Organizing Committee

Yufei Huang

General Co-Chair
Univ. of Pittsburgh Medical Center
Bio-sketch: Yufei Huang is currently Professor of the Department of Medicine, School of Medicine, University of Pittsburgh and Leader in AI for Cancer Research at UMPC Hillman Cancer Center and. Prior to that, he was Professor and Associate Chair on Research of Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA), and an adjunct professor at the Department of Population Health Science at the University of Texas Health San Antonio. He has been a visiting professor at the Center of Bioinformatics, Harvard Center for Neurodegeneration & Repair. Dr. Huang has multi-disciplinary expertise in cancer genomics, clinical informatics, and AI/machine learning. His current research focuses on studying the functions of m6A methylation in cancer and cancer viruses and developing AI and informatics tools for spatial single cell sequencing data analysis and visualization. He was a recipient of the National Science Foundation (NSF) CAREER Award, UTSA Presidential Achievement Award on Research Excellence, Best Paper Award IEEE Biomedical and Health Informatics Conference, Best Paper Award of Artificial Neural Networks in Engineering Conference, and Best Paper Award of IEEE Signal Processing Magazine. His research has been supported by NSF, NIH, Air Force Office of Scientific Research, Army Research Lab, Department of Defense, and Qatar National Research Fund. He serves as the Chair of the IEEE EMBS Biomedical and Health Informatics Technical Committee and in the role of Associate Editor for multiple journals including IEEE Transactions on Signal Processing, BMC Systems Biology, Frontiers Genetics, and Neurocomputing.

Georgia Tourassi

General Co-Chair
Oak Ridge National Lab
Bio-sketch: Georgia (Gina) Tourassi is the Director of the National Center for Computational Sciences and the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory. She joined ORNL in 2011 as the director of the Biomedical Sciences and Engineering Center after a long academic career in the department of radiology and the medical physics graduate program at Duke University Medical Center. In addition, she is an adjunct professor of radiology at Duke University and the University of Tennessee Graduate School of Medicine, joint UT-ORNL faculty of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee at Knoxville and the Bredesen Center. Dr. Tourassi’s research background and interests are in artificial intelligence, scalable data-driven biomedical discovery, high-performance computing, clinical decision support, and human-computer interaction. Her scholarly work includes more than 250 peer-reviewed journal articles, conference proceedings articles, book chapters, editorials, and conference abstracts as well as 15 invention disclosures and patents. Her research work has been funded by NIH, DOE, VA, DOD, and various foundations. Dr. Tourassi is a member of several scientific societies with extensive service records, has chaired an international medical imaging conference, serves on the technical committees of biomedical informatics, AI, and scientific computing conferences and workshops, and has prepared educational material and refresher courses. She has been recognized as a leading expert in her fields of expertise by being appointed Charter member of NIH Study sections and being elected member of the FDA Advisory Committee and review panel on Computer-Aided Diagnosis Devices. She is elected Fellow of the American Institute of Medical and Biological Engineering (AIMBE), the American Association of Physicists in Medicine (AAPM), the International Society for Optics and Photonics (SPIE), and the American Association for the Advancement of Sciences (AAAS). She is also senior member of the Institute of Electrical and Electronics Engineers (IEEE) and the International Neural Network Society (INNS).

Bjoern Eskofier

General Co-Chair
Friedrich Alexander Univ.
Bio-sketch: Bjoern M. Eskofier (SM, IEEE) heads the Machine Learning and Data Analytics (MaD) Lab at the Friedrich-Alexander-University Erlangen-Nuernberg (FAU). He is also the founding spokesperson of FAU’s Department Artificial Intelligence in Biomedical Engineering (AIBE), and co-spokesperson of the German Research Foundation collaborative research center “EmpkinS” (www.empkins.de). Since April 2023, he is an associate principal investigator and leader of the research group “Translational Digital Health” at the Helmholtz Zentrum Munich.
Dr. Eskofier studied Electrical Engineering at the FAU and graduated in 2006. He did his PhD in Biomechanics under the supervision of Prof. Dr. Benno Nigg at the University of Calgary (Canada). He authored more than 400 peer reviewed articles, holds 5 patents, started three spinoff startup companies, and is in a supporting role for further startups. He won several medical-technical research awards, including the “Curious Minds” award 2021 in “Life Sciences” by Manager Magazin and Merck. In 2016, he was a visiting professor in Prof. Paolo Bonato’s Motion Analysis Lab at Harvard Medical School (February-March), in 2018, he was a visiting professor in Prof. Alex “Sandy” Pentland’s Human Dynamics group at MIT Media Lab (March-August), and in 2023, he was a visiting professor in Prof. Scott Delp’s NMBL lab that is part of Stanford University’s Schools of Engineering and Medicine (April to August). He serves as Area Editor for the “IEEE Open Access Journal of Engineering in Medicine and Biology” and Associate Editor for the “IEEE Journal of Biomedical and Health Informatics”. He is also active in the organization of several IEEE and ACM meetings (e.g., BSN, BHI, EMBC, IJCAI, ISWC, UbiComp), most recently as General Chair of BHI 2023.

David Clifton

Technical Program Co-Chair
Oxford Univ.
Bio-sketch: Professor David Clifton is the Royal Academy of Engineering Chair of Clinical Machine Learning at the University of Oxford, and leads the Computational Health Informatics (CHI) Lab which focuses on “AI for Healthcare”. He is also NIHR Research Professor, appointed as the first non-medical scientist to the NIHR’s “flagship chair”. His research has won over 40 awards; he is a Grand Challenge awardee from the UK Engineering and Physical Sciences Research Council, which is an EPSRC Fellowship that provides long-term strategic support for nine “future leaders in healthcare.” He was joint winner of the inaugural “Vice-Chancellor’s Innovation Prize”, which identifies the best interdisciplinary research across the entirety of the University of Oxford. He was the recipient of the IEEE Early Career Award in 2022, given to one engineer annually for achievements within the first ten years of their academic career. He has previously taught widely across Oxford undergraduate and graduate courses in mathematics, statistics, and machine learning.

Parisa Rashidi

Technical Program Co-Chair
Univ. of Florida
Bio-sketch: Dr. Rashidi is a National Science Foundation (NSF) CAREER awardee, the National Institute of Health (NIH) Trailblazer Awardee, Herbert Wertheim College of Engineering (HWCOE) Assistant Professor Excellence Awardee, and a recipient of the UF term professorship. She is also a recipient of UF’s Provost excellence award for assistant professors. To date, she has authored 150+ peer-reviewed publications. She has chaired numerous workshops and symposiums on intelligent health systems and has served on the program committee of 20+ conferences. Over the past few years, she has received $10.6M in extramural research funds with collaborators and $3.05M as an individual investigator. Dr. Rashidi’s research has been supported by local, state, and federal grants, including awards from the National Institutes of Health (NIBIB, NCI, and NIGMS) and the National Science Foundation (NSF).

Jian Ma

Technical Program Co-Chair
Carnegie Mellon Univ.
Bio-sketch: Jian Ma is an American computer scientist and computational biologist. He is the Ray and Stephanie Lane Professor of Computational Biology in the School of Computer Science at Carnegie Mellon University. He is a faculty member in the Computational Biology Department. His lab develops machine learning algorithms to study the structure and function of the human genome. During his Ph.D. and postdoc training, he developed algorithms to reconstruct the ancestral mammalian genome. His research group has recently pioneered a series of new machine learning methods for 3D epigenomics and spatial genomics. He received an NSF CAREER award in 2011. In 2020, he was awarded a Guggenheim Fellowship in Computer Science. He is an elected Fellow of the American Association for the Advancement of Science. He leads an NIH 4D Nucleome Center to develop machine learning algorithms to better understand the cell nucleus.

Jie Liang

Finance Chair
Univ. of Illinois Chicago
Bio-sketch: Dr. Jie Liang is a Professor of Bioengineering at the University of Illinois at Chicago College of Engineering. He received his PhD training in experimental biophysics and continued his research training in computational geometry, computational topology, and computational biology during his postdoc years. Research in his lab is focused on constructing quantitative models and developing computational tools to study biological systems for gaining understanding of how living systems work. Dr. LiangGÇÖs lab has developed state-of-the-art tools for computing protein binding pockets and voids, as well as general metric measurements based on the alpha shape theory and dual complexes. The CastP server developed in his lab is widely used by structural biologists. In the past ten years, Dr, LiangGÇÖs lab gained significant experience in developing models and algorithms for sampling chain polymers, with studies on methodology development of constrained sampling by sequential Monte Carlo, including sampling transition state ensemble of protein folding based on contact maps, chain growth, as well as algorithm for pseudoknotted RNA secondary and tertiary structure. Recent work on the development of the Constrained Self-Avoiding Chromosome (C-SAC) model and the geometric sequential importance sampling technique enabled the elucidation of the physical basis of the scaling properties of chromosomes observed in FISH and Hi-C studies.

Bobak Mortazavi

Special Session/Workshop Co-Chair
Texas A&M Univ.
Bio-sketch: My research interests include end-to-end research on medical embedded systems and the application of data mining and machine learning algorithms necessary to make personalized, preventative medical treatments possible through advanced health analytics . My background is in embedded systems design, where I studied sensor fusion, reconfigurable architectures and systems, hardware accelerators, and gpu computing. During my Ph.D. I applied data mining and machine learning techniques to these systems to develop a personalized, exercise-level activity-recognition video game with wearable sensors. I am now primarily concerned with the ability to use supervised and unsupervised techniques to learn more about medical prediction and risk-stratification in order to better develop personalized medical systems, prediction models, comparative effectiveness techniques, and combine wearable sensors and other necessary data to make a clinical impact at the system level, provider level, and patient level.

Souparno Ghosh

Special Session/Workshop Co-Chair
Univ. of Nebraska–Lincoln
Bio-sketch: Souparno’s research focuses on Bayesian hierarchical models, image modeling, bioinfomatics and developing inferential methods for machine learning models. His current projects include machine learning models for image and functional data, transfer learning from heterogeneous data

Ahmed A. Metwally

Industry Liaison Chair
Google
Bio-sketch: Dr. Ahmed Metwally is a senior research scientist at Google. His research focuses on developing AI methods for longitudinal multimodal biomedical data fusion (wearables and omics) to detect cardiometabolic and infectious diseases early and personalize their treatments. Previously, he was a senior AI scientist at Illumina. Ahmed was a postdoctoral scholar in the Snyder lab at Stanford University (2018-2021). Ahmed holds a PhD in Biomedical Engineering and an MS in Computer Science, both from the University of Illinois at Chicago (2018). He received B.Sc. in Biomedical Engineering from Cairo University, Egypt. He has over 55 publications in prestigious journals, and is a co-inventor of two patents relating to diabetes prevention. Ahmed also led the Stanford Wearable Electronics Initiative and co-led the Stanford initiative for early prediction of COVID-19 using smartwatches. He is an IEEE senior member and was elected globally to serve on the board of IEEE EMBS from 2017 to 2019. He has received numerous awards, including the NIH Predoctoral Translational Scientist fellowship, Stanford RISE award, and ISMB’20 Best Talk award.

Ranadip Pal

Special Panel Chair
Texas Tech Univ.
Bio-sketch: Ranadip Pal (Senior Member, IEEE) received the B.Tech. degree in electronics and electrical communication engineering from the Indian Institute of Technology, Kharagpur, India, in 2002, and the M.S. and Ph.D. degrees in electrical engineering from Texas University, College Station, TX, USA, in 2004 and 2007, respectively. Since 2007, he has been with Texas Tech University, where he is currently a Professor with the Electrical and Computer Engineering Department. His research interests include genomic signal processing, stochastic modeling and control, machine learning and computational biology. He has authored more than 90 peer reviewed articles, including publications in high impact journals such as Nature Medicine and Cancer Cell and has authored a book entitled Predictive Modeling of Drug Sensitivity. He received the NSF CAREER Award in 2010, the President’s Excellence in Teaching Award in 2012, the Whitacre Research Award in 2014, and the Chancellor’s Council Distinguished Research Award in 2016.

Arun Das

Local Arrangement Chair
Univ. of Pittsburgh Medical Center
Bio-sketch: Dr. Das, a second-year postdoctoral associate at the Hillman Cancer Center at the University of Pittsburgh, boasts a diverse research portfolio encompassing explainable AI, robust AI, omics data analysis, and computational biology. His formative years at UTSA kindled a passion for merging AI with biology and human behavior. Collaborations with Dr. Paul Rad yielded AI-driven solutions detecting macular degeneration, identifying tumor regions in low-powered CT images, and predicting stuttering events. Engaging clinicians, biologists, psychologists, and neuroscientists, Dr. Das imbibed the nuances of applying AI in healthcare. Guided by Dr. Yufei Huang, Dr. Das honed his skills in single-cell spatial omics, culminating in the development of a spatial transcriptomics analysis pipeline. This innovative tool facilitates automated, reproducible analysis, unveiling hidden cellular and molecular signatures ripe for further exploration. Their work revealed concealed cellular interactions, immune and structure cell landscapes, and pathology trajectories in SARS-CoV-2 infected samples. Dr. Das was awarded the Hillman Fellow for Innovative Cancer Research award for his budding research in revealing spatial signatures of cancer tumor microenvironments. Dr. Das is a well cited early career researcher with over 17 publications and patents and aims to build a research lab involving research in novel multimodal neural networks uniting morphology and omics data, envisioning a research trajectory bridging cancer bioinformatics and AI.

Edward Sazonov

Publication Chair
Univ. of Alabama
Bio-sketch: Edward Sazonov is a professor in the electrical and computer engineering department at The University of Alabama College of Engineering in Tuscaloosa, Alabama, and the head of the Computer Laboratory of Ambient and Wearable Systems. His research interests span wireless, ambient and wearable devices, and methods of biomedical signal processing and pattern recognition. Devices developed in his laboratory include a wearable sensor for objective detection and characterization of food intake, a highly accurate physical activity and gait monitor integrated into a shoe insole, a wearable sensor system for monitoring of cigarette smoking, and others. His research has been supported by the National Science Foundation, National Institutes of Health, National Academies of Science, as well as by state agencies and private industry and foundations.

Yu-Chiao Chiu

Educational Activity Co-Chair
Univ. of Pittsburgh Medical Center
Bio-sketch: Dr. Chiu’s research interests include bioinformatics, machine learning, cancer genomics, and pharmacogenomics. The goal of his research is to systematically model genomics and pharmacogenomics to study cancer biology and improve cancer therapy. He is the recipient of a NIH/NCI K99/R00 Pathway to Independence Award for his work to develop deep learning methods that extract multi-omic signatures to predict the responses of pediatric cancer cells to chemical and genetic perturbations. He has received grants for his work from the Fund for Innovation in Cancer Informatics (ICI), the UPMC Hillman Cancer Center Developmental Pilot Program, Pittsburgh Liver Research Center (PLRC) Pilot & Feasibility Grant, and the San Antonio Life Sciences Institute (SALSI). Dr. Chiu has published more than 100 research articles in high-impact clinical and computational journals and conference papers/abstracts. He has been an active member of the academic enterprise, teaching and mentoring others. Dr. Chiu has also received patents for his work to predict prognosis of patients with acute myeloid leukemia.

Ahmad Pahlavan Tafti

Educational Activity Co-Chair
Univ. of Pittsburgh
Bio-sketch: Ahmad P. Tafti is an assistant professor of Health Informatics in the Department of Health Information Management, where he is also leading the Pitt HexAI Research Laboratory. Starting in August 2022, he serves our community as the Vice Chair of IEEE Computer Society at Pittsburgh. Tafti has a deep passion for AI-Powered health care informatics and health data science with better patient diagnosis, prognosis and treatment using large-scale multiple clinical data sources and advanced computational algorithms. His main research interest spans Explainable AI and Machine Learning from the technical perspectives, and Musculoskeletal Diseases and Disorders from the clinical perspective.

Kathy L. Grise

Data Competition Chair
IEEE Future Directions Senior Program Director
Bio-sketch: Kathy Grise, Senior Program Director – IEEE Future Directions, supports new and emerging initiatives, including cloud computing, big data, digital realities, AI/ML, digital twins, digital transformation, and quantum, supports IEEE Future Directions, and manages the digital presence team for Future Directions. Ms. Grise serves as the Technical Program Chair of the IEEE COMPSAC 2024 Symposium – Data Sciences, Analytics, & Technologies (DSAT). Prior to joining the IEEE staff, Ms. Grise held numerous positions at IBM, and most recently was a Senior Engineering Manager for Process Design Kit Enablement in the IBM Semiconductor Research and Development Center. Ms. Grise led the overall IT infrastructure implementation, and software development in support of semiconductor device modeling verification, packaging, and delivery; device measurement and characterization data collection and management, and automation for device modeling engineers. Ms. Grise is a graduate of Washington and Jefferson College, and an IEEE Senior member.

Subhamoy Mandal

Data Competition Co-Chair
IIT Kharagpur
Bio-sketch: Dr. Subhamoy Mandal is currently a Clinical Applications Engineer and Research Lead with Maxer Endoscopy GmbH (part of Erbe Elektomedizin Group), and an Affiliated Researcher with the Technical University of Munich. Previously, he was a Research Scientist in Molecular Imaging at the Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg. Previously, he was a DAAD PhD scholar at the Chair of Biological Imaging at TU München, and the Institute of Biological and Medical Imaging at Helmholtz Zentrum München. He received his MS (by research) from the Indian Institute of Technology Kharagpur, and B.E. in Biomedical Engineering from Manipal University, Karnataka, India. He is a recipient of the prestigious DAAD PhD Scholarships and the UK Commonwealth Scholarship. His areas of interest are Medical Signal & Image Processing, Medical Imaging and point-of-care affordable healthcare technologies. Subhamoy is an active Member of IEEE, and is a recipient of Computer Society’s Richard E. Merwin Student Scholarship. He was the 2013-14 Student Rep and AdCom member of IEEE Engineering in Medicine and Biology (EMB) Society, 2010-12 Chair, IEEE Education Society Student Activity Committee (IEEE EdSocSAC), and was awarded the IEEE Student Leadership Award (conferred by EdSoc) in 2013 for his contributions, He was the Founding Chair, IEEE EMB Student Club of IIT Kharagpur, which has been awarded the Best New Student Club/Chapter Award 2010 by IEEE EMBS Student and Member Activity Committee. He has been a Member of IEEE Ad-hoc Committee on Social Media Policy performing under the aegis of the IEEE Board of Directors, and also actively volunteered with the IEEE Student Branches at IIT Kharagpur(Treasurer 2009-10) and MIT Manipal. Subhamoy has been closely associated with several corporate organizations including Philips, GE and Microsoft. During his internships with Philips BOP and the master’s thesis, he has focused on developing low-cost point of care technologies to address the healthcare challenges of emerging economies. At GE Global Research his primary area of focus has been Magnetic Resonance Imaging (MRI) and its application in Brain Iron Quantification, leading to early diagnosis of Alzheimer’s and other neurodegenerative diseases. His goal is to achieve success in innovating technical and user-friendly solutions using the expertise of Biomedical engineering and domain knowledge of Medical Sciences by synchronized efforts in a collective venture.

Bobak Mortazavi

Data Competition Co-Chair
Texas A&M Univ.
Bio-sketch: My research interests include end-to-end research on medical embedded systems and the application of data mining and machine learning algorithms necessary to make personalized, preventative medical treatments possible through advanced health analytics . My background is in embedded systems design, where I studied sensor fusion, reconfigurable architectures and systems, hardware accelerators, and gpu computing. During my Ph.D. I applied data mining and machine learning techniques to these systems to develop a personalized, exercise-level activity-recognition video game with wearable sensors. I am now primarily concerned with the ability to use supervised and unsupervised techniques to learn more about medical prediction and risk-stratification in order to better develop personalized medical systems, prediction models, comparative effectiveness techniques, and combine wearable sensors and other necessary data to make a clinical impact at the system level, provider level, and patient level.

Tayo Obafemi-Ajayi

Data Competition Co-Chair
Missouri State Univ.

Ryan King

Data competition co-chair
Texas A&M Univ.
Bio-sketch: Ryan King is a Ph.D. student in the Department of Computer Science & Engineering at Texas A&M University, specializing in multimodal modeling, unsupervised pretraining, and learning robust patient representations for clinical outcomes predictions. He was awarded the Engineering Graduate Merit Fellowship by Texas A&M University in 2021 for his commitment to academic excellence. Ryan is dedicated to advancing the fields of machine learning and healthcare, with a focus on leveraging his research to improve patient care and medical decision-making. His work exemplifies a profound passion for applying cutting-edge technology to real-world challenges, ultimately aiming to enhance the well-being of individuals through innovative solutions.

Robert Richer

Social Activity Chair
Friedrich Alexander Univ.

May D. Wang

Steering Committee
Georgia Tech & Emory Univ.
Bio-sketch: Dr. May Dongmei Wang is Wallace H. Coulter Distinguished Faculty Fellow and full professor of Biomedical Engineering, Electrical and Computer Engineering, Computational Science and Engineering at Georgia Institute of Technology (GT) and Emory University (EU) in Atlanta, Georgia, USA. She is Director of Biomedical Big Data Initiative, Georgia Distinguished Cancer Scholar, Petit Institute Faculty Fellow, Kavli Fellow, AIMBE Fellow, IAMBE Fellow, IEEE Fellow, and Board of Directors of American Board of AI in Medicine. She has 20+ years academic professorship and ~4 years industrial research experience, focusing on Biomedical Big Data with AI-Driven Intelligent Reality (IR) for predictive, personalized, and precision health (pHealth). She published 300+ articles in referred journals and conference proceedings with more than 15K Google Scholar citations, and has delivered 300+ invited and keynote lectures. Dr. Wang received BEng from Tsinghua University China, and MS with PhD degrees from GT. She is a recipient of GT Outstanding Faculty Mentor for Undergrad Research Award, and EU MilliPub Award (for a high-impact paper that is cited over 1,000 times. Dr. Wang is the Senior Editor for IEEE Journal of Biomedical & Health Informatics (Impact Factor 7.7), an Associate Editor for IEEE Transactions for BME and IEEE Reviews for BME, a panelist for NIH CDMA (Clinical Data Management and Analysis) Study Section, NSF Smart and Connect Health, and Brain Canada. She was 2014-2015 IEEE IEEE Engineering in Medicine and Biology Society (EMBS) Distinguished Lecturer, and an Emerging Area Editor for Proceedings of National Academy of Sciences (PNAS). Over the past years, Dr. Wang served as GT Biomedical Informatics Program Co-Director in Atlanta Clinical and Translational Science Institute (ACTSI), Director of Bioinformatics and Biocomputing Core in NIH/NCI-sponsored U54 CCNE, Co-Director of GT Center of Bio-Imaging Mass Spectrometry, and was GT President LeadingWomen, GT Provost Emerging Leaders, and GT Carol Ann and David Flanagan Distinguished Faculty Fellow. Dr. Wang’s research has been supported by NIH, NSF, CDC, Georgia Research Alliance, Georgia Cancer Coalition, Shriners’ Hospitals for Children, Children’s Health Care of Atlanta, Enduring Heart Foundation, Coulter Foundation, Imlay Foundation, Microsoft Research, HP, UCB, and Amazon. Dr. Wang is 2023-2024 national Executive Leadership in Academic Technology, Engineering and Science (ELATES) Fellow. She has been making major contributions to the growth of Biomedical and Health Informatics Technical Community in IEEE-EMBS since 2012, and Intelligent Reality growth within IEEE. Professor Wang is an elected member of International Academy of Med. and Bio. Eng. (IAMBE) Executive Committee, and VP Conference of IEEE-EMBS.

Andrew F. Laine

Steering Committee
Columbia Univ.
Bio-sketch: As director of the Heffner Biomedical Imaging Lab at Columbia, Andrew Laine focuses on the mathematical analysis and quantification of medical images, signal and image processing, computer-aided diagnosis and biomedical / imaging informatics. His work is based on imaging structures at the molecular, cellular, tissue, and organ levels of analysis. The goal is to develop biomedical technology for unmet clinical needs and to transition that technology into commercial products that will improve healthcare and save lives. Laine was the first to use multiscale “wavelet” representation to enhance subtle details in mammograms. Today, the algorithm he developed in 1992 is used in almost all commercial digital mammography systems. Currently, Laine is applying multiresolution wavelet techniques to classify pulmonary emphysema. He is also collaborating on a project in medical informatics to enable clinicians to better diagnose a patient using both text and annotated findings from medical images. Laine’s work draws on such techniques as time-frequency decompositions, speckle tracking, texture analysis, variational segmentation, parametric deformable models, and image reconstructions.

Stephen Wong

Steering Committee
Methodist Hospital & Weill Cornell Medical College
Bio-sketch: Dr. Wong holds the John S. Dunn, Sr. Distinguished Endowed Chair in Biomedical Engineering; he is also a Professor of Radiology, Pathology, Laboratory Medicine, Neurology, and Neurosciences, the Associate Director of Translational Research at Methodist Cancer Center, and Chief of Medical Physics and Chief Research Information Officer at Houston Methodist Hospital. In addition, he serves as the Founding Director of the Ting Tsung and Wei Fong Chao Center for BRAIN (Bioinformatics Research and Imaging in the Neurosciences) and Founding Director of the Center for Modeling Cancer Development at Houston Methodist Research Institute. He also holds a dozen of other academic posts across institutions in Texas Medical Center as well as overseas universities and medical schools. An internationally acclaimed bioengineer and imaging scientist, Dr. Stephen Wong has led teams that developed production automation for first very large scale integration (VLSI) 1MB computer memory chip and the largest online brokerage trading system, and contributed to the first hospital-wide digital radiology image management system in US academic medical centers. Dr. Wong has more than twenty years of research and management experience in industry and academia, including Hewlett-Packard, AT&T Bell Laboratories, the Japanese Fifth Generation Computer Systems Project, Philips Medical Systems and Royal Philips Electronics, Charles Schwab, University of California – San Francisco/Berkeley, Harvard University and Houston Methodist Hospital. He received his senior executive education from the MIT Sloan School of Management, Stanford University Graduate School of Business and Columbia University Graduate School of Business. He holds many patents and has published over 300 peer-reviewed papers and four books. He also serves on and chairs NIH study panels, conference program committees, and the editorial boards of twelve scientific journals. As an international authority, he is sought as a speaker on medical imaging, systems biology, healthcare IT, drug development, biophotonics, clinical neuroscience and other related topics.

Dimitrios I. Fotiadis

Steering Committee
Univ. of Ioannina
Bio-sketch: Prof. Dimitrios I. Fotiadis received the Diploma degree in chemical engineering from the National Technical University of Athens, Athens, Greece, and the Ph.D. degree in chemical engineering and materials science from the University of Minnesota, Minneapolis. He is currently a Professor of Biomedical Engineering in the Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece, where he is also the Director of the Unit of Medical Technology and Intelligent Information Systems, and is also an Affiliated Member of Foundation for Research and Technology Hellas, Institute of Molecular Biology and Biotechnology, Dept. of Biomedical Research. He was a Visiting Researcher at the RWTH, Aachen, Germany, and the Massachusetts Institute of Technology, Boston. He has coordinated and participated in more than 250 R&D funded projects (in FP6, FP7, H2020, and national Projects), being the coordinator (e.g. INSILC, TAXINOMISIS, HOLOBALANCE, CARDIOCARE etc.) and Technical coordinator (e.g. SMARTOOL, KARDIATOOL, TO_AITION, etc.). He is the author or coauthor of more than 300 papers in scientific journals, 500 papers in peer-reviewed conference proceedings, and more than 50 chapters in books. He is also the author/editor of 30 books. His work has received more than 18,000 citations (h-index=68). He is IEEE EMBS Fellow, EAMBES Fellow, Fellow of IAMBE, member of the IEEE Technical Committee of information Technology in Healthcare, Editor in Chief of IEEE Journal of Biomedical and Health Informatics, Member of the Editorial Board in IEEE Reviews in Biomedical Engineering, Associate Editor for IEEE Open Journal in Engineering in Biology and Medicine and Computers in Biology and Medicine. His research interests include multiscale modelling of human tissues and organs, intelligent wearable/implantable devices for automated diagnosis, processing of big medical data, machine learning, sensor informatics, image informatics, and bioinformatics. He is the recipient of many scientific awards including the one by the Academy of Athens. He is the co-founder of PD Neurotechnology Ltd, UK.