NSF Workshop on Algorithm-Hardware Co-design for Medical Applications

September 26, 2024 - September 27, 2024, Pittsburgh, PA

https://sites.google.com/view/nsfworkshop

Keynote Speakers

Christopher Scully - FDA
Jonathan S. Maltz - University of California, Berkeley
Sharon Xiaolei Huang - Penn State University
Ajmal Zemmar - University of Louisville
Danny Chen - University of Notre Dame
Euisik Yoon - University of Michigan
George Demiris - University of Pennsylvania
Jie Gu - Northwestern University
Milan Sonka - University of Iowa
Mohammed Islam - University of Michigan
Omer Inan - Georgia Institute of Technology
Robert Webster III - Vanderbilt University
Roozbeh Jafari - Massachusetts Institute of Technology
Sam Kavusi - Google Verily
Shandong Wu - University of Pittsburgh

Christopher Scully

Christopher Scully is Assistant Director in the Division of Biomedical Physics, Office of Science and Engineering Laboratories (OSEL) within FDA’s Center for Devices and Radiological Health. After receiving his Ph.D. degree in Biomedical Engineering from Worcester Polytechnical Institute, Worcester, MA, he joined OSEL as an engineer researching and developing test methods for medical devices with novel patient monitoring algorithms and physiologic closed-loop control technology. Currently, he is the program coordinator for OSEL’s Medical Device Interoperability regulatory science research program. In this role he leads a team of engineers and scientists performing regulatory science research to develop tools for advancing patient access to innovative, safe, and effective interoperable medical devices. Dr. Scully has served on multiple standards committees including the AAMI Alarms Committee and IEEE Committee for the Standard for Wearable Cuffless Blood Pressure Measuring Devices.

Jonathan S. Maltz

Algorithm-hardware co-design has been a key focus of Dr Jonathan S Maltz’s career, After receiving a PhD in Electrical Engineering at University of California, Berkeley, Dr Maltz joined Siemens, where he developed algorithms and hardware for image-guided radiation therapy and x-ray imaging systems. He co-invented a multisource carbon nanotube-based x-ray tube for imaging during patient treatment, and won the Sylvia Sorkin Greenfield best paper award in Medical Physics in 2009 for an article describing the device. He also pioneered algorithms for joint scatter and beam-hardening correction that are widely used in commercial CT imaging systems.

In 2013, Dr Maltz was appointed Chief Technology Officer for Radiation Therapy at Shanghai United Imaging Healthcare, where his team developed the world’s first integrated CT-linac, enabling adaptive radiation therapy (ART) based on full plan-quality pretreatment images. Time-to-market was drastically reduced through the use of a simulate-first strategy, and by replacing hardware implementation with software-defined subsystems. The CT-linac, which was developed from scratch, was treating patients within 3.5 years of project inception. The key to practical ART is rapid plan adaptation with the patient in situ, so that high patient throughput is not compromised. Dr Maltz was among the first to apply deep learning to automate radiation therapy treatment plan adaptation.

Dr Maltz then joined GE HealthCare as CT Chief Scientist, where he focused on using intensive modeling to optimize photon counting CT system design. He also worked to extend the application of AI to all aspects of the imaging workflow; including scheduling, protocol selection, patient positioning, image quality optimization, and application of automated diagnostics for primary and incidental radiological findings. In the highly-cited 2022 article in Nature Machine Intelligence, titled "Development of Metaverse for Intelligent Healthcare," Dr. Maltz articulates a vision for optimizing both individual and public health. This vision includes moving beyond proprietary raw data formats, as well as empowering patients to own, share, and be compensated for their data, positing that this is key to building better models and achieving superior health outcomes.

At Berkeley, Dr Maltz has served as PI on NIH-funded research on non-invasive assessment of arterial endothelial function. He received the Martin Black Prize for the best paper in Physiological Measurement for his article describing a device for detecting the earliest signs of developing atherosclerosis.

Dr Maltz is author of over one hundred research articles and holds over 70 US patents. As a consultant, he currently helps healthcare companies navigate their digital transformations and to exploit modern system architectures to improve price-performance over the entire product lifecycle.

Sharon Xiaolei Huang

Dr. Sharon Xiaolei Huang is David Reese Professor of Data Science and Artificial Intelligence in the College of Information Sciences and Technology at the Pennsylvania State University, University Park, PA. Her research interests are in computer vision, biomedical image analysis, and machine learning. She has over 190 publications and her research works have been cited over 20,500 times with h-index 46. Her most impactful works are on the topics of image and video generation, image and video segmentation, saliency detection, and multimodal AI in the medical domain. She serves as an associate editor for the Medical Image Analysis journal and an associate editor for the Computerized Medical Imaging and Graphics journal. She received her Bachelor’s degree in computer science from Tsinghua University, and her Master’s and doctoral degrees in computer science from Rutgers University.

Ajmal Zemmar

Dr. Zemmar’s life story and his achievements are unique. He was born in Afghanistan, fled the war and immigrated to Germany at the age of 6, where he grew up and completed medical school. He then went to Zurich (Switzerland), where he did his PhD in neuroplasticity and neuro-recovery at the prestigious Swiss Federal Institute of Technology (currently ranked number 8 in the world). He did his neurosurgery residency in Vancouver (Canada) and then specialized in functional neurosurgery in Toronto. His research focus is the development of magnetic robotic technologies permitting curved trajectories in neurosurgery.

He has published more than 60 scientific articles, wrote 5 book chapters, received multiple academic grants and awards and holds several patents on innovative technologies. He serves as editor and reviewer for several recognized international journals, for the European Research Council (which is the EU equivalent to high-level NIH grants) and for the Michael J. Fox Foundation. His research was recently featured in more than 1000 news outlets across the globe and highlighted in a recently released movie.

Danny Chen

Danny Z. Chen received the B.S. degrees in Computer Science and in Mathematics from the University of San Francisco, California in 1985, and the M.S. and Ph.D. degrees in Computer Science from Purdue University, West Lafayette, Indiana in 1988 and 1992, respectively. He is a Professor in the Department of Computer Science and Engineering, the University of Notre Dame. His main research interests include computational biomedicine, biomedical imaging, computational geometry, algorithms and data structures, machine learning, data mining, and VLSI. He has worked extensively with biomedical researchers and practitioners, published many papers in these areas, and holds 8 US patents for technology development in biomedical applications. He received the NSF CAREER Award in 1996, a Laureate Award in the 2011 Computerworld Honors Program for developing “Arc-Modulated Radiation Therapy” (a new radiation cancer treatment approach), and the 2017 PNAS Cozzarelli Prize of the US National Academy of Sciences. He is a Fellow of IEEE and a Distinguished Scientist of ACM.

Euisik Yoon

Euisik Yoon is a professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor, Michigan. After receiving Ph.D. degree in Electrical Engineering from the University of Michigan, Ann Arbor, he worked for industry including the National Semiconductor Corp. in Santa Clara, CA and Silicon Graphics Inc. in Mountain View, CA before returning to academia (1990-1996). He took faculty positions at Korea Advanced Institute of Science and Technology (KAIST) in Daejon, Korea and the University of Minnesota, Minneapolis, MN, respectively. In 2008, he joined the University of Michigan, Ann Arbor, MI, where he is a Professor and the Director of NSF International Program for the Advancement of Neurotechnology (IPAN). He served as the Director of Solid-State Electronics Laboratory (2011-2015) and the Director of Lurie Nanofabrication Facility (2011-2016) at the University of Michigan. Currently, he is leading the NSF NeuroNex Hub: Multimodal Integrated Neural Technologies (MINT), disseminating neurotechnologies to the research community.

Dr. Yoon has served on various Technical Program Committees including the IEEE International Electron Device Meeting (IEDM) (2006-2008) and the IEEE International Conference on Micro Electro Mechanical Systems (MEMS) (2006, 2008-2010, 2021). He also served on the IEEE International Solid-State Circuit Conference (ISSCC) program committee (2003-2007) and organized and co-chaired the International Conference for Advanced Neurotechnology (ICAN) (2016-2020). He served as an associate editor for IEEE Solid-State Circuit Letters (2018-2021).

George Demiris

Dr. Demiris has been at the forefront of the intersection of informatics and nursing science, and his work has introduced new and innovative approaches to old problems in gerontology. He is exploring innovative ways to utilize technology and support patients and their families in various settings including home and hospice care. He has conducted numerous federally funded studies and his work has been funded consistently over the years both by the National Institutes of Health (NIH) and the National Science Foundation (NSF). His expertise is also in designing and evaluating “smart home” solutions for aging, and in understanding the potential of wearable devices or digitally augmented residential settings to facilitate passive monitoring and support independence and quality of life for community dwelling older adults. His research provides evidence-based recommendations as to how to design systems that are easily adopted by older adults and integrated in their lives. He has examined the challenges of privacy and obtrusiveness in the context of technology use, and he has provided a comprehensive examination of technical, ethical, and practical challenges associated with the use of technology to support aging.

Jie Gu

Jie Gu received the B.S degree from Tsinghua University, Beijing, China, the M.S degree from Texas A&M University, and the Ph.D degree in Electrical Engineering from University of Minnesota in 2008. Dr. Gu joined the Department of Electrical Engineering and Computer Science at Northwestern University from Jan. 2015. Before joining Northwestern University, Dr. Gu was a R&D researcher at Texas Instruments working on ultra-low power OMAP mobile processor and a senior staff engineer at Maxlinear working on broadband multimedia SoC chips. His research interest includes novel circuit and computing architecture for emerging computing tasks e.g. AI and foundamental research and development for semiconductor device and EDA design.

Milan Sonka

Milan Sonka received his Ph.D. degree in 1983 from the Czech Technical University in Prague, Czech Republic. He is Professor of Electrical & Computer Engineering, Professor of Ophthalmology & Visual Sciences, and Radiation Oncology, Co-director of the Iowa Institute for Biomedical Imaging, Director of the Iowa Initiative for Artificial Intelligence, IEEE Fellow, AIMBE Fellow, MICCAI Fellow, Fellow of the National Academy of Inventors, and Fulbright Specialist. His research interests include medical imaging and knowledge-based image analysis with an emphasis on cardiovascular, pulmonary, orthopedic, cancer, and ophthalmic image analysis. His data-driven analysis approaches typically benefit from the combination of artificial intelligence, machine learning, and deep learning data-driven approaches with more conventionally established strategies, combined in well -performing hybrid-level systems. He is the first author of 4 editions of “Image Processing, Analysis and Machine Vision” book (1993, 1998, 2008, 2014), co-editor of “Medical Image Analysis” book (2023), and co-author or co-editor of 20 other books/proceedings. He has published more than 220 journal papers and over 450 other publications. He is past Editor in Chief of the IEEE Transactions on Medical Imaging and past Associate Editor of the Medical Image Analysis journal.

Mohammed Islam

Mohammed N. Islam received the B.S. degree in 1981, the M.S. degree in 1983, and the Sc.D. degree in 1985, all electrical engineering, from the Massachusetts Institute of Technology, Cambridge. From 1985-1992 he was a member of the Technical Staff in the Advanced Photonics Department at AT&T Bell Laboratories, Holmdel, N.J. He joined the Electrical and Computer Engineering department at the University of Michigan in Ann Arbor in 1992, where he is currently a Full Tenured Professor. He also has a joint Full Professor appointment in the Biomedical Engineering Department, and also was with the University of Michigan Medical School, Department of Internal Medicine.

Prof. Islam was a Fannie and John Hertz Fellow from 1981-1985, and in 1992 he was awarded the OSA Adolf Lomb Medal for pioneering contributions to nonlinear optical phenomena and all-optical switching in optical fibers. He also received the U-M research excellence award in 1997 and became a Fellow of the Optical Society of America in 1998. In 2002 he received the Texas eComm Ten Award for being one of the 10 most influential people in Texas’s digital economy. He became a fellow of the IEEE in 2004. He is also the first recipient of the prestigious 2007 Distinguished University Innovator Award.

Prof. Islam has published over 153 papers in refereed journals and holds over 203 patents or patents pending. In addition, he has authored three books and has written several book chapters. He has also been an invited speaker at over 85 conferences and symposia, and he has founded a number of companies including Xtera Communications, Omni Sciences, Celeste Optics, AccuPhotonics, Omni MedSci, Omni Continuum, and Cheetah Omni. He is also a patent agent with the US Patent and Trademark Office.

His current research interests include infrared laser sources and their applications in defense and healthcare. On the defense side, applications are related to active remote sensing and identifying targets based on their chemical signature. On the healthcare side, his research relates to using light sources in diagnostics, therapeutics, and physiological measurements using wearable devices and contactless camera based systems. Using actively illuminated time-of-flight cameras, a number of applications are being pursued such as driver monitoring systems, telemedicine and remote patient monitoring, and patient monitoring in hospital settings. Also, traumatic brain injury studies are being performed using novel optical systems that simultaneously measure the brain metabolic and hemodynamic response.

Omer Inan

Omer Inan is Regents Entrepreneur, Professor and Linda J. and Mark C. Smith Chair in Bioscience and Bioengineering in the School of Electrical and Computer Engineering, and Adjunct Professor in the Coulter Department of Biomedical Engineering, at Georgia Tech. He received his BS, MS, and PhD in Electrical Engineering from Stanford in 2004, 2005, and 2009, respectively. From 2009-2013, he was the Chief Engineer at Countryman Associates, Inc., a professional audio manufacturer of miniature microphones and high-end audio products for Broadway theaters, theme parks, and broadcast networks. His research focuses on non-invasive physiological sensing and modulation for human health and performance. He has published more than 360 technical articles in peer-reviewed international journals and conferences, and has 18 issued patents. He has received several major awards for his research including the US National Science Foundation Faculty Early Career (CAREER) award, the US Office of Naval Research Young Investigator award, and the IEEE Sensors Council Early Career award. He also received an Academy Award for Technical Achievement from The Academy of Motion Picture Arts and Sciences (The Oscars). He is a Fellow of the IEEE, the American Institute for Medical and Biological Engineering (AIMBE), and the American College of Cardiology. He is currently an IEEE Engineering in Medicine and Biology Society Distinguished Lecturer. While at Stanford as an undergraduate, he was the school record holder and a three-time National Collegiate Athletic Association All-American in the discus throw.

Robert Webster III

Robert J. Webster III is the Richard A. Schroeder Professor of Mechanical Engineering at Vanderbilt University. He received his B.S. in electrical engineering from Clemson University in 2002, and his M.S. and Ph.D. in mechanical engineering from the Johns Hopkins University in 2004 and 2007. In 2008, he joined the mechanical engineering faculty of Vanderbilt University, where he currently directs the Medical Engineering and Discovery Laboratory. He founded and serves on the steering committee for the Vanderbilt Institute for Surgery and Engineering, which brings together physicians and engineers to solve challenging clinical problems. He is the founder and President of Virtuoso Surgical, Inc. and EndoTheia, Inc. which are commercializing technologies invented in his laboratory, and have raised over $30M in private capital and grant funding, and received FDA Breakthrough Device designation.

Prof. Webster's research interests include surgical robotics, medical device design, image-guided surgery, and continuum robotics. He is a recipient of the IEEE Robotics and Automation Society Early Career Award, the National Science Foundation CAREER award, the Robotics Science and Systems Early Career Spotlight Award, IEEE Volz award, and the award for Excellence in Teaching from Vanderbilt University. In addition to his primary appointment in Mechanical Engineering, he holds appointments at Vanderbilt in Electrical Engineering, Otolaryngology, Neurological Surgery, Urologic Surgery, and Medicine at Vanderbilt. Eleven of his prior trainees are now in faculty positions. He directs the Mid-South REACH Hub, a large NIH entrepreneurship center, and teaches entrepreneurship at Vanderbilt.

Roozbeh Jafari

Dr. Roozbeh Jafari is a principal staff member in the Biotechnology and Human Systems Division at MIT Lincoln Laboratory with a joint research appointment on MIT campus. He is also an adjunct professor in Electrical and Computer Engineering and in the School of Engineering Medicine at Texas A&M University. Jafari’s goal is to establish impactful and highly collaborative programs to promote the health and wellness of interest to our national security and our communities. His aspiration is to serve as a catalyst between Lincoln Laboratory, MIT campus, and other academic entities across the nation for such programs. He joined MIT from Texas A&M where he was the Tim and Amy Leach Professor in Electrical and Computer Engineering and in the School of Engineering Medicine.

Jafari received his PhD in computer science from the University of California, Los Angeles, and completed a postdoctoral fellowship at the University of California, Berkeley. His research interests lie in the areas of wearable computer design, sensors, systems, and AI for digital health paradigms and, most recently, digital twin for precision health. He has raised more than $89 million for research with $25 million directed toward his lab. His research has been funded by the NSF, NIH, DoD (TATRC), DTRA, DIU, AFRL, AFOSR, DARPA, SRC, and industry (Texas Instruments, Tektronix, Samsung & Telecom Italia). He has published more than 200 papers in refereed journals and conferences. He has served as the general chair and technical program committee chair for several flagship conferences in the area of wearable computers. Jafari is the recipient of the National Science Foundation CAREER award (2012), the IEEE Real-Time & Embedded Technology & Applications Symposium best paper award (2011), the Andrew P. Sage best transactions paper award (2014), the ACM Transactions on Embedded Computing Systems best paper award (2019), the William O. and Montine P. Head Memorial research award for outstanding engineering contribution award from the College of Engineering at Texas A&M University (2019), the dean of engineering excellence award at Texas of A&M University (2021), and the TEES research impact award at Texas A&M University (2021). He has also been named the Texas A&M Presidential Fellow (2019).

Jafari serves on the editorial board for Nature Digital Medicine, the IEEE Transactions on Biomedical Circuits and Systems, the IEEE Sensors Journal, IEEE Internet of Things Journal, IEEE Journal of Biomedical and Health Informatics, IEEE Open Journal of Engineering in Medicine and Biology, and the ACM Transactions on Computing for Healthcare. He is the past chair of the IEEE Wearable Biomedical Sensors and Systems Technical Committee as well the IEEE Applied Signal Processing Technical Committee (elected). He serves on scientific panels for funding agencies frequently, has served as a standing member of the NIH Biomedical Computing and Health Informatics (BCHI) study section (2017-2021), and was the inaugural chair of the NIH Clinical Informatics and Digital Health (CIDH) study section (2020-2022). He is a fellow of the American Institute for Medical and Biological Engineering.

Sam Kavusi

Sam Kavusi is the head of Retina Imaging and Teleretinal Integration at Verily. He is interested in improving availability and accuracy of retina image captures especially outside of the ophthalmic environments. Generally, he is interested in application of on-device intelligence, computational imaging, artificial intelligence, and consumer electronics in the development of modern medical devices. He received the B.S. degree (Hons.) from Sharif University, Tehran, Iran in 1999, and the M.S. and PhD. degrees in electrical engineering from Stanford University, Stanford, CA in 2001 and 2006, respectively. He has held various industry positions leading and developing smartphone cameras, semiconductor/MEMS sensors and proteomic chips at Google and Bosch. He is co-inventor of more than 70 patents and his publications are cited more than 800 times.

Shandong Wu

Shandong Wu (Member, IEEE) received the Ph.D. degree in computer vision from the City University of Hong Kong, Hong Kong, in 2009. He was a Postdoctoral Fellow of Computer Vision with the University of Central Florida, Orlando, FL, USA, and a Postdoctoral Fellow of Clinical Radiology Research with the University of Pennsylvania, Philadelphia, PA, USA. He is currently a Tenured Associate Professor with joint appointments in Radiology (primary), Biomedical Informatics, Bioengineering, Intelligent Systems, and Clinical and Translational Science with the University of Pittsburgh, Pittsburgh, PA, USA. He leads the Intelligent Computing for Clinical Imaging Lab and is the Founding Director of the Pittsburgh Center for AI Innovation in Medical Imaging. His research interests include artificial intelligence for clinical/translational study, computational biomedical imaging analysis, big (health) data coupled with machine/deep learning, and radiomics/radiogenomics.

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