Economic Forum Young Global Leader, a recognition bestowed on 100 of the world’s most promising business leaders, artists, public servants, technologists, and social entrepreneurs in 2018. Before joining Google, She was the Head of Research at Snap, leading the AI/AR innovation effort. She received her Ph.D. degree from the Computer Science Department at Stanford University.

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Jia Li

Co-founder, Chief AI Officer and President of a Stealth Generative AI Startup & Co-founder and Chairperson
HealthUnity Corporation

Jia is Co-founder, Chief AI Officer and President of a Stealth Generative AI Startup. She is elected as IEEE Fellow for Leadership in Large Scale AI. She is co-teaching the inaugural course of Generative AI and Medicine at Stanford University, where she has served multiple roles including Advisory Board Committee to Nourish, Chief AI Fellow, RWE for Sleep Health and Adjunct Professor at the School of Medicine in the past. She was the Founding Head of R&D at Google Cloud AI. At Google, she oversaw the development of the full stack of AI products on Google Cloud to power solutions for diverse industries. With the passion to make more impact to our everyday life, she later became an entrepreneur, building and advising companies with award-winning platforms to solve today's greatest challenges in life. She has served as Mentor and Professor-in-Residence at StartX, advising founders/companies from Stanford/Alumni. She is the Co-founder and Chairperson of HealthUnity Corporation, a 501(c)3 nonprofit organization. She served briefly at Accenture as a part-time Chief AI Follow for the Generative AI strategy. She also serves as an advisor to the United Nations Children's Fund (UNICEF). She is a board member of the Children's Discovery Museum of San Jose. She was selected as a World Economic Forum Young Global Leader, a recognition bestowed on 100 of the world’s most promising business leaders, artists, public servants, technologists, and social entrepreneurs in 2018. Before joining Google, She was the Head of Research at Snap, leading the AI/AR innovation effort. She received her Ph.D. degree from the Computer Science Department at Stanford University.

Author:

Krishna Rangasayee

Founder & CEO
SiMa.ai

Krishna is founder and CEO of SiMa.ai™, a machine learning company enabling effortless ML for the Embedded Edge.

Previously, he was the COO of Groq, a machine learning startup. He was with Xilinx for 18 years, where he was Senior Vice President and GM of Xilinx’s overall business prior to his most recent role as Executive Vice President, Global Sales. Prior to Xilinx, he held various engineering and business roles at Altera Corporation and Cypress Semiconductor. He holds 25+ international patents. He has also served on the board of directors of public and private companies.

... read more

Krishna Rangasayee

Founder & CEO
SiMa.ai

Krishna is founder and CEO of SiMa.ai™, a machine learning company enabling effortless ML for the Embedded Edge.

Previously, he was the COO of Groq, a machine learning startup. He was with Xilinx for 18 years, where he was Senior Vice President and GM of Xilinx’s overall business prior to his most recent role as Executive Vice President, Global Sales. Prior to Xilinx, he held various engineering and business roles at Altera Corporation and Cypress Semiconductor. He holds 25+ international patents. He has also served on the board of directors of public and private companies.

Abstract coming soon...

Author:

Wayne Wang

Founder & CEO
Moffett AI

Wayne Wang is the Founder & CEO of Moffett AI, and is an expert in digital-analog hybrid circuits in Silicon Valley with 15 years of experience. His main experience is as a CPU high-speed link architect.

He has several years of experience in semiconductor entrepreneurship in Silicon Valley. He used to be the core architect of Intel and Qualcomm, and participated in the development of five generations of Intel CPU processors, with a cumulative mass production of over 5 billion pieces.

... read more

Wayne Wang

Founder & CEO
Moffett AI

Wayne Wang is the Founder & CEO of Moffett AI, and is an expert in digital-analog hybrid circuits in Silicon Valley with 15 years of experience. His main experience is as a CPU high-speed link architect.

He has several years of experience in semiconductor entrepreneurship in Silicon Valley. He used to be the core architect of Intel and Qualcomm, and participated in the development of five generations of Intel CPU processors, with a cumulative mass production of over 5 billion pieces.

PANEL

Tools like ChatGPT and Stable Diffusion have stunned the world with their ability to generate text and images.  But despite their power, they have key limitations that make them unsuitable for many key corporate applications.  In this panel we will discuss the emerging trends in generative AI, their business value and the tradeoffs between using a fixed foundation model and the pros and cons of fine-tuning these models.

Moderator

Author:

Dan McCreary

Distinguished Engineer, Graph & AI
Optum

Dan is a distinguished engineer in AI working on innovative database architectures including document and graph databases. He has a strong background in semantics, ontologies, NLP and search. He is a hands-on architect and like to build his own pilot applications using new technologies. Dan started the NoSQL Now! Conference (now called the Database Now! Conferences). He also co-authored the book Making Sense of NoSQL, one of the highest rated books on Amazon on the topic of NoSQL. Dan worked at Bell Labs as a VLSI circuit designer where he worked with Brian Kernighan (of K&R C). Dan also worked with Steve Jobs at NeXT Computer.

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Dan McCreary

Distinguished Engineer, Graph & AI
Optum

Dan is a distinguished engineer in AI working on innovative database architectures including document and graph databases. He has a strong background in semantics, ontologies, NLP and search. He is a hands-on architect and like to build his own pilot applications using new technologies. Dan started the NoSQL Now! Conference (now called the Database Now! Conferences). He also co-authored the book Making Sense of NoSQL, one of the highest rated books on Amazon on the topic of NoSQL. Dan worked at Bell Labs as a VLSI circuit designer where he worked with Brian Kernighan (of K&R C). Dan also worked with Steve Jobs at NeXT Computer.

Abstract coming soon...

Moderator

Author:

Steven Woo

Fellow and Distinguished Inventor
Rambus


I was drawn to Rambus to focus on cutting edge computing technologies. Throughout my 15+ year career, I’ve helped invent, create and develop means of driving and extending performance in both hardware and software solutions. At Rambus, we are solving challenges that are completely new to the industry and occur as a response to deployments that are highly sophisticated and advanced.

As an inventor, I find myself approaching a challenge like a room filled with 100,000 pieces of a puzzle where it is my job to figure out how they all go together – without knowing what it is supposed to look like in the end. For me, the job of finishing the puzzle is as enjoyable as the actual process of coming up with a new, innovative solution.

For example, RDRAM®, our first mainstream memory architecture, implemented in hundreds of millions of consumer, computing and networking products from leading electronics companies including Cisco, Dell, Hitachi, HP, Intel, etc. We did a lot of novel things that required inventiveness – we pushed the envelope and created state of the art performance without making actual changes to the infrastructure.

I’m excited about the new opportunities as computing is becoming more and more pervasive in our everyday lives. With a world full of data, my job and my fellow inventors’ job will be to stay curious, maintain an inquisitive approach and create solutions that are technologically superior and that seamlessly intertwine with our daily lives.

After an inspiring work day at Rambus, I enjoy spending time with my family, being outdoors, swimming, and reading.

Education

  • Ph.D., Electrical Engineering, Stanford University
  • M.S. Electrical Engineering, Stanford University
  • Master of Engineering, Harvey Mudd College
  • B.S. Engineering, Harvey Mudd College
... read more

Steven Woo

Fellow and Distinguished Inventor
Rambus


I was drawn to Rambus to focus on cutting edge computing technologies. Throughout my 15+ year career, I’ve helped invent, create and develop means of driving and extending performance in both hardware and software solutions. At Rambus, we are solving challenges that are completely new to the industry and occur as a response to deployments that are highly sophisticated and advanced.

As an inventor, I find myself approaching a challenge like a room filled with 100,000 pieces of a puzzle where it is my job to figure out how they all go together – without knowing what it is supposed to look like in the end. For me, the job of finishing the puzzle is as enjoyable as the actual process of coming up with a new, innovative solution.

For example, RDRAM®, our first mainstream memory architecture, implemented in hundreds of millions of consumer, computing and networking products from leading electronics companies including Cisco, Dell, Hitachi, HP, Intel, etc. We did a lot of novel things that required inventiveness – we pushed the envelope and created state of the art performance without making actual changes to the infrastructure.

I’m excited about the new opportunities as computing is becoming more and more pervasive in our everyday lives. With a world full of data, my job and my fellow inventors’ job will be to stay curious, maintain an inquisitive approach and create solutions that are technologically superior and that seamlessly intertwine with our daily lives.

After an inspiring work day at Rambus, I enjoy spending time with my family, being outdoors, swimming, and reading.

Education

  • Ph.D., Electrical Engineering, Stanford University
  • M.S. Electrical Engineering, Stanford University
  • Master of Engineering, Harvey Mudd College
  • B.S. Engineering, Harvey Mudd College
Panellists

Author:

David Kanter

Founder & Executive Director
MLCommons

David founded and leads MLCommons, to make machine learning better for everyone through benchmarks, such as MLPerf, and building datasets and tools for data-centric AI.

The mission of MLCommons™ is to make machine learning better for everyone. Together with its 50+ founding Members and Affiliates, including startups, leading companies, academics, and non-profits from around the globe, MLCommons will help grow machine learning from a research field into a mature industry through benchmarks, public datasets and best practices. MLCommons firmly believes in the power of open-source and open data. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.

... read more

David Kanter

Founder & Executive Director
MLCommons

David founded and leads MLCommons, to make machine learning better for everyone through benchmarks, such as MLPerf, and building datasets and tools for data-centric AI.

The mission of MLCommons™ is to make machine learning better for everyone. Together with its 50+ founding Members and Affiliates, including startups, leading companies, academics, and non-profits from around the globe, MLCommons will help grow machine learning from a research field into a mature industry through benchmarks, public datasets and best practices. MLCommons firmly believes in the power of open-source and open data. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.

PANEL

Abstract coming soon...

Author:

Bryan McCann

Co-Founder & CTO
You.com

Bryan is a Co-Founder and the CTO of You.com. Prior to You.com, Bryan was a Lead Research Scientist at Salesforce Research working on Deep Learning and its applications to Natural Language Processing (NLP).


He authored the first paper and holds the patent on contextualized word vectors, which eventually led to the transfer learning revolution in NLP with BERT and other transformer-based architectures for contextualized word vectors. He was the recipient of the 1st ever eVe award at SXSW 2021 for his collaboration with award-winning (and Netflix show writing) author Daniel Kehlmann. He is a regular speaker on topics of literature and AI, poetry and AI, and other crossovers between AI and the arts.

... read more

Bryan McCann

Co-Founder & CTO
You.com

Bryan is a Co-Founder and the CTO of You.com. Prior to You.com, Bryan was a Lead Research Scientist at Salesforce Research working on Deep Learning and its applications to Natural Language Processing (NLP).


He authored the first paper and holds the patent on contextualized word vectors, which eventually led to the transfer learning revolution in NLP with BERT and other transformer-based architectures for contextualized word vectors. He was the recipient of the 1st ever eVe award at SXSW 2021 for his collaboration with award-winning (and Netflix show writing) author Daniel Kehlmann. He is a regular speaker on topics of literature and AI, poetry and AI, and other crossovers between AI and the arts.

Author:

Sravanthi Rajanala

Director, Machine Learning & Search
Walmart Tech

Sravanthi Rajanala is the Director of Data Science and Machine Learning in Walmart's Search Technologies. She began her career in telecom and worked for Microsoft and Nokia before joining Bing Search in 2011 to work in machine learning and search. Sravanthi has led initiatives in query and document understanding, ranking, and question answering. In 2021, she joined Walmart and now leads the Search Core Algorithms, Machine Translation, and Metrics Science. Sravanthi holds a Master's degree in Computational Science from the Indian Institute of Science and a Bachelor's degree in Computer Science from Osmania University.

... read more

Sravanthi Rajanala

Director, Machine Learning & Search
Walmart Tech

Sravanthi Rajanala is the Director of Data Science and Machine Learning in Walmart's Search Technologies. She began her career in telecom and worked for Microsoft and Nokia before joining Bing Search in 2011 to work in machine learning and search. Sravanthi has led initiatives in query and document understanding, ranking, and question answering. In 2021, she joined Walmart and now leads the Search Core Algorithms, Machine Translation, and Metrics Science. Sravanthi holds a Master's degree in Computational Science from the Indian Institute of Science and a Bachelor's degree in Computer Science from Osmania University.

Author:

Selcuk Kopru

Director, Engineering & Research, Search
eBay

Selcuk Kopru is Head of ML & NLP at eBay and is an experienced AI leader with proven expertise in creating and deploying cutting edge NLP and AI technologies and systems. He is experienced in developing scalable Machine Learning solutions to solve big data problems that involve text and multimodal data. He is also skilled in Python, Java, C++, Machine Translation and Pattern Recognition. Selcuk is also a strong research professional with a Doctor of Philosophy (PhD) in NLP in Computer Science from Middle East Technical University.

... read more

Selcuk Kopru

Director, Engineering & Research, Search
eBay

Selcuk Kopru is Head of ML & NLP at eBay and is an experienced AI leader with proven expertise in creating and deploying cutting edge NLP and AI technologies and systems. He is experienced in developing scalable Machine Learning solutions to solve big data problems that involve text and multimodal data. He is also skilled in Python, Java, C++, Machine Translation and Pattern Recognition. Selcuk is also a strong research professional with a Doctor of Philosophy (PhD) in NLP in Computer Science from Middle East Technical University.

As cars become increasingly electrified, and digitized, more advanced electronics are needed. This means we will be using more chips within the vehicle, an extreme environment where reliability is challenged, and where safety is paramount.  

This brings new challenges in lifetime reliability, requiring Performance degradation monitoring, Time-to-failure prediction, Mission profile validation with usage feedback and Advanced root cause analysis.  

Using ML and data analytics, mobility companies can Increase reliability and safety.  

Meeting the safety and performance demands of software-defined, electric and autonomous automotive architectures is a grave challenge, one that is keeping the electronics industry busy with innovation. Questions around SOC / ECU useful life, mission profiling, failure prevention and prescriptive maintenance are being addressed with new data sources and adaptive software approaches.   

This panel will explore the critical role of machine learning (ML) in achieving reliability and functional safety (FuSa) in automotive chips. It will discuss the current state of ML in automotive chip safety, the opportunities and challenges associated with its use, and potential solutions for ensuring optimized operation of advanced electronics in cars. 

The panel will further discuss a hybrid strategy of leveraging traditional approaches and new data sources to meet business objectives (availability, cost, power). By introducing new architectures that connect edge to cloud, HW to SW, production to usage, and telemetry to analytics, ML-driven data serves as a basis for fleet management and optimization, with powerful loop back mechanisms.  

Moderator

Author:

Nitza Basoco

VP, Business Development
proteanTecs

Nitza Basoco is a technology leader with over 20 years of semiconductor experience. At proteanTecs, she leads the Business Development team, responsible for driving partnership strategies and building value-add ecosystem growth. 

Previously, Nitza was the VP of Operations at Synaptics with responsibility for growing and scaling their worldwide test development, product engineering and manufacturing departments. Prior to Synaptics, Nitza spent a decade holding various leadership positions within the operations organization at MaxLinear, ranging from test development engineering to supply chain. Earlier in her career, Nitza served as a Principal Test Development Engineer for Broadcom Corporation and as a Broadband Applications Engineer at Teradyne.  

Nitza holds MEng and BSEE degrees from Massachusetts Institute of Technology.

... read more

Nitza Basoco

VP, Business Development
proteanTecs

Nitza Basoco is a technology leader with over 20 years of semiconductor experience. At proteanTecs, she leads the Business Development team, responsible for driving partnership strategies and building value-add ecosystem growth. 

Previously, Nitza was the VP of Operations at Synaptics with responsibility for growing and scaling their worldwide test development, product engineering and manufacturing departments. Prior to Synaptics, Nitza spent a decade holding various leadership positions within the operations organization at MaxLinear, ranging from test development engineering to supply chain. Earlier in her career, Nitza served as a Principal Test Development Engineer for Broadcom Corporation and as a Broadband Applications Engineer at Teradyne.  

Nitza holds MEng and BSEE degrees from Massachusetts Institute of Technology.

NETWORKING BREAK
PRESENTATION

Abstract coming soon...

Author:

Martin Ruskowski

Chairman, Department of Machine Tools and Control Systems
RPTU Kaiserslautern-Landau

Professor Dr. Martin Ruskowski took over the position as Head of the renamed Institute of Machine Tools and System Controls (WSKL) on June 1, 2017. His major research focus is on industrial robots as machine tools, artificial intelligence in automation technology, and the development of innovative control concepts for automation.

All equipment and machinery in the factories of tomorrow will be networked: Machines will have the ability to communicate and exchange data among themselves. Robots will continue to play an ever greater role in the world of Industrie 4.0. In the future, they may even replace traditional machine tools is some application situations, for example, in the milling of special components. "A priority of my work at TU Kaiserslautern and DFKI will be to improve the fitness of robots for demanding mechanical processing tasks. The new technologies that result from our research will provide more flexibility to companies and, ultimately, serve as a jobs motor in Germany," said Ruskowski in describing his new responsibilities.

Ruskowski is an expert in the fields of robotics and Industry 4.0. At DFKI and RPTU, his aim will be to develop solutions for the digitalization of production plants while also working on new control systems and robot mechanics to increase the efficiency of future generations of industrial robots. He will also study the question of how to make self-optimizing machines. A major focus is on Human-Machine Interaction in automated production plants. "In the context of the digitalization of production, we need new engineering techniques that will allow humans to more closely integrate the production processes," he added. "We can achieve this in cooperation with Technologie-Initiative SmartFactory KL e.V." This unique research lab located at DFKI provides ideal conditions for the practical evaluation of ambitious research projects.In addition, Ruskowski will hold a series of lectures at the department of Mechanical and Process Engineering on the subjects of machine tools and industrial robotics.

He studied electrical engineering at Leibniz University Hannover and also received his doctorate in mechanical engineering there. His doctoral thesis was a study of the dynamics of machine tools and the use active magnet guides for damping vibrations. Prior to his relocation to Kaiserslautern, Ruskowski held several management positions at industrial firms, most recently since 2015 as Vice President for Global Research and Development at KUKA Industries.

 

... read more

Martin Ruskowski

Chairman, Department of Machine Tools and Control Systems
RPTU Kaiserslautern-Landau

Professor Dr. Martin Ruskowski took over the position as Head of the renamed Institute of Machine Tools and System Controls (WSKL) on June 1, 2017. His major research focus is on industrial robots as machine tools, artificial intelligence in automation technology, and the development of innovative control concepts for automation.

All equipment and machinery in the factories of tomorrow will be networked: Machines will have the ability to communicate and exchange data among themselves. Robots will continue to play an ever greater role in the world of Industrie 4.0. In the future, they may even replace traditional machine tools is some application situations, for example, in the milling of special components. "A priority of my work at TU Kaiserslautern and DFKI will be to improve the fitness of robots for demanding mechanical processing tasks. The new technologies that result from our research will provide more flexibility to companies and, ultimately, serve as a jobs motor in Germany," said Ruskowski in describing his new responsibilities.

Ruskowski is an expert in the fields of robotics and Industry 4.0. At DFKI and RPTU, his aim will be to develop solutions for the digitalization of production plants while also working on new control systems and robot mechanics to increase the efficiency of future generations of industrial robots. He will also study the question of how to make self-optimizing machines. A major focus is on Human-Machine Interaction in automated production plants. "In the context of the digitalization of production, we need new engineering techniques that will allow humans to more closely integrate the production processes," he added. "We can achieve this in cooperation with Technologie-Initiative SmartFactory KL e.V." This unique research lab located at DFKI provides ideal conditions for the practical evaluation of ambitious research projects.In addition, Ruskowski will hold a series of lectures at the department of Mechanical and Process Engineering on the subjects of machine tools and industrial robotics.

He studied electrical engineering at Leibniz University Hannover and also received his doctorate in mechanical engineering there. His doctoral thesis was a study of the dynamics of machine tools and the use active magnet guides for damping vibrations. Prior to his relocation to Kaiserslautern, Ruskowski held several management positions at industrial firms, most recently since 2015 as Vice President for Global Research and Development at KUKA Industries.

 

Author:

Tatjana Legler

Deputy Head of Department
RPTU Kaiserslautern-Landau

Tatjana Legler studied mechanical engineering at the Technical University of Kaiserslautern. She wrote her master thesis on "Optimization of automated visual inspection of common rails using neural networks". She has been working at the Department of Machine Tools and Control Systems since November 2017.

Research Fields

Tatjana Legler deals with the use of artificial intelligence in the production environment. This includes, for example, the analysis of process data for the prediction of product quality and federated learning.

... read more

Tatjana Legler

Deputy Head of Department
RPTU Kaiserslautern-Landau

Tatjana Legler studied mechanical engineering at the Technical University of Kaiserslautern. She wrote her master thesis on "Optimization of automated visual inspection of common rails using neural networks". She has been working at the Department of Machine Tools and Control Systems since November 2017.

Research Fields

Tatjana Legler deals with the use of artificial intelligence in the production environment. This includes, for example, the analysis of process data for the prediction of product quality and federated learning.

Abstract coming soon...

Author:

Matthew Burns

Technical Marketing Manager
Samtec

Matthew Burns develops go-to-market strategies for Samtec’s Silicon-to-Silicon solutions. Over the course of 20+ years, he has been a leader in design, applications engineering, technical sales and marketing in the telecommunications, medical and electronic components industries. Mr. Burns holds a B.S. in Electrical Engineering from Penn State University.

... read more

Matthew Burns

Technical Marketing Manager
Samtec

Matthew Burns develops go-to-market strategies for Samtec’s Silicon-to-Silicon solutions. Over the course of 20+ years, he has been a leader in design, applications engineering, technical sales and marketing in the telecommunications, medical and electronic components industries. Mr. Burns holds a B.S. in Electrical Engineering from Penn State University.

PRESENTATION

Author:

Girish Nadkarni

Director, Charles Bronfman Institute of Personalized Medicine
Icahn School of Medicine Mt. Sinai

Girish N. Nadkarni, MD, MPH, is the Irene and Dr. Arthur M. Fishberg Professor of Medicine at the Icahn School of Medicine at Mount Sinai. As an expert physician-scientist, Dr. Nadkarni bridges the gap between comprehensive clinical care and innovative research. He is the System Chief of the Division of Data Driven and Digital Medicine (D3M), the Co-Director of the Mount Sinai Clinical Intelligence Center (MSCIC) and the Director of  Charles Bronfman Institute for Personalized Medicine. 

Before completing his medical degree at one of the top-ranked medical colleges in India, Dr. Nadkarni received training in mathematics. He then received a master’s degree in public health at the Johns Hopkins Bloomberg School of Public Health, and then was a research associate at the Johns Hopkins Medical Institute. Dr. Nadkarni completed his residency in internal medicine and his clinical fellowship in nephrology at the Icahn School of Medicine at Mount Sinai. He then completed a research fellowship in personalized medicine and informatics. 

Dr. Nadkarni has authored more than 240 peer-reviewed scientific publications, including articles in the New England Journal of Medicine, the Journal of the American Medical Association, the Annals of Internal Medicine and Nature Medicine. Dr. Nadkarni is the principal or co-investigator for several grants funded by the National Institutes of Health focusing on informatics, data science, and precision medicine. He is also one of the multiple principal investigators of the NIH RECOVER consortium focusing on the long-term sequelae of COVID-19. He has several patents and is also the scientific co-founder of investor-backed companies—one of which, Renalytix, is listed on NASDAQ. In recognition of his work as an active clinician and investigator, he has received several awards and honors, including the Dr. Harold and Golden Lamport Research Award, the Deal of the Year award from Mount Sinai Innovation Partners, the Carl Nacht Memorial Lecture, and the Rising Star Award from ANIO.

... read more

Girish Nadkarni

Director, Charles Bronfman Institute of Personalized Medicine
Icahn School of Medicine Mt. Sinai

Girish N. Nadkarni, MD, MPH, is the Irene and Dr. Arthur M. Fishberg Professor of Medicine at the Icahn School of Medicine at Mount Sinai. As an expert physician-scientist, Dr. Nadkarni bridges the gap between comprehensive clinical care and innovative research. He is the System Chief of the Division of Data Driven and Digital Medicine (D3M), the Co-Director of the Mount Sinai Clinical Intelligence Center (MSCIC) and the Director of  Charles Bronfman Institute for Personalized Medicine. 

Before completing his medical degree at one of the top-ranked medical colleges in India, Dr. Nadkarni received training in mathematics. He then received a master’s degree in public health at the Johns Hopkins Bloomberg School of Public Health, and then was a research associate at the Johns Hopkins Medical Institute. Dr. Nadkarni completed his residency in internal medicine and his clinical fellowship in nephrology at the Icahn School of Medicine at Mount Sinai. He then completed a research fellowship in personalized medicine and informatics. 

Dr. Nadkarni has authored more than 240 peer-reviewed scientific publications, including articles in the New England Journal of Medicine, the Journal of the American Medical Association, the Annals of Internal Medicine and Nature Medicine. Dr. Nadkarni is the principal or co-investigator for several grants funded by the National Institutes of Health focusing on informatics, data science, and precision medicine. He is also one of the multiple principal investigators of the NIH RECOVER consortium focusing on the long-term sequelae of COVID-19. He has several patents and is also the scientific co-founder of investor-backed companies—one of which, Renalytix, is listed on NASDAQ. In recognition of his work as an active clinician and investigator, he has received several awards and honors, including the Dr. Harold and Golden Lamport Research Award, the Deal of the Year award from Mount Sinai Innovation Partners, the Carl Nacht Memorial Lecture, and the Rising Star Award from ANIO.

Abstract coming soon...

Author:

Drew Matter

Vice President
Mikros Technologies

Drew Matter serves as Vice President at Mikros Technologies, a premier designer and manufacturer of DLC single-phase and 2-phase cold plates and loops.  Mikros works closely with AI/ML system designers to provide highly-optimized thermal management solutions with industry-leading heat transfer performance to improve the power, performance, packaging, reliability and sustainability of their systems.

... read more

Drew Matter

Vice President
Mikros Technologies

Drew Matter serves as Vice President at Mikros Technologies, a premier designer and manufacturer of DLC single-phase and 2-phase cold plates and loops.  Mikros works closely with AI/ML system designers to provide highly-optimized thermal management solutions with industry-leading heat transfer performance to improve the power, performance, packaging, reliability and sustainability of their systems.

PRESENTATION
MODERATED ROUNDTABLE DISCUSSION GROUPS

Join this moderated roundtable discussion group of 10-20 attendees focusing on novel training and learning paradigms for ML. 

There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.

The subtopics to be discussed will include:

- Limitations of current training architectures and paradigms
- Use cases and challenges for distributed learning (i.e. federated learning)
- Data centric AI + few & low shot learning methods for efficient training
- Datasets for ML training - Open Source options

Join this moderated roundtable discussion group of 10-20 attendees focusing on selecting ML training platforms for specific use cases. 

There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.

The subtopics to be discussed will include:

- GPUs vs ASICS vs commodity hardware (i.e. software-accelerated CPUs)
- Considerations for efficient training of training large language models
- Fitting workloads to training hardware - overcoming issues with memory etc.
- Software considerations for novel AI hardware training platforms

Join this moderated roundtable discussion group of 10-20 attendees focusing on AI hardware & systems design.

There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.

The subtopics to be discussed will include:

- Tackling power consumption for AI hardware
- Memory bandwidth and capacity challenges and solutions
- AI hardware & systems co-design
- System software engineering challenges for novel AI hardware

Wednesday, 13 Sep, 2023
DAY 2 - SERVER TO EDGE: DEPLOYMENT AND INFERENCE/SERVING
REGISTRATION & MORNING NETWORKING
OPENING KEYNOTE

Abstract coming soon...

Author:

Alexis Black Bjorlin

VP, Infrastructure Hardware
Meta

Dr. Alexis Black Bjorlin is VP, Infrastructure Hardware Engineering at Meta. She also serves on the board of directors at Digital Realty and Celestial AI. Prior to Meta, Dr. Bjorlin was Senior Vice President and General Manager of Broadcom’s Optical Systems Division and previously Corporate Vice President of the Data Center Group and General Manager of the Connectivity Group at Intel. Prior to Intel, she spent eight years as President of Source Photonics, where she also served on the board of directors. She earned a B.S. in Materials Science and Engineering from Massachusetts Institute of Technology and a Ph.D. in Materials Science from the University of California at Santa Barbara.

... read more

Alexis Black Bjorlin

VP, Infrastructure Hardware
Meta

Dr. Alexis Black Bjorlin is VP, Infrastructure Hardware Engineering at Meta. She also serves on the board of directors at Digital Realty and Celestial AI. Prior to Meta, Dr. Bjorlin was Senior Vice President and General Manager of Broadcom’s Optical Systems Division and previously Corporate Vice President of the Data Center Group and General Manager of the Connectivity Group at Intel. Prior to Intel, she spent eight years as President of Source Photonics, where she also served on the board of directors. She earned a B.S. in Materials Science and Engineering from Massachusetts Institute of Technology and a Ph.D. in Materials Science from the University of California at Santa Barbara.

Author:

Petr Lapukhov

Network Engineer
Meta

Petr Lapukhov is a Network Engineer at Meta. He has 20+ years in the networking industry, designing and operating large scale networks. He has a depth of experience in developing and operating software for network control and monitoring. His past experience includes CCIE/CCDE training and UNIX system administration.

... read more

Petr Lapukhov

Network Engineer
Meta

Petr Lapukhov is a Network Engineer at Meta. He has 20+ years in the networking industry, designing and operating large scale networks. He has a depth of experience in developing and operating software for network control and monitoring. His past experience includes CCIE/CCDE training and UNIX system administration.

KEYNOTE

Every electronic system you know is either going to get smarter or get replaced.  AI is allowing us to solve a new set of problems just recently thought of as impossible.  The challenge that we have is to make AI work, not just in the data center, but in all the systems we use and interact with on a daily basis.  These systems vary from a Falcon Heavy Rocket to a smart contact lens.  Some have kilowatts of power available, others not even a microwatt.  The AI systems we deliver must meet a vast range of requirements and work in all kinds of environments.   

 

Because AI is computationally very complex, using an average off-the-shelf MPU just isn’t going to get the job done.  Mo Movahed will describe how you can design the next generation of intelligent systems to surpass these challenges.  

At the same time, these systems are often placed in situations where they must work all the time, with no disruptions in service. Ankur Gupta will describe how you can use embedded analytics to design AI systems at the edge that operate reliably, safely, and securely.  

Author:

Ankur Gupta

VP & GM, Tessent
Siemens EDA

Ankur Gupta is vice president and general manager of Tessent Silicon Lifecycle Solutions business unit for Siemens EDA. He and his global team are responsible for developing and marketing best-in-class DFT and Lifecycle solutions for the Semiconductor industry.

Ankur brings 20+ years of experience in Digital design, implementation and signoff. He oversaw the first five deployments of Innovus to the market, while at Cadence. Later, at Ansys, he oversaw the launch and deployment of RedHawk-SC, a market leader in power-grid signoff.

... read more

Ankur Gupta

VP & GM, Tessent
Siemens EDA

Ankur Gupta is vice president and general manager of Tessent Silicon Lifecycle Solutions business unit for Siemens EDA. He and his global team are responsible for developing and marketing best-in-class DFT and Lifecycle solutions for the Semiconductor industry.

Ankur brings 20+ years of experience in Digital design, implementation and signoff. He oversaw the first five deployments of Innovus to the market, while at Cadence. Later, at Ansys, he oversaw the launch and deployment of RedHawk-SC, a market leader in power-grid signoff.

Author:

Mo Movahed

GM, CSD Division
Siemens Digital Industry Software

MO Movahed is the GM for CSD division at Siemens, responsible for High-Level Synthesis and Verification, Low-Power Solutions and FPGA Synthesis.

MO has more than 35 years of products and business experience with broad background and expertise in design verification & implementation tools and methodology. Prior to joining Siemens EDA, he held various VP positions at Synopsys where he led Digital Verification products & business including VCS, VC Static, SpyGlass, VC Formal & Emulation Power in Verification BU, and StarRC, PrimePower Gate and RTL, and PrimeECO products in Digital Implementation BU.

Prior to Synopsys, Mo was SVP at Atrenta and led innovation of industry leading SpyGlass products & solutions and was heavily involved with the growth of Atrenta from both customer & business perspective resulting in successful acquisition by Synopsys in 2015.  MO has held leadership positions at Lattice Semi, Cadence, and Xerox Research Lab and holds 15+ US Patents. 

... read more

Mo Movahed

GM, CSD Division
Siemens Digital Industry Software

MO Movahed is the GM for CSD division at Siemens, responsible for High-Level Synthesis and Verification, Low-Power Solutions and FPGA Synthesis.

MO has more than 35 years of products and business experience with broad background and expertise in design verification & implementation tools and methodology. Prior to joining Siemens EDA, he held various VP positions at Synopsys where he led Digital Verification products & business including VCS, VC Static, SpyGlass, VC Formal & Emulation Power in Verification BU, and StarRC, PrimePower Gate and RTL, and PrimeECO products in Digital Implementation BU.

Prior to Synopsys, Mo was SVP at Atrenta and led innovation of industry leading SpyGlass products & solutions and was heavily involved with the growth of Atrenta from both customer & business perspective resulting in successful acquisition by Synopsys in 2015.  MO has held leadership positions at Lattice Semi, Cadence, and Xerox Research Lab and holds 15+ US Patents. 

KEYNOTE

Abstract coming soon...

Author:

David Glasco

VP, Tensilica IP Group
Cadence
... read more

David Glasco

VP, Tensilica IP Group
Cadence
NETWORKING LUNCH
PRESENTATION

Abstract coming soon...

Author:

Suqiang Song

Engineering Director, Data Platform & ML Infrastructure
Airbnb

As engineering director, Suqiang leads multiple teams of ML infrastructure engineers, driving machine learning platforms and infrastructure solutions for all product and engineering teams in Airbnb.

As a senior AI leader, he works closely with senior partners in product and engineering to shape Airbnb’s vision in AI and ML, streamline innovations, and ensure Airbnb has a complete set of AI infrastructure that meets long-term needs.

Previously, Suqiang served as Vice President, Data Platforms and Engineering Services at Mastercard, as one of the Data / AI commit board members to identify strategies and directions for Data Enablement, Data and ML platforms across multiple product lines and multiple deployment infrastructures. He has led worldwide engineering teams of data engineers, Machine Learning engineers, and data analysts to build unified data and ML platforms both on-premise and on-cloud for Mastercard

... read more

Suqiang Song

Engineering Director, Data Platform & ML Infrastructure
Airbnb

As engineering director, Suqiang leads multiple teams of ML infrastructure engineers, driving machine learning platforms and infrastructure solutions for all product and engineering teams in Airbnb.

As a senior AI leader, he works closely with senior partners in product and engineering to shape Airbnb’s vision in AI and ML, streamline innovations, and ensure Airbnb has a complete set of AI infrastructure that meets long-term needs.

Previously, Suqiang served as Vice President, Data Platforms and Engineering Services at Mastercard, as one of the Data / AI commit board members to identify strategies and directions for Data Enablement, Data and ML platforms across multiple product lines and multiple deployment infrastructures. He has led worldwide engineering teams of data engineers, Machine Learning engineers, and data analysts to build unified data and ML platforms both on-premise and on-cloud for Mastercard

Author:

Prasad Saripalli

Distinguished Engineer
Capital One

Prasad Saripalli serves as a Distinguished Engineer at Capital One, a technology driven bank on the Fortune 100 list, redefining Fintech and Banking using data, technology, AI and ML in unprecedented ways. Most recently, Prasad served as the Vice President of AIML and Distinguished Engineer at MindBody Inc - a portfolio company of Vista which manages the world's fourth-largest enterprise software company after Microsoft, Oracle, and SAP. Earlier, he served as VP Data Science at Edifecs, an industry premier healthcare information technology partnership platform and software provider, building Smart Decisions ML & AI Platform with Ml Apps Front. Prior to this, Prasad served as CTO and VP Engineering at Secrata.com, provider of Military grade Security and Privacy solutions developed and deployed over the past 15 years at Topia Technology for the Federal Government and the Enterprise, and as CTO & EVP at ClipCard, a SaaS based Hierarchical Analytics and Visualization platform.

At IBM, Prasad served as the Chief Architect for IBM's SmartCloud Enterprise (http://www.ibm.com/cloud-computing/us/en/). At Runaware, he served as the Vice President of Product Development. As a Principal Group Manager at Microsoft, Prasad co-led the development of virtualization stack on Windows 7 responsible for shipping Virtual PC7 and Windows XP Mode on Windows 7.


Prasad teaches Machine Learning, AI, NLP, Distributed Systems, Cloud Engineering and Robotics at Northeastern University and the University of Washington Continuum College.

... read more

Prasad Saripalli

Distinguished Engineer
Capital One

Prasad Saripalli serves as a Distinguished Engineer at Capital One, a technology driven bank on the Fortune 100 list, redefining Fintech and Banking using data, technology, AI and ML in unprecedented ways. Most recently, Prasad served as the Vice President of AIML and Distinguished Engineer at MindBody Inc - a portfolio company of Vista which manages the world's fourth-largest enterprise software company after Microsoft, Oracle, and SAP. Earlier, he served as VP Data Science at Edifecs, an industry premier healthcare information technology partnership platform and software provider, building Smart Decisions ML & AI Platform with Ml Apps Front. Prior to this, Prasad served as CTO and VP Engineering at Secrata.com, provider of Military grade Security and Privacy solutions developed and deployed over the past 15 years at Topia Technology for the Federal Government and the Enterprise, and as CTO & EVP at ClipCard, a SaaS based Hierarchical Analytics and Visualization platform.

At IBM, Prasad served as the Chief Architect for IBM's SmartCloud Enterprise (http://www.ibm.com/cloud-computing/us/en/). At Runaware, he served as the Vice President of Product Development. As a Principal Group Manager at Microsoft, Prasad co-led the development of virtualization stack on Windows 7 responsible for shipping Virtual PC7 and Windows XP Mode on Windows 7.


Prasad teaches Machine Learning, AI, NLP, Distributed Systems, Cloud Engineering and Robotics at Northeastern University and the University of Washington Continuum College.

PRESENTATION

Abstract coming soon...

Author:

Pushpak Pujari

Head of Product - Camera Software and Video Products
Verkada

Pushpak leads Product Management at Verkada where he runs their Cloud Connected Security Camera product lines. He is responsible for using AI and Computer Vision on the camera to improve video and analytics capabilities and reduce incidence response time by surfacing only meaningful events in real-time, with minimal impact on bandwidth.

Before Verkada, Pushpak led Product Management at Amazon where he built the end-to-end privacy-preserving ML platform at Amazon Alexa, and launched a no-code platform to design and deploy IoT automation workflows on edge devices at Amazon Web Services (AWS). Previous to Amazon, he spent 4 years at Sony in Japan building Sony’s flagship mirrorless cameras.

Pushpak has extensive experience of starting, running and growing multi-million dollar products used by millions of users at the fastest growing companies in the US and the world. He holds an MBA from Wharton and Bachelors in Electrical Engineering from IIT Delhi, India

... read more

Pushpak Pujari

Head of Product - Camera Software and Video Products
Verkada

Pushpak leads Product Management at Verkada where he runs their Cloud Connected Security Camera product lines. He is responsible for using AI and Computer Vision on the camera to improve video and analytics capabilities and reduce incidence response time by surfacing only meaningful events in real-time, with minimal impact on bandwidth.

Before Verkada, Pushpak led Product Management at Amazon where he built the end-to-end privacy-preserving ML platform at Amazon Alexa, and launched a no-code platform to design and deploy IoT automation workflows on edge devices at Amazon Web Services (AWS). Previous to Amazon, he spent 4 years at Sony in Japan building Sony’s flagship mirrorless cameras.

Pushpak has extensive experience of starting, running and growing multi-million dollar products used by millions of users at the fastest growing companies in the US and the world. He holds an MBA from Wharton and Bachelors in Electrical Engineering from IIT Delhi, India

Author:

Sakyasingha Dasgupta

Founder & CEO
EdgeCortix

Dr. Sakyasingha Dasgupta is the founder and CEO of Edgecortix, Inc. He is an AI and machine learning technologist, entrepreneur and engineer with real-world experience in taking cutting edge research from ideation stage to scalable products. Having worked at global companies like Microsoft, IBM Research and national research labs like RIKEN and Max Planck Institute, in his more recent roles, he has helped establish and lead technology teams at lean startups in Japan and Singapore, in robotics & automation and Fintech sectors.

After spending more than a decade in research and development in diverse areas like, brain inspired computing, robotics, computer vision, hardware acceleration for AI, wearable devices, internet of things, machine learning in finance and healthcare, Sakya founded EdgeCortix, a deep-tech startup automating machine learning driven AI hardware & software co-design for an intelligent distributed edge ecosystem.

Sakyasingha recently took part in a webinar titled "Software, The Elephant in the Room for Edge AI Hardware Acceleration" - register for free to watch on-demand here

... read more

Sakyasingha Dasgupta

Founder & CEO
EdgeCortix

Dr. Sakyasingha Dasgupta is the founder and CEO of Edgecortix, Inc. He is an AI and machine learning technologist, entrepreneur and engineer with real-world experience in taking cutting edge research from ideation stage to scalable products. Having worked at global companies like Microsoft, IBM Research and national research labs like RIKEN and Max Planck Institute, in his more recent roles, he has helped establish and lead technology teams at lean startups in Japan and Singapore, in robotics & automation and Fintech sectors.

After spending more than a decade in research and development in diverse areas like, brain inspired computing, robotics, computer vision, hardware acceleration for AI, wearable devices, internet of things, machine learning in finance and healthcare, Sakya founded EdgeCortix, a deep-tech startup automating machine learning driven AI hardware & software co-design for an intelligent distributed edge ecosystem.

Sakyasingha recently took part in a webinar titled "Software, The Elephant in the Room for Edge AI Hardware Acceleration" - register for free to watch on-demand here

PRESENTATION

Author:

Arun Iyengar

CEO
Untether AI

Arun Iyengar is the CEO of Untether AI. He brings to Untether AI extensive operational and general management experience across a variety of markets from automotive, cloud, to wired and wireless infrastructure. Prior to Untether AI, Iyengar held leadership roles at Xilinx, AMD, and Altera where he set and executed strategies to grow revenues in each of the targeted markets.

... read more

Arun Iyengar

CEO
Untether AI

Arun Iyengar is the CEO of Untether AI. He brings to Untether AI extensive operational and general management experience across a variety of markets from automotive, cloud, to wired and wireless infrastructure. Prior to Untether AI, Iyengar held leadership roles at Xilinx, AMD, and Altera where he set and executed strategies to grow revenues in each of the targeted markets.

NETWORKING BREAK
PANEL

Abstract coming soon...

Author:

Nikhil Gulati

VP, Engineering & Product Strategy
Baker Hughes
... read more

Nikhil Gulati

VP, Engineering & Product Strategy
Baker Hughes

Author:

Jaya Kawale

VP of Engineering, AI/ML
Tubi

Jaya Kawale is the head of Machine Learning at Tubi, a Fox Corporation content platform. Jaya´s team works on solving various ML problems for Tubi´s product, ranging from recommendations, content understanding and acquisition, ads ML, etc. Her team also work on the application of cutting edge machine learning technologies such as contextual bandits, deep learning, computer vision and NLP to improve user experience at Tubi.

... read more

Jaya Kawale

VP of Engineering, AI/ML
Tubi

Jaya Kawale is the head of Machine Learning at Tubi, a Fox Corporation content platform. Jaya´s team works on solving various ML problems for Tubi´s product, ranging from recommendations, content understanding and acquisition, ads ML, etc. Her team also work on the application of cutting edge machine learning technologies such as contextual bandits, deep learning, computer vision and NLP to improve user experience at Tubi.

Author:

Julius Lo

Director
NEUCHIPS

Julius is a Director of NEUCHIPS, an AI ASIC startup for recommendation inferencing. Julius leads NEUCHIPS software team, covering server integration to on-board firmware. Before NEUCHIPS, Julius worked for Global Unchip Corp., hTC and Mediatek, devoting himself to RTL circuit design, Linux device drivers and performance optimization with power balancing in 20+ chips. He is an author of 6+ international patents in the areas of schedulgin and data compression.

... read more

Julius Lo

Director
NEUCHIPS

Julius is a Director of NEUCHIPS, an AI ASIC startup for recommendation inferencing. Julius leads NEUCHIPS software team, covering server integration to on-board firmware. Before NEUCHIPS, Julius worked for Global Unchip Corp., hTC and Mediatek, devoting himself to RTL circuit design, Linux device drivers and performance optimization with power balancing in 20+ chips. He is an author of 6+ international patents in the areas of schedulgin and data compression.

PANEL

Author:

Gayathri Radhakrishnan

Partner
Hitachi Ventures

Gayathri is currently Partner at Hitachi Ventures. Prior to that, she was with Micron Ventures, actively investing in startups that apply AI to solve critical problems in the areas of Manufacturing, Healthcare and Automotive. She brings over 20 years of multi-disciplinary experience across product management, product marketing, corporate strategy, M&A and venture investments in large Fortune 500 companies such as Dell and Corning and in startups. She has also worked as an early stage investor at Earlybird Venture Capital, a premier European venture capital fund based in Germany. She has a Masters in EE from The Ohio State University and MBA from INSEAD in France. She is also a Kauffman Fellow - Class 16.

... read more

Gayathri Radhakrishnan

Partner
Hitachi Ventures

Gayathri is currently Partner at Hitachi Ventures. Prior to that, she was with Micron Ventures, actively investing in startups that apply AI to solve critical problems in the areas of Manufacturing, Healthcare and Automotive. She brings over 20 years of multi-disciplinary experience across product management, product marketing, corporate strategy, M&A and venture investments in large Fortune 500 companies such as Dell and Corning and in startups. She has also worked as an early stage investor at Earlybird Venture Capital, a premier European venture capital fund based in Germany. She has a Masters in EE from The Ohio State University and MBA from INSEAD in France. She is also a Kauffman Fellow - Class 16.

Author:

Sakyasingha Dasgupta

Founder & CEO
EdgeCortix

Dr. Sakyasingha Dasgupta is the founder and CEO of Edgecortix, Inc. He is an AI and machine learning technologist, entrepreneur and engineer with real-world experience in taking cutting edge research from ideation stage to scalable products. Having worked at global companies like Microsoft, IBM Research and national research labs like RIKEN and Max Planck Institute, in his more recent roles, he has helped establish and lead technology teams at lean startups in Japan and Singapore, in robotics & automation and Fintech sectors.

After spending more than a decade in research and development in diverse areas like, brain inspired computing, robotics, computer vision, hardware acceleration for AI, wearable devices, internet of things, machine learning in finance and healthcare, Sakya founded EdgeCortix, a deep-tech startup automating machine learning driven AI hardware & software co-design for an intelligent distributed edge ecosystem.

Sakyasingha recently took part in a webinar titled "Software, The Elephant in the Room for Edge AI Hardware Acceleration" - register for free to watch on-demand here

... read more

Sakyasingha Dasgupta

Founder & CEO
EdgeCortix

Dr. Sakyasingha Dasgupta is the founder and CEO of Edgecortix, Inc. He is an AI and machine learning technologist, entrepreneur and engineer with real-world experience in taking cutting edge research from ideation stage to scalable products. Having worked at global companies like Microsoft, IBM Research and national research labs like RIKEN and Max Planck Institute, in his more recent roles, he has helped establish and lead technology teams at lean startups in Japan and Singapore, in robotics & automation and Fintech sectors.

After spending more than a decade in research and development in diverse areas like, brain inspired computing, robotics, computer vision, hardware acceleration for AI, wearable devices, internet of things, machine learning in finance and healthcare, Sakya founded EdgeCortix, a deep-tech startup automating machine learning driven AI hardware & software co-design for an intelligent distributed edge ecosystem.

Sakyasingha recently took part in a webinar titled "Software, The Elephant in the Room for Edge AI Hardware Acceleration" - register for free to watch on-demand here

PRESENTATION
MODERATED ROUNDTABLE DISCUSSION GROUPS

Join this moderated roundtable discussion group of 10-20 attendees focusing on challenges in deploying machine learning into production.

There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.

The subtopics to be discussed will include:

- Mitigating challenges from changes between training and production infrastructure
- MLOps workflows for shortening time-to-value
- Navigating compatability, scalability and availabilty of hardware during deployment

Join this moderated roundtable discussion group of 10-20 attendees focusing on efficient cloud based ML inference.

There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.

The subtopics to be discussed will include:

- Optimizing hardware for efficient inference: balancing cost and performance
- Latency and throughput challenges in cloud-based machine learning inference
- Designing distributed systems for scalable and reliable inference

Join this moderated roundtable discussion group of 10-20 attendees focusing on efficient edge ML inference.

There will be several moderators per topic area to allow for multiple tables and questions will be prepared in advance. Each group will be multidisciplinary with representation from across the tech stack. Attendees who have registered for the event will be able to sign up for the roundtable discussion groups closer to the event, or via an AI Hardware & Edge AI Summit sales representative.

The subtopics to be discussed will include:

- Efficient edge-based inference on low-power devices: hardware and software optimizations
- Challenges of handling high-dimensional data at the edge for efficient inference
- Adapting machine learning models for low-power edge devices: balancing model accuracy and computational complexity
- Designing efficient edge-to-cloud communication protocols to minimize latency and optimize bandwidth usage

Thursday, 14 Sep, 2023
DAY 3 - SERVER TO EDGE: ML Use Cases - Case Studies & Tutorials
REGISTRATION & MORNING NETWORKING
INVITED KEYNOTE

Author:

Amin Vahdat

Fellow & VP of ML, Systems & Cloud AI
Google

Amin Vahdat is a Fellow and Vice President of Engineering at Google, where his team is responsible for delivering industry-best Machine Learning software and hardware that serves all of Google and the world, now and in the future, and Artificial Intelligence technologies that solve customers’ most pressing business challenges. He previously led the Systems and Services Infrastructure organization from 2021 until the present, and the Systems Infrastructure organization from 2019 - 2021. Until 2019, he was the area Technical Lead for the Networking organization at Google, responsible for Google's technical infrastructure roadmap in collaboration with the Compute, Storage, and Hardware organizations. 

Before joining Google, Amin was the Science Applications International Corporation (SAIC) Professor of Computer Science and Engineering at UC San Diego (UCSD) and the Director of UCSD’s Center for Networked Systems. He received his doctorate from the University of California Berkeley in computer science, and is a member of the National Academy of Engineering (NAE) and an Association for Computing Machinery (ACM) Fellow. 

Amin has been recognized with a number of awards, including the National Science Foundation (NSF) CAREER award, the UC Berkeley Distinguished EECS Alumni Award, the Alfred P. Sloan Fellowship, the Association for Computing Machinery's SIGCOMM Networking Systems Award, and the Duke University David and Janet Vaughn Teaching Award. Most recently, Amin was awarded the SIGCOMM lifetime achievement award for his contributions to data center and wide area networks.

... read more

Amin Vahdat

Fellow & VP of ML, Systems & Cloud AI
Google

Amin Vahdat is a Fellow and Vice President of Engineering at Google, where his team is responsible for delivering industry-best Machine Learning software and hardware that serves all of Google and the world, now and in the future, and Artificial Intelligence technologies that solve customers’ most pressing business challenges. He previously led the Systems and Services Infrastructure organization from 2021 until the present, and the Systems Infrastructure organization from 2019 - 2021. Until 2019, he was the area Technical Lead for the Networking organization at Google, responsible for Google's technical infrastructure roadmap in collaboration with the Compute, Storage, and Hardware organizations. 

Before joining Google, Amin was the Science Applications International Corporation (SAIC) Professor of Computer Science and Engineering at UC San Diego (UCSD) and the Director of UCSD’s Center for Networked Systems. He received his doctorate from the University of California Berkeley in computer science, and is a member of the National Academy of Engineering (NAE) and an Association for Computing Machinery (ACM) Fellow. 

Amin has been recognized with a number of awards, including the National Science Foundation (NSF) CAREER award, the UC Berkeley Distinguished EECS Alumni Award, the Alfred P. Sloan Fellowship, the Association for Computing Machinery's SIGCOMM Networking Systems Award, and the Duke University David and Janet Vaughn Teaching Award. Most recently, Amin was awarded the SIGCOMM lifetime achievement award for his contributions to data center and wide area networks.

INVITED KEYNOTE

Author:

Bratin Saha

VP & GM, ML & AI Services
Amazon

Dr. Bratin Saha is the Vice President of Machine Learning and AI services at AWS where he leads all the ML and AI services and helped build one of the fastest growing businesses in AWS history. He is an alumnus of Harvard Business School (General Management Program), Yale University (PhD Computer Science), and Indian Institute of Technology (BS Computer Science). He has more than 70 patents granted (with another 50+ pending) and more than 30 papers in conferences/journals. Prior to Amazon he worked at Nvidia and Intel leading different product groups spanning imaging, analytics, media processing, high performance computing, machine learning, and software infrastructure.

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Bratin Saha

VP & GM, ML & AI Services
Amazon

Dr. Bratin Saha is the Vice President of Machine Learning and AI services at AWS where he leads all the ML and AI services and helped build one of the fastest growing businesses in AWS history. He is an alumnus of Harvard Business School (General Management Program), Yale University (PhD Computer Science), and Indian Institute of Technology (BS Computer Science). He has more than 70 patents granted (with another 50+ pending) and more than 30 papers in conferences/journals. Prior to Amazon he worked at Nvidia and Intel leading different product groups spanning imaging, analytics, media processing, high performance computing, machine learning, and software infrastructure.

NETWORKING LUNCH
PRESENTATION
PRESENTATION

Author:

Vikas Chandra

Director, AI
Meta

Vikas Chandra is Director of AI Research at Facebook where he leads the On-device AI research focusing on AR and VR products. Prior to Facebook, he was Director of Applied Machine Learning at Arm Inc. He received his Ph.D. and M.S. degrees in Electrical and Computer Engineering from Carnegie Mellon University. He held the positions of Visiting Scholar (2011 – 2014) and Visiting Faculty (2016 - 2017) in the EE department at Stanford University. He has authored 70+ research publications and is an inventor on 40+ US and international patents. Dr. Chandra received the ACM-SIGDA Technical Leadership Award in 2009 and was invited to the 2017 Frontiers of Engineering Symposium organized by the National Academy of Engineering. He is a senior member of IEEE.

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Vikas Chandra

Director, AI
Meta

Vikas Chandra is Director of AI Research at Facebook where he leads the On-device AI research focusing on AR and VR products. Prior to Facebook, he was Director of Applied Machine Learning at Arm Inc. He received his Ph.D. and M.S. degrees in Electrical and Computer Engineering from Carnegie Mellon University. He held the positions of Visiting Scholar (2011 – 2014) and Visiting Faculty (2016 - 2017) in the EE department at Stanford University. He has authored 70+ research publications and is an inventor on 40+ US and international patents. Dr. Chandra received the ACM-SIGDA Technical Leadership Award in 2009 and was invited to the 2017 Frontiers of Engineering Symposium organized by the National Academy of Engineering. He is a senior member of IEEE.

Author:

Behnam Bastani

Senior Director, Engineering
Roblox

Behnam Bastani is Senior Director of Engineering for AI & ML at Roblox, where he is building a collaborative immersive computing platform, reaching variable computing devices over heterogeneous network conditions. He is currently overseeing adaptive engine platform and on device AI/ML at Roblox.

Behnam has 20+ years experience in building, scaling up and leveraging software, hardware and operating system organizations across multiple sites to innovate and launch new experiences on low powered consumer products. His product focus includes Graphics & AI based Rendering, Mobile Display System, Cloud Computing and on-Device AI.

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Behnam Bastani

Senior Director, Engineering
Roblox

Behnam Bastani is Senior Director of Engineering for AI & ML at Roblox, where he is building a collaborative immersive computing platform, reaching variable computing devices over heterogeneous network conditions. He is currently overseeing adaptive engine platform and on device AI/ML at Roblox.

Behnam has 20+ years experience in building, scaling up and leveraging software, hardware and operating system organizations across multiple sites to innovate and launch new experiences on low powered consumer products. His product focus includes Graphics & AI based Rendering, Mobile Display System, Cloud Computing and on-Device AI.

PANEL
NETWORKING BREAK

Author:

Sutanay Choudhury

Chief Scientist, Data Science
Pacific Northwest National Laboratory

Sutanay Choudhury is Chief Scientist, Data Sciences in Advanced Computing, Mathematics and Data division at Pacific Northwest National Laboratory, and the co-director of the Computational and Theoretical Chemistry Institute. His current research focuses on scalable graph representation learning and neural-symbolic reasoning, with applications to chemistry, medical informatics and power grid. Sutanay has more than a decade's experience in developing artificial intelligence and data analytics systems that extract, learn and search for patterns from the "complex web of things" - webs that emerge from atomistic interaction in molecular networks, to interaction between diseases, drugs and genes, or the web of human knowledge captured in knowledge bases such as Wikipedia, PubChem and SNOMED. His research has been supported by US Department of Energy, US Department of Homeland Security, DARPA and US Department of Veterans Affairs.

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Sutanay Choudhury

Chief Scientist, Data Science
Pacific Northwest National Laboratory

Sutanay Choudhury is Chief Scientist, Data Sciences in Advanced Computing, Mathematics and Data division at Pacific Northwest National Laboratory, and the co-director of the Computational and Theoretical Chemistry Institute. His current research focuses on scalable graph representation learning and neural-symbolic reasoning, with applications to chemistry, medical informatics and power grid. Sutanay has more than a decade's experience in developing artificial intelligence and data analytics systems that extract, learn and search for patterns from the "complex web of things" - webs that emerge from atomistic interaction in molecular networks, to interaction between diseases, drugs and genes, or the web of human knowledge captured in knowledge bases such as Wikipedia, PubChem and SNOMED. His research has been supported by US Department of Energy, US Department of Homeland Security, DARPA and US Department of Veterans Affairs.

PRESENTATION

Author:

Eugenio Zuccarrelli

Manager, Data Science
CVS Health

Eugenio is a Business-Focused Data Science Leader, leading the innovation efforts for several Fortune 500 companies across multiple industries, including Healthcare (CVS Health), Automotive (BMW) and Finance (Morningstar).

He is a Forbes 30 Under 30, a Fulbright Scholarship recipient and studied across MIT, Harvard and Imperial College London. Currently, he leads the innovation efforts for complex chronic care at CVS Health, the #1 Healthcare company in the world and a Fortune 5 firm.

In addition, he has been working in the Task Force using analytics to fight COVID-19 and develop policy recommendations for The White House and overall finding solutions to fight the COVID-19 pandemic. You can find Eugenio's work across Forbes, The Washington Post, Bloomberg and Financial Times as well as multiple journals and in the App Store.

When he is not working, Eugenio enjoys contemporary art as well as playing Tennis with friends and traveling.

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Eugenio Zuccarrelli

Manager, Data Science
CVS Health

Eugenio is a Business-Focused Data Science Leader, leading the innovation efforts for several Fortune 500 companies across multiple industries, including Healthcare (CVS Health), Automotive (BMW) and Finance (Morningstar).

He is a Forbes 30 Under 30, a Fulbright Scholarship recipient and studied across MIT, Harvard and Imperial College London. Currently, he leads the innovation efforts for complex chronic care at CVS Health, the #1 Healthcare company in the world and a Fortune 5 firm.

In addition, he has been working in the Task Force using analytics to fight COVID-19 and develop policy recommendations for The White House and overall finding solutions to fight the COVID-19 pandemic. You can find Eugenio's work across Forbes, The Washington Post, Bloomberg and Financial Times as well as multiple journals and in the App Store.

When he is not working, Eugenio enjoys contemporary art as well as playing Tennis with friends and traveling.

Author:

Becky Soltanian

VP, Research & Development
Sanborn

Dr. Soltanian’s career in the field of AI has been extensive. With a global reach, her endeavors in AI, engineering, and academia span over 20 years. Her background includes a considerable amount of hands-on experience in a variety of roles in automation, AI, robotics, and computer vision. Most recently, Dr. Soltanian worked as a principal artificial intelligence and machine learning engineer, developing algorithms that improved perception and localization. She has also held leadership and management positions where she successfully directed teams in developing and applying advanced technologies in the use of lidar and other data types.

Dr. Soltanian holds a PhD in Electrical, Electronics and Communications Engineering; a Master of Technology in Digital Signal Processing; and a Bachelor of Science in Electrical Engineering. She’s worked for a variety of different companies such as Byton, Daqri and Velodyne Lidar, and has six (6) patents in the field of Autonomous Driving and automation.

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Becky Soltanian

VP, Research & Development
Sanborn

Dr. Soltanian’s career in the field of AI has been extensive. With a global reach, her endeavors in AI, engineering, and academia span over 20 years. Her background includes a considerable amount of hands-on experience in a variety of roles in automation, AI, robotics, and computer vision. Most recently, Dr. Soltanian worked as a principal artificial intelligence and machine learning engineer, developing algorithms that improved perception and localization. She has also held leadership and management positions where she successfully directed teams in developing and applying advanced technologies in the use of lidar and other data types.

Dr. Soltanian holds a PhD in Electrical, Electronics and Communications Engineering; a Master of Technology in Digital Signal Processing; and a Bachelor of Science in Electrical Engineering. She’s worked for a variety of different companies such as Byton, Daqri and Velodyne Lidar, and has six (6) patents in the field of Autonomous Driving and automation.

PRESENTATION

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