Jun Deng (PhD, DABR, FAAPM, FASTRO) – Professor of Therapeutic Radiology; Director of Physics Research, Therapeutic Radiology, Yale University School of Medicine

Dr. Jun Deng is a Professor and Director of Physics Research at the Department of Therapeutic Radiology of Yale University School of Medicine, an ABR board certified medical physicist at Yale-New Haven Hospital, and the Principal Investigator of the Yale Smart Medicine Lab (YSML). 

With funding from NIBIB, NSF, NCI, DOE and YCC, Dr. Deng’s research has been focused on artificial intelligence, machine learning, big data, and medical imaging for early cancer detection, real-time clinical decision support, digital twins of cancer patients, as well as AI-empowered mobile health and smart medicine. 

Dr. Deng has been serving on the Editorial Board of numerous peer-reviewed journals, on the study sections of NIH, NSF, DOD, ACS, RSNA and ASTRO since 2005, and as scientific reviewer for various science foundations and institutions
since 2015. Dr. Deng is an elected fellow of the Institute of Physics, AAPM, and ASTRO.

Harold H. Hines, Jr. -Professor of Medicine (Cardiology), Yale University

Dr. Harlan Krumholz is a cardiologist and scientist at Yale University and Yale New Haven Hospital. He is the Harold H. Hines, Jr. Professor of Medicine. He is a leading expert in the science to improve the quality and efficiency of care, eliminate disparities and promote equity, improve integrity and transparency in medical research, engage patients in their care, and avoid wasteful practices. Recent efforts are focused on harnessing the digital transformation in healthcare to accelerate knowledge generation and facilitate the delivery of care aligned with each patient’s needs and preferences. 

Dr. Krumholz has been honored by membership in the National Academy of Medicine, the Association of American Physicians, and the American Society for Clinical Investigation. He was named a Distinguished Scientist of the American Heart Association and received their Award of Meritorious Achievement and their Clinical Research Prize. He served as a member of the Advisory Committee to the Director of the National Institutes of Health. He is a co-founder of HugoHealth, a patient-centric platform to engage people as partners in research and clinical care, facilitate the secure acquisition and movement of digital health data, and promote learning health communities.

He is a co-founder of Refactor Health, an enterprise healthcare AI-augmented health data management company. Dr. Krumholz has published more than 1000 articles and three books and has an h-index of more than 200.

Qi Wang (PhD) – Professor of Mathematics, University of South Carolina

Dr. Qi Wang is a professor of Mathematics at the Department of Mathematics at the University of South Carolina. He is an applied and computational mathematician and modeler.

His research interests include modeling and computation of complex systems in materials and life science, development of efficient numerical algorithms for partial differential equations, data science and machine learning applications in materials and life science.

He is currently developing an individualized, multiscale, multimodal digital twin framework for a cancer patient to be used in optimizing the patient treatment pathway. He is especially interested in developing cutting-edge deep learning models to approximate complex biomedical systems of spatial-temporal resolution. He has published over 185 peer-reviewed journal papers and has been continuously funded by federal funding agencies.

Ying Ding (PhD) – Bill & Lewis Suit Professor, School of Information & Dell Medical School, University of Texas at Austin

Dr. Ying Ding is Bill & Lewis Suit Professor at School of Information, University of Texas at Austin. 

Her current research interests include data-driven science of science, AI in healthcare, Semantic Web, knowledge graph, data science, scholarly communication, and the application of Web technologies. 

She has been involved in various NIH, NSF and European-Union funded projects. She has published 240+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press and Chinese Academy of Sciences, and serves as the editorial board member for several top journals in Information Science and Semantic Web. She is the co-founder of Data2Discovery company advancing cutting edge AI technologies in drug discovery and healthcare.

Huanmei Wu (PhD) – Professor and Department Chair of Health Services Administration and Policy; Assistant Dean for Global Engagement, Temple University

Dr. Wu is the Department Chair of Health Services Administration and Policy and Assistant Dean for Global Engagement at Temple University College of Public Health. 

With funding from NIH, NSF, USAID, JDRI, RWJF, local organizations, and national industries, Dr. Wu’s research covers bioinformatics, health informatics, clinical informatics, big data analytics, predictive modeling, machine learning, precision medicine, public health, and clinical decision support systems (CDSSs). Her work features interdisciplinary collaborations with academia, community health centers, research institutes, industrial partners, and various stakeholders in healthcare. 

Dr. Wu has been serving on program committees for numerous national and international conferences, as guest editor of several peer-reviewed journal special issues, on the study sections of NIH and NSF, and as a scientific reviewer for various science foundations and institutions. 

Hongfang Liu (PhD) – McWilliams Chair Professor and Director of Translational AI Excellence and Applications in Medicine, University of Texas Health Science Center at Houston

Dr. Liu’s research has been extensively funded by the National Science Foundation and the National Institute of Health (NIH) since 2003. Her work accelerates the pace of knowledge discovery, implementation and delivery of
improved health care. 

Dr. Liu is a member of several professional societies,
including the American Medical Informatics Association (AMIA) and the International Society for Computational Biology (ISCB). Dr. Liu has extensive expertise in data normalization, clinical NLP, and predictive modeling in the healthcare domain with nearly 400 research articles. She led the data normalization program in Mayo Strategic Health IT Advanced Research Projects (SHARP) Program Area 4 Consortium (SHARPn), the core technology base for SHARPn, to enable the use of EHR for secondary purposes, such as quality measurement, comparative effectiveness research, translational research, high
throughput phenotyping, and outcomes research.

Shimei Pan (PhD) – Associate Professor, University of Maryland Baltimore County

Dr. Shimei Pan is an Associate Professor at the Information Systems Department of UMBC. Before joining UMBC, Dr. Pan was a research scientist at IBM Watson Research Center in New York. 

Her primary research interests are AI, Machine Learning, and Natural Language Processing (NLP). She is also interested in ethical AI/ML and human-AI interaction. 

Dr. Pan has authored 100+ peer-reviewed papers in AI conferences and journals. She has also served on the program committees for major international conferences (e.g., ACL, EMNLP, NAACL, and IJCAI). Dr. Pan has co-chaired several major international conferences and workshops such as IEEE ICTAI 2020, ACM IUI 2019, ACM IUI 2015, IJCAI workshop on Artificial Intelligence and Computational Psychology, and IEEE BIBM workshop on Data Mining in Translational Biomedical Informatics

Haiying Shen (PhD) – Associate Professor, Computer Science Department, University of Virginia

Dr. Haiying Shen is currently an Associate Professor in the Department of Computer Science and affiliated with the School of Data Science at the University of Virginia. 

Her research interests include distributed computer systems, cloud and edge computing, distributed machine learning, big data and cyber-physical systems. 

In these areas, she has published more than 350 journal and conference papers in top tier journals and conferences. Her papers received George N. Saridis best transactions paper award 2021, the best paper awards in CloudCom2016 and NAS2018, best paper runner-up award in ICCCN2015, best paper award nominees in ICPP2021, MASS2011 and CCGrid2009. She was a recipient of the TCSC Mid-career Award 2015, IBM Faculty Award 2015, Microsoft Faculty Fellowship Award 2010, and NSF CAREER Award 2013. She is an Associate Editor for the IEEE/ACM Transactions on Networking (TON), IEEE Transactions on Mobile Computing (TMC), IEEE Networking Letters (NL). She is also a program committee member of many leading conferences, and the former program co-chair for a number of international conferences. She is a senior member of the IEEE and the ACM.

Tanveer Syeda-Mahmood (PhD) – IEEE Fellow, AIMBE, MICCAI, IBM Fellow, IBM Almaden Research Center

Dr. Tanveer Syeda-Mahmood is an IBM Fellow and Global Imaging AI Leader in IBM Research. Dr. Syeda-Mahmood graduated from the MIT AI Lab in 1993 with a PhD in Computer Science. 

Prior to IBM, she worked as a Research Staff Member at Xerox Webster Research Center, Webster, NY. She joined IBM Almaden Research Center in 1998. Dr. Syeda-Mahmood is the General co-Chair of MICCAI 2023, the premier conference in medical imaging. She is also the Program co-Chair of IEEE ISBI 2022 to be held in Calcutta, India. She was the General Chair of the First IEEE International Conference on Healthcare Informatics, Imaging, and Systems Biology, San Jose, CA 2011. She was also the program co-chair of CVPR 2008. Dr. Syeda-Mahmood is a Fellow of IEEE. She is also the first IBMer to become an AIMBE Fellow. She is also a member of IBM Academy of Technology. Dr. Syeda-Mahmood was declared Master Inventor in 2011 and in 2019. She is the recipient of key awards including IBM Corporate Award 2015, Best of IBM Award 2015, 2016 and several outstanding innovation awards.

Aidong Zhang (PhD) – ACM Fellow, AIMBE, IEEE, William Wulf Faculty Fellow and Professor, University of Virginia

Dr. Aidong Zhang is a William Wulf Faculty Fellow and Professor of Computer Science, Data Science, and Biomedical Engineering at University of Virginia. She was the Founding Chair of the ACM (Association for Computing Machinery) Special Interest Group on Bioinformatics, Computational Biology, and Biomedical informatics (2010-2015) with more than 300 members. She served as the Editor-in-Chief of the IEEE Transactions on Computational Biology and Bioinformatics (TCBB) in 2017-2021. 

Her research interests include machine learning, data mining/data science, bioinformatics, and health informatics. She has authored over 390 research publications in these areas. She is a fellow of ACM, AIMBE, and IEEE.

Luke Achenie (PhD) – FAIChE, Professor of Chemical Engineering; Director of Multiscale Scientific Computing and Data Science Lab, Virginia Tech

Dr. Luke Achenie is currently professor of Chemical Engineering with courtesy appointments in Biomedical Engineering and Mechanics (BEAM) and Health Sciences (FHS) all at Virginia Tech. 

Dr. Achenie has focused his research in computational modeling of multi-scale systems with Mathematical Programming (optimization) as a core technology in his research. Achenie’s current research is in data science (machine learning and AI), molecular dynamics, and optimization (math programming). 

Dr. Achenie has authored/co-authored more than 190 papers in journals and peer-reviewed conference articles. Dr. Achenie once served as a rotating NSF Program Director and has served on numerous committees in ACS (American Chemical Society) and the AIChE (American Institute of Chemical Engineering). He is also an active member of SIAM and AAAS. He is AIChE Fellow, Carnegie African Diaspora Fellow and member of Connecticut Academy of Engineering. Finally, Dr. Achenie has served on several NIH study sections (former standing member of NIH/BDMA and NIH/BCHI) and NSF panels.

Ying Xiao (PhD) – FAAPM, Professor of Radiation Oncology, University of Pennsylvania

Dr. Ying Xiao is a Professor and an ABR board certified medical physicist at the Department of Radiation Oncology of University of Pennsylvania. 

Dr. Xiao has significant experience in developing methods and strategies to convert the data into knowledge to better guide patient treatment (Big Data) and adapted our clinical and clinical research quality processes for high efficiency and accuracy with machine learning/artificial intelligence including the optimization of radiation therapy treatment plan using imaging, clinical information. 

Dr. Xiao works closely with NCI’s clinical trial network and is familiar with the CDISC requirements of the clinical trial data elements. From the professional standardization effort with American Association of Physicists in Medicine (AAPM) and American Society of Therapeutic Radiation Oncology (ASTRO), clinical standards such as AAPM TG-263 and HL7 are regularly utilized. Dr. Xiao and colleagues have conducted investigations into obtaining the best radiotherapy treatment plans that target the tumor while sparing critical structures; developed quality assurance science; provided AI/machine learning models to assist cancer therapy decision making.

Sanjay Purushotham (PhD) – Assistant Professor, University of Maryland Baltimore County

Dr. Sanjay Purushotham is an Assistant Professor in the Department of Information Systems at the University of Maryland, Baltimore County. He obtained his Ph.D. in Electrical Engineering from the University of Southern California. 

His research interests are machine learning, deep learning, computer vision, and its applications to biomedical informatics, climate sciences, and multimedia data mining. His current work involves developing novel deep learning models for data-driven analysis of healthcare time series data. 

He has produced more than 50 peer-reviewed publications at machine learning/data mining venues such as KDD, AAAI, ICML, and NeurIPS and has won the best paper and best poster awards at international conferences. His research is funded by NSF, NASA, ARL, and ESIP. He has co-chaired and co-organized the Time Series workshops at IJCAI in 2022 and the KDD conferences from 2016 to 2022.

Zhiyuan Chen (PhD) – Professor of Information Systems, University of Maryland Baltimore County

Dr. Zhiyuan Chen has obtained a BS and a MS from Fudan University, China, and a PhD in Computer Science from Cornell University. He is currently a professor at the Department of Information Systems, University of Maryland Baltimore County. 

His research covers the areas of data science, big data, privacy preserving data mining and data management, data exploration and navigation, semantic-based search and data integration using semantic networks, adversarial learning and its applications in cyber security. 

He has published extensively in these areas and has received funding from NSF, Department of Energy, IBM, Office of Naval Research, MITRE, and Department of Education.

Richard Fletcher (PhD) – Research Scientist, Mechanical Engineering & Lincoln Laboratory, MIT; Research Scientist, Psychiatry, Massachusetts General Hospital

Dr. Rich Fletcher directs the Mobile Technology Group which develops a variety of wearable sensors, mobile devices, diagnostic algorithms, and machine learning/AI algorithms to address problems in point of care diagnostics, behavior medicine, and mental health. Dr. Fletcher works to address health disparities through his extensive work in global health, with funded research from NIH, Gates Foundation and USAID. 

Dr. Fletcher is also a research scientist at Massachusetts General Hospital, Recovery Research Institute, where he applies Digital Phenotyping, Internet of Things, and mHealth platforms to address the serious problem of drug addiction and substance abuse.  In 2011, Dr. Fletcher was an early creator of mHealth systems for Just-In-Time interventions (US Patent 8,655,441) and developed the MIT Media Lab’s first generation of wearable sensors for ambulatory measurement of psychophysiology (now commercialized through Empatica). 

Dr. Fletcher holds over 20 patents in the areas of wireless sensors and wearable devices. As a student, Dr. Fletcher worked directly with Neil Gershenfeld and Kevin Ashton who coined the name “Internet of Things.” Dr. Fletcher is also a military veteran and works as a visiting scientist at MIT Lincoln Laboratory to support military applications of wireless and mHealth technologies. Dr. Fletcher’s extensive prior work in RFID at the MIT Media Lab and MIT’s Auto-ID Lab helped lay the foundation for Digital Twin paradigms for the Internet of Things, which is now being adapted for human health.

Cecil Lynch (MD, MS) – Accenture Global Biomedical Informatics Lead

Dr. Cecil Lynch is recognized as a thought leader in health informatics and has served in leadership roles within Academic and Clinical Healthcare Systems (UC Davis), the HL7 Standards Development Organization including as a co-Chair of the Vocabulary Technical Committee, and currently as a member of the Architectural Review Board and the FHIR Governance Board. He serves as a National and International advisor on Health Informatics and has served numerous government agencies. He designed and implemented the Semantic Web ontology and JESS Rules Engine-based CDC National Tuberculosis Surveillance System. He was technical lead and architect of the Template Service to validate quality of incoming data, for the National Australian Personally Controlled Electronic Health Record (PCEHR) program that supported aggregation of all personal health data nationally. This effort included integration of data from dozens of different EMR systems. As Chief of the State of California Office of Informatics and Surveillance, he designed strategy for systems integration, surveillance systems design and vendor selection, HIPAA compliance across divisions. 

At Accenture he is a Subject Matter Advisor on Big Data in Healthcare, Health and Clinical Analytics, Health Data Exchange and Connectivity. He serves as a domain expert in data standards, interoperability and enterprise architecture and is the Product Owner and Enterprise Architect of the Accenture Healthcare on Azure Platform.

Evangelia Katsoulakis (MD) – Veterans Administration

Dr. Evangelia Katsoulakis received her undergraduate training from MIT, with dual degrees in Biology and Economics. She is an attending physician in the Department of Therapeutic Radiology at the James A. Haley Tampa VA. She is an experienced radiation oncologist whose passion is to improve the lives of patients through the use of data science and health informatics. She is board eligible for Clinical Informatics. 

She currently is a core member of the VA ROQS Radiation Oncology Quality Survey Program in the VA and works to develop national quality measures in radiation oncology. She also works with Precision Oncology in the VA. She is a founding member of Precision GRID, Genomics Clinical Radiotherapy Information Database, which is an effort that will generate the largest collection of radiation oncology data merged with clinical and genomic data. She has engaged in multiple projects and collaborations in the fields of radiomics, radiogenomics, genomics, and informatics. She leads machine learning initiatives in the VA and has obtained Department of Defense Grant funding as well as Florida State Funding for her work. She guides the clinical decision support modules and overall schema for trial design/schema as well as modeling care of the individual cancer patient.

Perry W. Payne, Jr. (MD, JD, MPP) – George Washington University, Dept. of Clinical Research and Leadership/Dept. of Health Policy

Dr. Perry Payne is the Healthcare Transformation Leaders at George Washington University. He has taught, researched, and written papers on the ethical, legal, and social implications of innovative health care technologies for over ten years. His research interests include increases access to novel technologies, utilizing technology to better determine the variation in response to prescription drugs in diverse populations, and translating innovative research into community benefits as a method of addressing health disparities.

Jim Chen (PhD) – University of Kentucky, Associate Professor, Internal Medicine; Associate Professor, Computer Science

Dr. Jin Chen is an associate professor in the Institute for Biomedical Informatics (IBI), Department of Internal Medicine and Department of Computer Science, the University of Kentucky since 2016. 

Dr. Chen’s research focuses on the development of data mining and computer vision algorithms to solve problems in medical and biological informatics. He has developed a series of algorithms for phenomics and genomics data analysis, including inter-functional clustering, heterogeneity pattern recognition, phenotype ontology development, phenotype data quality control, gene ranking, data visualization, etc. He is also interested in biological network reconstruction using high-dimensional omics data. 

His work covers regulatory module identification, organelle communication pattern mining, and data-driven ontology construction. He has published more than 50 papers in biomedical informatics, computer science, and biology. Dr. Chen’s research has been supported by NSF, NIH, DOE, MSU and UKY.

Jinwei Liu (PhD) – Assistant Professor, Florida A&M University

Dr. Jinwei Liu is an Assistant Professor in the Department of Computer and Information Sciences at Florida A&M University (FAMU). He received the Ph.D. degree in Computer Engineering from Clemson University and the M.S. degree in Computer Science from Clemson University and University of Science and Technology of China.

His research interests include cloud computing, AI/ML, health care, cybersecurity, big data, data mining, social networks, and wireless networks, etc. His work has led to a number of top journal/conference publications (e.g., IEEE TON, IEEE TMC, IEEE TPDS, etc.).

He was recognized for outstanding achievement in academic publications and was awarded a FRAP grant at FAMU. He has served regularly on program chairs/committees, proceeding editor of several international conferences/workshops such as CCGRID, ICCCN, ISCAI, ICFEC, INTERNET, INFOCOMP, IWMSN, NEAC, ICCCBDA, SOENG, etc., and the Editor-in-Chief and/or Editorial Board Member of several journals. He is a member of the IEEE and ACM.

Leili Shahriyari (PhD) – Assistant Professor, University of Massachusetts Amherst

Dr. Leili Shahriyari is an assistant professor at University of Massachusetts Amherst. Her lab, currently with three graduate students, four undergrads, and two post docs, develops innovative frameworks to systematically employ a combination of machine learning (ML) and statistical methods as well as mathematical techniques to arrive at personalized cancer therapies. She studied computer science with a specific focus on ML and data science, and mathematics, particularly differential geometry.

During her postdoc at MBI as an MBI/NSF funded postdoctoral fellow, she pursued an independent research program and established collaboration with biologists and physicians. Her pioneering works on computational oncology have led to the UT System Rising STARs award, more than thirty invited talks, and several sponsored travel awards such as AWM-NSF and two Landahl-Busenberg travel awards, invitations as a panelist on international conferences, and reviewer for more than 18 different scientific journals, Otto-Hahn-Medal of Max Planck Institute, an NSF-NIH review panel, and an NCI review panel. Moreover, her R21 NCI grant received impact score 14 and percentile 1. Since she has a strong background in mathematical modeling, bioinformatics, and ML, she will participate in developing the mathematical model and connecting the proposed bioinformatics, mathematical and ML models.

Amit Majumdar (PhD) – Associate Professor, Department of Radiation Medicine and Applied Sciences, University of California San Diego

Dr. Amit Majumdar is the Director of SDSC’s Data Enabled Scientific Computing division and is an Associate Professor in the Department of Radiation Medicine and Applied Sciences at UC San Diego. He received his B.S. from Jadavpur University, Calcutta, India in 1985, M.S. from Idaho State University in 1988 and Ph.D. from University of Michigan in 1996. 

After working one year at the Ford Research Laboratory in Michigan, he joined the San Diego Supercomputer Center in 1997. His research interests are in high performance computing (HPC), computational science, and cyberinfrastructure software and services such as science gateways. He has developed parallel algorithms for various kinds of HPC machines and is interested in optimizing, scaling and analyzing performance of scientific applications on HPC machines. He has been involved in computational science projects where medical applications utilize HPC and cyberinfrastructure. 

Some of his recent funded projects include developing the neuroscience gateway (NSG) for computational neuroscientists (NSF and NIH funded), analyzing performance of scientific applications on next generation dense many core architectures (NSF funded), developing parallel I/O libraries for physics-based modeling codes (DoD funded) etc. He serves as a PI or Co-PI on multiple research projects funded by NSF, NIH, DoD, AFOSR, and industry (Intel, Engility, Microsoft).

Subhashini Sivagnanam (MS) – Manager of Cyberinfrastructure Solutions and Services, SDSC, University of California San Diego

Subhashini Sivagnanam is an expert in scientific data integrity, cyberinfrastructure (CI) tool development, and blockchain-based solutions. Subhashini Sivagnanam leads the Cyberinfrastructure Solutions and Services (CISS) group at SDSC. 

Her primary areas of research focus are on the fields of distributed computing, cyberinfrastructure development, scientific data management, and reproducible science. 

As a PI, Co-PI, or Key Personnel, she has been involved in various NSF, NIH, and SDSC internal funded projects that involve developing CI research software, providing CI services to the research community, and carrying out HPC-related research.

Omar Martinez (JD, MPH, MS) – Associate Professor, Department of Population Health Sciences, College of Medicine, University of Central Florida

Dr. Omar Martinez completed a dual degree program, simultaneously gaining his master’s degree in public health and juris doctorate at Indiana University-Bloomington. He also completed a master’s degree in clinical research methods at Columbia University Mailman School of Public Health. Professor Martinez completed an NIH T32 postdoctoral research fellowship in behavioral science research in HIV prevention at the HIV Center for Clinical and Behavioral Studies at Columbia University and the New York State Psychiatric Institute. 

Professor Martinez’s research expertise includes the correlates, prevalence, and prevention of substance use, mental illness, and HIV among underserved and vulnerable populations. His work has contributed to a better understanding of the impact of syndemic factors, including both individual-level factors (e.g. substance use and mental health problems) and the larger social context (e.g. immigration policies, stigma, discrimination, structural racism, violence, and cultural imperialism) that affects the overall health outcomes among systematically and structurally excluded populations.

Sung Jun Ma (MD) – Assistant Professor, Department of Radiation Oncology, Ohio State University Comprehensive Cancer Center

Dr. Sung Jun Ma is an Assistant Professor in the Department of Radiation Oncology at the Ohio State University Comprehensive Cancer Center, treating patients with head and neck and thoracic malignancies. Dr. Ma’s research interests include machine learning in oncology, personalized medicine, outcomes research, racial and socioeconomic disparities, financial toxicity, symptom burden, and quality of life. Dr. Ma has authored over 60 peer-reviewed manuscripts and is a member of ASTRO and ASCO. Dr. Ma’s research is funded by Roswell Park Comprehensive Cancer Center and NCCN/AstraZeneca.

Rui Zhang (PhD) – Associate Professor, Department of Surgery, University of Minnesota

Dr. Zhang is Professor and Founding Chief of Division of Computational Health Sciences at the University of Minnesota. He was named as McKnight Presidential Fellow and hold several leadership roles, including Chair of AI and Data science for Healthcare workgroup within the UMN’s Data Science and AI Hub, Associate Director of Health AI & Data Science for the Center for Learning Health System Sciences, the Director of Natural Language Processing/Information Extraction (NLP/IE) research program, and previously served as Director of NLP at UMN’s Clinical and Translational Science Institute. Dr. Zhang’s research is at the forefront of integrating novel AI with healthcare research and practice, analyzing multimodal biomedical data, including electronic health records, biomedical literature, and patient-generated data. His research is fully supported by multiple NIH grants as Principal Investigator, focusing on transformative AI projects including mining safety use of dietary supplements (two NCCIH R01s), discovering drug repurposing of Alzheimer’s disease (NIA R01), predicting breast cancer treatment related cardiotoxicity (NCI R01), identifying medical language bias in kidney transplantation (NIDDK R01), and develop knowledge graph on complementary and integrative health (NCCIH U01). He has published over 150 peer-reviewed articles, including Natural Medicine, Natural Communications, Natural Digital Medicine. His work has been reported by The Wall Street Journal, and interviewed byCBS News. Dr. Zhang is a Fellow of International Academy of Health Sciences Informatics (FIAHSI), Fellow of American College of Medical Informatics (FACMI) and Fellow of AMIA. He is the current Chair of AMIA Natural Language Processing (NLP) Working Group. Follow Rui on Twitter at @RuiZhang1229 and lab at http://ruizhang.umn.edu.

April Heyward – President, South Carolina Academy of Science

April Heyward is a Staff Scientist in the Department of Public Health Sciences focusing on
Artificial Intelligence in Public Health at the Medical University of South Carolina (MUSC). She
serves on the Leadership Team of the Clemson-MUSC AI Hub. Her teaching and research
interests include Artificial Intelligence, Data Science, Digital Twins for Health, Deep Learning,
Generative AI, Health Informatics, Large Language Models, Machine Learning, Public Health
and Epidemiology, Research Methods, and Scientometrics. She is a member of the Association
for the Advancement of Artificial Intelligence (AAAI), American Medical Informatics
Association (AMIA), American Public Health Association (APHA), APHA Epidemiology
Section, APHA Health Informatics Information Technology Section, Digital Twins for Health
Society (DT4HS), and the South Carolina Public Health Association. April serves as the Chair of
the DT4HS Membership Committee, a member of the AAAS (American Association for the
Advancement of Science) EPSCoR Advisory Board, and an NSF (National Science Foundation)
Reviewer.

April’s skills and experience includes R Programming (R Coding), RStudio IDE (Integrated Development Environment), Data Science, Machine Learning, Natural Language Processing, Text Mining, Bibliometric Analysis and Science Mapping (Web of Science Core Collection Data and PubMed Data), Sentiment and Emotions Analysis, Twitter API, Network Analysis, Primary and Secondary Data Collection, Data Curation, Data Wrangling, Data Analysis, Data Visualization, Quantitative Methods, Qualitative Methods, Descriptive and Inferential Statistics, and Survey Development and Analysis,.

Her educational background includes a Master of Research Administration from the University of Central Florida. She is in the Dissertation phase of the Doctor of Public Administration program at Valdosta State University. April is a Riley Institute Diversity Fellow at Furman University.

Jim St. Clair (University of Mississippi) – CEO of MyLigo, St.Clair Consulting; Global Health IT & Cybersecurity Leader

Jim St. Clair is a distinguished leader at the intersection of public health and technology, with over 25 years of experience driving digital transformation in healthcare. As president of his own consulting firm, he has provided strategic leadership in AI workforce development, interoperability, and health IT modernization, securing multi-million-dollar grants and contracts to advance public health initiatives. His tenure as Executive Director of Linux Foundation Public Health saw him expanding global collaborations, launching cutting-edge initiatives in healthcare AI and patient identity management, and fostering partnerships with WHO, UNDP, and national health agencies.

A visionary in health IT and cybersecurity, Jim has spearheaded numerous large-scale technology adoption efforts, including AI/ML applications, blockchain governance, and verifiable credential frameworks for healthcare. His leadership roles at both healthtech start-ups and non-profits underscore his expertise in aligning emerging technologies with industry standards to enhance patient identity verification, data security, and interoperability. His extensive contributions to HL7, IEEE, ISO, and other standards bodies demonstrate his commitment to shaping global health technology standards and driving meaningful industry collaboration.

Jim’s impact extends beyond corporate leadership to public speaking, consulting, and thought leadership in digital health. A recipient of multiple FedHealthIT 100 awards, he continues to influence policy and technological advancements in health IT. His ability to bridge the gap between technology and public health policy makes him a sought-after advisor and advocate for transformative solutions that enhance healthcare delivery, security, and accessibility worldwide.

Jim is a veteran and former naval officer, having served both in active and reserve capacities. Following his military service, he earned degrees from Texas A&M University, National Intelligence University, and the University of Mississippi.

Jake Y. Chen, PhD – Chief Bioinformatics Officer, UAB Informatics Institute

Dr. Jake Y. Chen is the Associate Director and Chief Bioinformatics Officer of the UAB Informatics Institute, a Professor of Genetics, Computer Science, and Biomedical Engineering, and Chief of the Informatics Section of the UAB Department of Genetics. Before joining UAB, Dr. Chen was the founding director of the Indiana Center for Systems Biology and Personalized Medicine at Indiana University and a tenured faculty member at Indiana University School of Informatics and Purdue University Computer Science Department. Dr. Chen has over 20 years of research and development experience in biological data mining, systems biology, and translational informatics in both Academia and the industry. He has over 150 peer-reviewed publications and presented worldwide on topics related to biocomputing, bioinformatics, and data sciences in life sciences. He was elected as the President-elect of the Midsouth Computational Biology and Bioinformatics Society (MCBIOS) in 2019. He also serves on the editorial boards of BMC Bioinformatics, Journal of American Medical Informatics Association (JAMIA), and Personalized Medicine. Dr. Chen’s contribution to the field of computational biology and bioinformatics was highly recognized. He was cited as one of “17 Informatics Experts Worth Listening To” by HealthTechTopia (2011), a grand-prize winner of the “Cancer Cell Drug Discovery Grand Challenge” by Innocentive.com (2012), three-time finalist as “Indiana’s Technology Educator of the Year” award by TechPoint (2012-14), and recently as one of the “Top 100 AI Leaders in Drug Discovery and Healthcare” by Deep Knowledge Analytics (2019).

Irina Babina, PhD – Cancer Geneticist; CEO, Concr

Trained as a geneticist, Irina spent over 12 years as a cancer scientist, developing targeted breast and gastric cancer therapies and researching mechanisms of cancer resistance at the Royal College of Surgeons and the Institute of Cancer Research in London. Seeing a lack of translation of promising science, she turned to funding management and investing, helping other researchers with the development of their healthcare projects, devolving over £120m of public and private funds into innovation. This led her to Concr – a deeptech company that applies astrophysics computational models to solve translational challenges in cancer treatment and care. After holding several leadership roles, she succeeded founder-CEO in January 2024.

Reinhard Laubenbacher, PhD – Professor of Medicine; Director, Laboratory for Systems Medicine, University of Florida

Dr. Laubenbacher joined the University of Florida in May 2020 as a professor in the Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine. He is the director of the Laboratory for Systems Medicine. Prior to joining UF, he served as director of the Center for Quantitative Medicine and Professor in the Department of Cell Biology in the University of Connecticut School of Medicine, with a joint appointment at the Jackson Laboratory for Genomic Medicine. He is a fellow of AAAS, the Society for Mathematical Biology, and the American Mathematical Society. He is president-elect of the Society for Mathematical Biology, having previously served as editor-in-chief of the Bulletin of Mathematical Biology, its flagship journal. Dr. Laubenbacher is a mathematician by training, and his broad research interests lie in computational and mathematical systems biology, with applications to human health. Most of his research is in collaboration with a broad spectrum of scientists and clinicians. An important focus of his work in recent years has been on the development of medical digital twin technology.

Zachary S. Brooks, PhD, MBA – Founder & CEO, UGenome AI; Founder & President, World Transplant Athletes

Zachary S. Brooks serves as the Founder and CEO for UGenome AI, a company whose vision is to make genomic medicine personal and accessible for everyone. UGenome’s leading product called ProPEx, helps people and clinics get precise information on the best matched medications to individuals based on their unique DNA. Dr. Brooks also serves as the Founder & President of World Transplant Athletes (WTA) whose motto is if you have a body with a new part, You Are a World Transplant Athlete. World Transplant Athletes generates research on the benefits of exercise post-transplation with academic partners then shares that information back to its 4,000 recipient followers on Instagram. Zachary is a two-time #1 best-selling Amazon author (“Discovering Your Human Algorithm” & “Discovering What Activates You”), 2021 Comeback-Giveback Awardee of the Chris Klug Foundation, and 2017 Flinn-Brown Fellow (Arizona). Dr. Brooks holds a Masters from University of Massachusetts Boston, earning his PhD from the both Colleges of Science and Humanities University of Arizona while studying bilingual decision making, and an Executive MBA from Quantic School of Business and Technology writing about pharmacogenomic digital twins. He serves as an advisory board member for The Beautiful Way based in Boston whose goal is to improve clinical trials representativeness. He is an avid cyclist who has competed internationally in soccer and cycling and speaks four languages having lived in 7 countries.

Stephen Aylward, PhD – Global Lead, Strategic Applied Research, Health Care & Life Sciences, NVIDIA; Adjunct Professor of Computer Science, University of North Carolina at Chapel Hill

Dr. Aylward serves as the Global Lead for Strategic Applied Research in the Health Care and Life Sciences: Digital Devices team at NVIDIA. His current research centers on leveraging AI in the creation and continuous update of high-fidelity, real-time, dynamic digital twins of patients—spanning multiple physiological systems—to optimize device design, intervention planning, procedural guidance, and outcome prediction.

With over 25 years of experience, Dr. Aylward has spearheaded NIH, DARPA, and DoD-funded research in medical imaging, and has played a pivotal role in the creation and leadership of widely used open-source platforms such as the Insight Toolkit (ITK), 3D Slicer, VolView, and MONAI. He has authored more than 200 publications, garnering over 17,000 citations.

Dr. Aylward is recognized as a MICCAI Fellow and holds an adjunct professorship in Computer Science at the University of North Carolina at Chapel Hill (UNC). He chairs the MONAI Advisory Board and serves on advisory boards for the Vanderbilt Institute for Surgery and Engineering, the Johns Hopkins Laboratory for Computational Sensing and Robotics, and Medtronic’s AI Technology Advisory Board.

Before joining NVIDIA, Dr. Aylward was Senior Director of Strategic Initiatives at Kitware, where he also founded the company’s North Carolina office. Earlier in his career, he was a tenured associate professor of Radiology at UNC.

Yuzhou Chen, PhD – Assistant Professor of Statistics, University of California, Riverside; Adjunct Professor, Temple University; Visiting Research Collaborator, Princeton University

Dr. Yuzhou Chen is a tenure-track Assistant Professor in the Department of Statistics at University of California, Riverside. He is also an adjunct professor in the Department of Computer and Information Sciences at Temple University and a Visiting Research Collaborator in Department of Electrical and Computer Engineering at Princeton University. Before that, Dr. Chen worked as a postdoctoral scholar in the Department of Electrical and Computer Engineering at Princeton University. Dr. Chen received his Ph.D. in Statistics from Southern Methodist University. His research focuses on geometric deep learning, topological data analysis, medical digital twins, knowledge discovery in graphs and spatio-temporal data, with applications to power systems, biosurveillance and environmental data analytics. His research has appeared in the top machine learning and data mining top conferences, including ICML, ICLR, NeurIPS, KDD, AAAI, ICDM, ECML-PKDD, etc. He was the recipient of 2024 American Statistical Association on Joint Statistical Computing and Statistical Graphics Section Best Student Paper Award, 2021/2022 American Statistical Association Section on Statistics in Defense and National Security Best Student Paper Award, and 2021 Chateaubriand Fellowship from the Embassy of France in the United States.