2025 - i2b2 Symposium-Presenters-v.xlsx

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1	Presenter	Affiliation	email	Topic title: Summary	Bio's	link to site

2	Gilbert Omenn, MD, PhD	University of Michigan	gomenn@med.umich.edu	Introduction	Professor of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, & Public Health, University of Michigan, Ann Arbor. Dr. Omenn’s research focuses on cancer proteogenomics, splice isoforms, and prediction of functions of unannotated proteins. He is a leader of the global Human Proteome Project. He is a member of the National Academy of Medicine and past president of the AAAS.
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4	Isacc Kohane	HMS	isaac_kohane@hms.harvard.edu	Keynote: Human Values Project: The AI we want for the Research we need. Moderator, The Future of i2b2 and LLMs: Transforming Cohort Discovery?	Isaac (Zak) Kohane, MD, PhD is the inaugural Chair of the Department of Biomedical Informatics and the Marion V. Nelson Professor of Biomedical Informatics at Harvard Medical School. He served as co-author of the Institute of Medicine Report on Precision Medicine that has been the template for national effort. He recently has taken the title of Editor-In-Chief of a new journal from the New England Journal of Medicine entitled NEJM AI Over the last 30 years, Zak’s research agenda has been driven by the vision of what biomedical researchers could do to find new cures, provide new diagnoses and deliver the best care available if data could be converted more rapidly to knowledge and knowledge to practice. In so doing, Kohane has designed and led multiple internationally adopted efforts to “instrument” the healthcare enterprise for discovery and to enable innovative decision-making tools to be applied to the point of care. At the same time, the new insights afforded by ’omic-scale molecular analyses have inspired him and his collaborators to work on re-characterizing and reclassifying diseases such as autism, rheumatoid arthritis and cancers. In many of these studies, the developmental trajectories of thousands of genes have been a powerful tool in unraveling complex diseases.
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6	Shawn Murphy	MGH, HMS	murphy.shawn@mgh.harvard.edu	Panelist, The Future of i2b2 and LLMs: Transforming Cohort Discovery? Moderator, Debate - Federated vs Centralized Networks: Optimizing Medical Data for Research: Centralized, Federated, and Hybrid Approaches Networks Panel - Federated Learning	Dr Murphy is also Professor of Neurology and Biomedical Informatics at Harvard Medical School. He has developed the initial Research Patient Data Registry (RPDR) for Partners HealthCare, a large data warehouse with 7 million patients and 3 billion rows. Dr. Murphy is the chief architect of the NIH Sponsored Informatics for Integrating Biology and the Bedside (i2b2).
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8	Griffin Weber	BIDMC, HMS	griffin_weber@hms.harvard.edu	Panelist, The Future of i2b2 and LLMs: Transforming Cohort Discovery? Computational Phenotypes - Federated Learning Networks Panel- MassCPR UI Working group/Committee on Technology Updates Machine Learning in i2b2 to address data quality issues: Loyalty Cohorts/Computational Phenotypes, CIPHER demo	Associate Professor of Medicine and Biomedical Informatics in the Department of Medicine, Beth Israel Deaconess Medical Center (BIDMC), and the Department of Biomedical Informatics, Harvard Medical School (HMS). He is also the Director of the Biomedical Research Informatics Core (BRIC) at BIDMC.. Dr Weber was the original author of the i2b2 WebClient.
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10	Nathan Palmer	HMS	nathan_palmer@hms.harvard.edu	Panelist, The Future of i2b2 and LLMs: Transforming Cohort Discovery?	Nathan Palmer, PhD. Director, Core for Computational Biomedicine Nathan Palmer received a PhD in computer science from the Massachusetts Institute of Technology, studying machine learning, protein folding, and functional genomics. He then held a postdoctoral research position in the lab of Isaac Kohane at Harvard Medical School, during which his research interests expanded to include large-scale genomics, epidemiology, and medical informatics. He then went on to direct the Healthcare Data Science Program in the Department of Biomedical Informatics at Harvard Medical School. In his current role as Director of the Core for Computational Biomedicine, Dr. Palmer is part of a team of leading-edge technologists who evaluate and deploy modern data analytic processing and storage platforms to meet the needs of emergent research programs, with the goal of improving research reproducibility, scale, and efficiency. This team provides access to data resources comprising tens of billions of medical facts from tens of millions of patients to the research community at HMS, and develops both the technical and methodological solutions to perform novel analytics at scale. Dr. Palmer continues to work in the area of functional genomics and epidemiology through collaborations with the various Harvard teaching hospitals.
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12	Samuel Aronson, ALM, MA.	MGB	saronson@mgb.org	Panelist, The Future of i2b2 and LLMs: Transforming Cohort Discovery?	Samuel "Sandy" Aronson is the Executive Director of IT and AI Solutions for Mass General Brigham Personalized Medicine and the Senior Director of IT for our Accelerator for Clinical Transformation. His teams develop and deploy technology to improve clinical processes in clinical genetics, remote health and decentralized clinical trials. In clinical genetics, the team has built infrastructure that supports the evolution and practice of genetic based personalized medicine in both patient facing and laboratory settings. This system ecosystem enables a continuous learning process that harnesses clinical testing flows to advance knowledge surrounding genetic variation. The infrastructure includes the GeneInsight Suite of applications that were registered as a medical device and distributed. The team is now working to deepen support for whole genome sequence management and interpretation. This includes developing and validating Generative AI functionality to support variant assessment. The team has also deployed a platform that enables remote patient management by task shifted workforces using omnichannel communication. These capabilities have been used to equitably manage large patient populations. The platform is also currently supporting multiple decentralized clinical trials. We are now enhancing these capabilities using Generative AI focused on improving trial quality and cost effectiveness. Prior to this position, Mr. Aronson was an IT consultant to the biotechnology industry working for Tribiosys. Mr. Aronson also held several positions with Sapient Corporation, was a Strategic Consultant for Monitor Company and founded both LearningAction, a web-based training company now part of Best Software and Stanford Data Solutions, a software consulting firm. Mr. Aronson holds a Masters in Organizational Behavior and a Bachelors in Computer Science from Stanford University. He also holds a Masters focused in Biology from Harvard Extension School.
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14	Tianxi Cai	Harvard T.H. Chan School of Public Health	tcai@hsph.harvard.edu	Computational Phenotypes - Federated Learning	Tianxi Cai is a major player in developing analytical tools for mining EHR data and predictive modeling with biomedical data. She provides statistical leadership on several large-scale projects, including the NIH-funded Undiagnosed Diseases Network at DBMI. Cai's research lab develops novel statistical and machine learning methods for several areas including clinical trials, real world evidence, and personalized medicine using genomic and phenomic data. Cai received her ScD in Biostatistics at Harvard and was an assistant professor at the University of Washington before returning to Harvard as a faculty member in 2002.
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16	Shyam Visweswaran	University of Pittsburgh	shv3@pitt.edu	Networks Panel - ENACT - Enclaves Use Cases	Dr. Visweswaran trained as a physician in India, completed a residency in neurology at the Boston University Medical Center, and obtained a PhD in Intelligent Systems in 2007 at the University of Pittsburgh. Upon graduation, he joined the faculty at the University of Pittsburgh’s newly formed Department of Biomedical Informatics, where he contributed to the development of the graduate curriculum for informatics students. Dr. Visweswaran’s research focuses on application of machine learning to biomedicine with a specific focus on developing machine learning-based clinical decision support, precision medicine and personalized modeling, data mining and causal discovery from biomedical data, and research data warehousing. He initiated a NLM-funded research program on developing a learning electronic medical records (EMR) system that uses machine learning to provide decision support using the right data, at the right time. In the Department of Biomedical Informatics, I serve as the Director of the Machine Learning in Medicine Center (MLMC) and as the Director of the Center of Clinical Research Informatics (CCRI). He serves as the Director of the Biomedical Informatics Core for the University of Pittsburgh Clinical and Translational Science Institute, as a PD/PI for the All of Us Pennsylvania research project, as the Data Harmonization lead for the Accrual of patients to Clinical Trials (ACT) network, and directs the development of an EMR data warehouse called Neptune.
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18	Jeff Klann	MGB	jklann@partners.org	Panelist, Debate - Federated vs Centralized Networks: Optimizing Medical Data for Research: Centralized, Federated, and Hybrid Approaches Enabling Data Science workflows supported by new features in i2b2 1.8.2: Data Export Demonstration Machine Learning in i2b2 to address data quality issues: Loyalty Cohorts/Computational Phenotypes, CIPHER demo	Dr. Klann has worked with i2b2 for ten years, developing a research agenda that uses i2b2 as a substrate for data analytics, multi-site research networks, software architecture, data standards, and interoperability. His recent appointment as the Director of i2b2 Core Platform Development will allow him to apply his personal experience in large-scale i2b2 projects to improve the core product. In this position, he hopes to engage the vibrant user community, increase the openness and visibility of the software, and to continue to make the core platform relevant to evolving users’ needs. Dr. Klann is an Assistant Professor of Medicine at Harvard Medical School and in the Massachusetts General Hospital Laboratory of Computer Science. He holds a BS and MEng in Computer Science from MIT and a PhD from Indiana University in Health Informatics. He completed an NLM Research Training Fellowship concurrently with his PhD.
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20	Kavishwar Wagholikar, PhD	MGB	KWAGHOLIKAR@mgh.harvard.edu	Enabling Data Science workflows supported by new features in i2b2 1.8.2: Docker Containers	Kavishwar Wagholikar, MD, PhD, is Assistant Professor of Medicine at Harvard Medical School. His research is focussed on knowledge representation and information extraction for phenotyping applications, which includes clinical decision support (CDS), and quality analysis. Dr. Wagholikar completed clinical training (MBBS) and PhD in Scientific Computing from India, and was post-doctoral fellow at Mayo Clinic (2011-14). Dr. Wagholikar is recipient of K99/R00 career development award from NLM (2014-19). The objective of his research is to develop a framework for natural language processing (NLP) enabled CDS. The framework consists of methodologies and tools that will facilitate rapid development of apps for secondary use. Dr. Wagholikar’s research is in close collaboration with clinical practice.
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22	Michele Morris	University of Pittsburgh	mim18@pitt.edu	Ontology Working Group Update	Michele Morris is a highly skilled professional specializing in ontology development for the ENACT network. With a strong background in data management and clinical research, she has made significant contributions to the field through her expertise in creating and maintaining complex ontologies . Michele's work ensures the seamless integration and utilization of health data across multiple institutions, enhancing the quality and efficiency of clinical research . Her dedication to advancing healthcare through innovative data solutions makes her a valuable asset to the ENACT network and the broader medical research community.
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24	Abu Mosa	Vice Chair for Clinical Research Informatics Associate Professor, Department of Biomedical Informatics and Data Science Heersink School of Medicine \| The University of Alabama at Birmingham		Ontology to support additional data domains in i2b2. Panelist, Debate: Federated vs Centralized Networks: Optimizing Medical Data for Research: Centralized, Federated, and Hybrid Approaches	Abu Mosa, PhD - Dr. Mosa, a visionary in the domain of biomedical informatics, is at the forefront of integrating data-driven artificial intelligence with groundbreaking healthcare innovations. With over a decade of experience, he has pioneered efforts in advancing the use of real-world observational data and enhancing informatics infrastructure for research at a national scale. His expertise is backed by a BS and MS in Computer Science and a PhD in Biomedical Informatics. As the Senior Director and an Associate Professor of Biomedical Informatics, Dr. Mosa bridges his expertise across computational and health sciences. Recognized for his contributions, he was inducted as a Fellow of the American Medical Informatics Association. A principal investigator on numerous research grants, Dr. Mosa also leads MU's involvement in national healthcare data projects. Outside academia, he enjoys gardening, travel, and sports, reflecting his diverse passions and dynamic approach to life and work.
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26	Thomas H. McCoy, MD	MGH, HMS	tmccoy@mgh.harvard.edu	Panelist, Debate: Federated vs Centralized Networks: Optimizing Medical Data for Research: Centralized, Federated, and Hybrid Approaches	Dr. Thomas H. McCoy Jr., MD, is a distinguished psychiatrist and researcher specializing in big data, data security, and electronic health records. He serves as the Director of Research at the Center for Quantitative Health at Massachusetts General Hospital and is an Associate Professor of Psychiatry at Harvard Medical School . Dr. McCoy's work focuses on developing strategies for precision medicine and quantitative health, aiming to improve patient outcomes through innovative data-driven approaches . His contributions to the field are marked by his dedication to advancing healthcare through the integration of clinical and biological measures.
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28	Jackie Honerlaw, RN, BSN, MPH	US Dept. of Veteran's Affairs	Jackueline.honerlaw@va.gov	Machine Learning in i2b2 to address data quality issues: Loyalty Cohorts/Computational Phenotypes, CIPHER demo	Jacqueline Honerlaw, RN, BSN, MPH, is a seasoned project and team manager with extensive experience in epidemiology and clinical care. She has a robust background in electronic medical records research and has been serving as a General Health Scientist at the Veterans Health Administration since 2014. Jacqueline's work focuses on optimizing Veterans' health data, driving collaborative research, and improving clinical operations. She also serves as the Deputy Director of the Centralized Interactive Phenomics Resource (CIPHER), where she contributes to advancing health data innovation . Her dedication to advancing healthcare through innovative solutions and her leadership in managing complex projects make her a valuable asset to the field.
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30	Hossein Estiri, PhD	MGH	hestiri@mgh.harvard.edu	Curating precision PASC Research Cohort for clinical studies on Long Covid	Assistant professor of medicine at Harvard Medical School, and a member of the research staff at the MGH Laboratory of Computer Science. He is a computational demographer, data scientist, and clinical research informaticist who applies a variety of data science methodologies—including geo-spatial and statistical learning techniques—to develop computational models that explain complex demographic, ecological, and health outcomes. His current work focuses on architecting visual analytics applications to explore data quality in electronic health records data and characterize patients using statistical learning techniques and data science methodologies.
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32	Jonas Hügel, PhD	University Medical Center Göttingen	jonas.huegel@med.uni-goettingen.de	Curating precision PASC Research Cohort for clinical studies on Long Covid	Dr. Jonas Hügel is a Postdoc at the Department of Medical Informatics, University Medical Center Göttingen and a member of the Campus Institute Data Science at the Georg-August-University Göttingen. His work focuses on using ML for temporal phenotyping in complex diseases, such as cancer, Alzheimer’s Disease, and Post-COVID-19. Furthermore, he has worked on multiple research projects integrating clinical and genomic health data. Dr. Hügel holds a B. Sc. In Applied Computer Science with a focus on Medical Informatics and a M.Sc. in Computer Science with a specialization on applied Systems System Engineering. He wrote his Master’s Thesis in cooperation with the Max-Planck-Institute for Biophysical Chemistry. Afterward, he obtained his doctorate in computer science from the Georg-August-University in Göttingen. During his doctoral studies, he was a visiting researcher at the Clinical Augmented Intelligence Group at Massachusetts General Hospital in Boston.
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34	Diane Keogh	Executive Director i2b2	diane.keogh@transmartfoundation.org		Diane was the Executive Director of the i2b2 Foundation prior to being named the Executive Director of the combine i2b2 tranSMART Foundation. Diane has extensive Healthcare IT experience including academic medical centers, community and specialty hospitals, provider networks, industry, and biomedical research with a major focus on developing scalable enterprise strategies and solutions.
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