tinyML Summit

Jeff Bier is the founder of the Embedded Vision Alliance (www.embedded-vision.com), a partnership of 90+ technology companies that works to enable the widespread use of practical computer vision. He is also the General Chairman of the Embedded Vision Summit — the only conference devoted to enabling product creators to build better products using computer vision, at the edge and in the cloud.

In addition, Jeff is president of BDTI (www.bdti.com). For over 25 years, he has led BDTI in helping hundreds of companies choose the right processors and develop optimized software for demanding applications in computer vision, deep learning, audio and video.

Jeff is a frequent keynote and invited speaker at industry conferences. Jeff earned B.S. and M.S. degrees in electrical engineering from Princeton University and U.C. Berkeley.
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Byron Changuion is the engineering lead for the Machine Learning and Optimization Group at Microsoft Research, in Redmond, Washington. He is currently focused on bringing the power of AI and new ML techniques to small, resource constrained devices. His team is responsible for building the Embedded Learning Library (ELL), which is a set of tools allowing developers to design and deploy intelligent machine-learned models onto embedded systems, micro-controllers and small single-board computers. He brings twenty years' experience in developing device-centric platforms and OS infrastructure, spanning portable devices, personal health monitors and embedded systems.
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Dr. Chappell joined DARPA as a program manager in July 2011 and became Director of the Agency's Microsystems Technology Office (MTO) in June 2014. His interests include advanced packaging, adaptable RF systems, and antenna arrays.

Prior to DARPA, Dr. Chappell served as a professor in the Electrical and Computer Engineering Department of Purdue University, where he also led the Integrated Design of Electromagnetically-Applied Systems (IDEAS) Laboratory. His research focus has been on high frequency components, specifically the unique integration of RF and microwave components based on electromagnetic analysis. This ranged from advanced RF sensors such as miniature RF ion trap mass spectrometry to advanced digital-at-every element antenna arrays. Dr. Chappell has conducted extensive research on the development of adaptable RF systems, focusing on tunable preselect filters. He has shown the ability to design a single RF system that is adaptable to numerous application areas and/or adjustable to dynamic changes within the spectral environment.

Dr. Chappell is the recipient of many research and teaching awards. He has been the advisor of numerous IEEE MTT International Microwave Symposium best paper finalists and a coauthor of two best papers at the GOMACTech conference. His paper on wearable MIMO systems was selected for the best journal paper at the IEEE VT Society in 2009. In 2011, he received the ARL Director's Coin for his work on standoff inverse analysis and manipulation of electronic systems MUIR analyzing the effects of nonlinearities in high power systems. He was selected as a Collaborative Investigator by the Howard Hughes Medical Institute for work on RF implantable systems and to join the Frontiers of Engineering meetings sponsored by the National Academies of Engineering.

Dr. Chappell received his Bachelor of Science in 1998 from the University of Michigan, where he graduated summa cum laude. He received his Masters and Doctor of Philosophy, also from the University of Michigan, studying in the Radiation Laboratory on spectral isolation techniques for high frequency microwave systems using composite materials.

Charles Chong is the Director of Strategic Marketing at PixArt Imaging in North America, overlooking strategic partnerships pertaining to advance applications utilizing CMOS imagers. Charles brings with him extensive experience in the field of imaging, since his role of a Camera Design Engineer, using CCDs (Charge Coupled Devices) at Perkinelmer Optoelectronics in 2000. Since then, Charles has had the opportunity to witness and be a part of the imaging revolution, from CCD to CMOS, from FSI (Front Side Illumination) to BSI (Back Side Illumination), through his roles at Micron Imaging and OmniVision Technologies.

Charles now heads the strategic efforts at PixArt Imaging USA with focus in low power Always ON sensing application utilizing CMOS imaging technology. Charles holds a B.S degree in Electrical Engineering (2000) and an MBA (2008) from Santa Clara University.
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Simon Craske, one of the Arm Fellows, is currently responsible for leading the development and maintenance of Arm's R and M-Profile embedded architectures. Based at Arm’s headquarters in Cambridge, Simon has spent more than a decade working with the Arm architecture, developing features across the entire 32/64-bit portfolio. Simon has a wealth of experience in both the design and verification of processor intellectual property, ranging from large SIMD engine implementations, through to being the Technical Lead of Arm’s smallest, most energy efficient CPU to date, Cortex-M0+.

Simon has a Masters Degree in Electronic Engineering from the University of Southampton, is a Member of the IET, and holds over fifty granted US patents spanning CPU architecture, verification and implementation.
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Hans De Clercq is Co-founder and CTO of Byteflies. Hans obtained his PhD on medical wearables at Micas in 2015 and won several wearable health innovation awards, including the Engibous Prize for Innovation In Analog in 2012 and the TI EMEA innovation award in 2013. With the aim to make make healthcare proactive, he co-founded Byteflies, together with Hans Danneels. It offers a wearable health platform and collaborates with top pharma and research institutes in Europe and US. Byteflies won the Deloitte Rising Star award (2018), was nominated as "Most Promising Company" by Belcham (2017) and was selected by Google as 1 of 4 companies to collaborate on machine learning in healthcare.
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Eric Flamand got his PhD in Computer Science from INPG, France, in 1982. For the first part of his career he worked as a researcher with CNET and CNRS in France, on architectural automatic synthesis, design and architecture, compiler infrastructure for higly constrained heterogeneous small parallel processors.

He then held different technical management in the semiconductor industry, first with Motorola where he was involved into the architecture definition and tooling of the StarCore DSP, then with STMicroelectronics, first being in charge of all the software development of the Nomadik Application Processor and then in charge of the P2012 corporate initiative aiming at the development of a many core device.

He is now co-founder and CTO of Greenwaves Technologies a French based startup developping an IOT processor derived from Pulp. He is also acting as a part time research consultant for ETH-Z.
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Mr. Edwin Park is a Principal Engineer with Qualcomm Research since 2011. He is directly responsible for leading the system activities surrounding the Always-on Computer Vision Module (CVM) project. In this role, he leads his team in developing the architecture, creating the algorithms, and producing models so devices can “see” at the lowest power. Featuring an extraordinarily small form factor, Edwin has designed the CVM to be integrated into a wide variety of battery-powered and line-powered devices, performing object detection, feature recognition, change/motion detection, and other applications.

Since joining Qualcomm Research, Edwin has worked on a variety of projects such as making software modifications to Qualcomm radios, enabling them to support different radio standards. Edwin has also focused on facilitating carriers’ efforts worldwide to migrate from their legacy 2G cellular systems to 3G, allowing them to increase their data capacity. Edwin Park’s work at Qualcomm Research has resulted in over 40 patents.

Prior to joining Qualcomm, Park was a founder at AirHop Communications and Vie Wireless Technologies. Edwin had various engineering and management positions at Texas Instruments and Dot Wireless. He also worked at various other startups including ViaSat and Nextwave.

Park received a Master Electrical Engineering from Rice University, Houston, TX, USA and a BSEE specializing in Physical Electronics and BA in Economics also from Rice University.
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Chris is a Silicon Valley entrepreneur and technologist, now co-founder and CEO of BabbleLabs, a deep learning technology company focused on speech. Most recently, he has led Cognite Ventures, a specialized analysis and investment company for deep learning start-ups. Prior to Cognite, he served as CTO for Cadence’s IP Group.

Chris joined Cadence after its acquisition of Tensilica, the company he founded in 1997 to develop extensible processors. He led Tensilica as CEO and later, CTO, to develop one of the most prolific embedded processor architectures.

Before that he was VP and GM of the Design Reuse Group at Synopsys. Chris was a pioneer in developing RISC architecture and helped found MIPS Computer Systems. He holds an MSEE and PhD in electrical engineering from Stanford and a BA in physics from Harvard. He holds more than 40 US and international patents. He was named an IEEE Fellow in 2015 for his work in development of microprocessor technology.
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Dennis Sylvester is a Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. His main research interests are in the design of miniaturized ultra-low power microsystems, touching on analog, mixed-signal, and digital circuits. He has published over 500 articles and holds 43 US patents in these areas. His research has been commercialized via three major venture capital funded startup companies; Ambiq Micro, Cubeworks, and Mythic. He was named a Top Contributing Author at ISSCC and most prolific author at IEEE Symposium on VLSI Circuits. He received his PhD in Electrical Engineering from UC-Berkeley, and has held research staff positions at Synopsys and Hewlett-Packard Laboratories as well as visiting professorships at the National University of Singapore and Nanyang Technological University.
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Marian Verhelst is an associate professor at the MICAS laboratories (MICro-electronics And Sensors) of the Electrical Engineering Department of KU Leuven, Belgium. Her research focuses on embedded machine learning, hardware accelerators, self-adaptive circuits and systems, and low-power embedded sensing and processing.

She received a Ph.D. from KU Leuven in 2008, was a visiting scholar at the Berkeley Wireless Research Center (BWRC) of UC Berkeley in 2005, and worked as a research scientist at Intel Labs, Hillsboro OR, from 2008 till 2011.

Marian is a member of the DATE conference executive committee and was a member of the ESSCIRC and ISSCC TPCs and of the ISSCC executive committee.

Marian is an SSCS Distinguished Lecturer, was a member of the Young Academy of Belgium an associate editor for TCAS-II and JSSC and a member of the STEM advisory committee to the Flemish Government. Marian currently holds a prestigious ERC Starting Grant from the European Union.
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Naveen Verma received the B.A.Sc. degree in Electrical and Computer Engineering from the UBC, Vancouver, Canada in 2003, and the M.S. and Ph.D. degrees in Electrical Engineering from MIT in 2005 and 2009 respectively. Since July 2009 he has been a faculty member at Princeton University. His research focuses on advanced sensing systems, exploring how systems for learning, inference, and action planning can be enhanced by algorithms that exploit new sensing and computing technologies. This includes research on large-area, flexible sensors, energy-efficient statistical-computing architectures and circuits, and machine-learning and statistical-signal-processing algorithms. Prof. Verma has served as a Distinguished Lecturer of the IEEE Solid-State Circuits Society, and currently serves on the technical program committees for ISSCC, VLSI Symp., DATE, and IEEE Signal-Processing Society (DISPS).
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Pete Warden is the technical lead of the TensorFlow mobile and embedded team at Google, and was previously CTO of Jetpac (acquired in 2014).
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Kisun You is a Software Engineering Manager on the Siri team at Apple. He leads the team responsible for on-device software frameworks enabling Siri speech features such as "Hey Siri" in various Apple products including iPhone, Apple Watch, Mac, and HomePod. Prior to joining Apple, he worked at Intel and Qualcomm conducting research and development for machine learning applications in audio, speech, and computer vision. He received his Ph.D. and B.S. degrees in Electrical Engineering from Seoul National University, South Korea.

Dr. Evgeni Gousev is a Senior Director of Engineering in Qualcomm Research. He leads HW R&D org in the Silicon Valley Center and is also responsible for developing ultra low power embedded computing platform, including always on machine vision AI technology. He has been with Qualcomm Technologies, Inc. since 2005 after joining from IBM T.J. Watson Research Center where he drove projects in the field of advanced silicon technologies.

From 1993 to 1998, Dr. Gousev held academic professorship appointments with Rutgers University and Hiroshima University (1997). Evgeni holds a M.S. degree in Applied Physics and a Ph.D. in Solid-State Physics. He has co-edited 24 books and published 163 papers and is an inventor on more than 60 issued and filed patents.

Pete Warden is the technical lead of the TensorFlow mobile and embedded team at Google, and was previously CTO of Jetpac (acquired in 2014).

Ian Bratt is a Distinguished Engineer at Arm, where he leads the Machine Learning Technology group within the ML business unit. Recently, Ian's team defined the architecture for Arm's family of Machine Learning Processors and has been responsible for multiple ML related improvements to the Arm IP roadmap.

Before working in machine learning, Ian worked as an architect on several generations of Arm Mali GPUs, during a high-growth period which culminated in Arm partners shipping over 1B Mali GPUs in 2016.

Prior to Arm, Ian worked at the pioneering multicore startup, Tilera. Ian has worked on NPUs, CPUs, GPUs, memory systems and SoC architecture. He holds an S.M. from MIT and has 23 granted US patents.

Kurt's research at University of California, Berkeley, focuses on computational problems in Deep Learning. In particular, Kurt has worked to reduce the training time of ImageNet to minutes and, with the SqueezeNet family, to develop a family of Deep Neural Networks suitable for mobile and IoT applications.

Before joining Berkeley as a Full Professor in 1998, Kurt was CTO and SVP at Synopsys. Kurt's contributions to Electronic Design Automation were recognized at the 50^th Design Automation Conference where he was noted as a Top 10 most cited author, as an author of a Top 10 most cited paper, and as one of only three people to have won four Best Paper Awards at that conference. Kurt was named a Fellow of the IEEE in 1996.

Boris Murmann is a Professor of Electrical Engineering at Stanford University. He joined Stanford in 2004 after completing his Ph.D. degree in electrical engineering at the University of California, Berkeley in 2003. From 1994 to 1997, he was with Neutron Microelectronics, Germany, where he developed low-power and smart-power ASICs in automotive CMOS technology. Since 2004, he has worked as a consultant with numerous Silicon Valley companies.

Dr. Murmann's research interests are in mixed-signal integrated circuit design, with special emphasis on sensor interfaces, data converters and custom circuits for embedded machine learning. In 2008, he was a co-recipient of the Best Student Paper Award at the VLSI Circuits Symposium and a recipient of the Best Invited Paper Award at the IEEE Custom Integrated Circuits Conference (CICC). He received the Agilent Early Career Professor Award in 2009 and the Friedrich Wilhelm Bessel Research Award in 2012.

He has served as an Associate Editor of the IEEE Journal of Solid-State Circuits, an AdCom member and Distinguished Lecturer of the IEEE Solid-State Circuits Society, as well as the Data Converter Subcommittee Chair and the Technical Program Chair of the IEEE International Solid-State Circuits Conference (ISSCC). He is the faculty director of the Stanford SystemX Alliance and Stanford's System Prototyping Facility. He is a Fellow of the IEEE.

Chris is a Silicon Valley entrepreneur and technologist, now co-founder and CEO of BabbleLabs, a deep learning technology company focused on speech. Most recently, he has led Cognite Ventures, a specialized analysis and investment company for deep learning start-ups. Prior to Cognite, he served as CTO for Cadence’s IP Group.

Chris joined Cadence after its acquisition of Tensilica, the company he founded in 1997 to develop extensible processors. He led Tensilica as CEO and later, CTO, to develop one of the most prolific embedded processor architectures.

Before that he was VP and GM of the Design Reuse Group at Synopsys. Chris was a pioneer in developing RISC architecture and helped found MIPS Computer Systems. He holds an MSEE and PhD in electrical engineering from Stanford and a BA in physics from Harvard. He holds more than 40 US and international patents. He was named an IEEE Fellow in 2015 for his work in development of microprocessor technology.

Marian Verhelst is an associate professor at the MICAS laboratories (MICro-electronics And Sensors) of the Electrical Engineering Department of KU Leuven, Belgium. Her research focuses on embedded machine learning, hardware accelerators, self-adaptive circuits and systems, and low-power embedded sensing and processing.

She received a Ph.D. from KU Leuven in 2008, was a visiting scholar at the Berkeley Wireless Research Center (BWRC) of UC Berkeley in 2005, and worked as a research scientist at Intel Labs, Hillsboro OR, from 2008 till 2011.

Marian is a member of the DATE conference executive committee and was a member of the ESSCIRC and ISSCC TPCs and of the ISSCC executive committee.

Marian is an SSCS Distinguished Lecturer, was a member of the Young Academy of Belgium an associate editor for TCAS-II and JSSC and a member of the STEM advisory committee to the Flemish Government. Marian currently holds a prestigious ERC Starting Grant from the European Union.