Prof. Jake Y. Chen is the Triton Endowed Professor of Biomedical Informatics and Data Science at the University of Alabama at Birmingham School of Medicine, with joint appointments in Genetics, Computer Science, and Biomedical Engineering. As founding director of UAB’s Systems Pharmacology AI Research Center (SPARC), he has spent over 25 years pioneering AI-driven approaches to computational drug discovery, from network‐based pharmacology models and multi-omics integration frameworks to patient-specific digital twin simulations. His work—drawing on clinical records, genomic assays, and real-world evidence—has led to more than 200 peer-reviewed publications and has directly informed translational studies in precision medicine.

Dr. Chen also serves as Contact MPI for the NIH U54-funded CONNECT consortium (2024–2029), where he leads a multi-institutional effort to build AI-ready biomedical knowledge networks from over $1 billion in NIH-supported data. A trusted advisor to NIH, NSF, FDA, and the U.S. Congress, he has helped shape national and global regulatory frameworks for AI in healthcare. His contributions have earned him fellowships with ACMI, AIMBE, AMIA, and ACM, recognition among the “Top 100 AI Leaders in Drug Discovery & Healthcare,” and the CAST-USA Pioneer Award. As founder of Medeolinx, LLC, he commercialized the GeneTerrain AI platform for pharmaceutical target identification and continues to guide industry and government on integrating AI into drug discovery pipelines.

Dr. Bo Huang is Executive Director, Statistics Group Head of Non-malignant Hematology at Pfizer. He has more than 17 years of industry experience across all stages of clinical development in oncology and rare diseases, and successfully led a number of global submissions, including the first Pfizer submission in the FDA’s Real-Time Oncology Review pilot program. He is a recognized scientific leader in developing and applying innovative quantitative methods in drug development, with over 100 scientific publications in medical and statistical journals. In addition, he has been serving as Guest Editor/Associate Editor for several scientific journals, serving as Industry Co-Chair of the 2021 Regulatory-Industry Statistics Workshop, and was the elected 2024 Program Chair for the ASA Biopharmaceutical Section. He was also an elected Board Director of the International Chinese Statistical Association (2016-2019). Bo received his PhD in Statistics from the University of Wisconsin-Madison, and is an elected Fellow of the American Statistical Association (2023).

Dr. Kun Huang received his BS degrees in Biological Science and Computer Science from Tsinghua University in 1996 and his MS degrees in Physiology, Electrical Engineering, and Mathematics all from University of Illinois at Urbana-Champaign (UIUC). He then received his PhD in Electrical and Computer Engineering from UIUC in 2004 with a focus on computer vision and machine learning. He was a faculty member in the Department of Biomedical Informatics at The Ohio State University (OSU) from 2004 to 2017 where he served as the Associate Dean for Genome Informatics in the College of Medicine. He joined Indiana University School of Medicine as Director for Data Science and Informatics of the Precision Health Initiative in 2017. Currently he is the IUSM PHI Endowed Chair for Genomic Data Science, Professor and Chair of the Department of Biostatistics and Health Data Science at Indiana University School of Medicine and Fairbanks School of Public Health. He is also the Associate Director for Data Science of the IU Simon Comprehensive Cancer Center and a member of the Regenstrief Institute. His research interests include bioimage informatics, computational pathology, translational bioinformatics, and heath data science. He is an elected Fellow of American Institute of Medical and Biological Engineering (AIMBE) and published more than 250 research papers.

Dr. Zhongwu Lai is currently an executive director at AstraZeneca, leading a team of data scientists to advance AstraZeneca’s oncology portfolio through advanced data analysis. He has more than 25 years of industry experience in biopharma, and has made significant contributions to the field of bioinformatics, genomics, NGS, and translational science in cancer research. He has authored and co-authored over 50 scientific publications, with over 40k citations. One of his achievements is the development of VarDict, a versatile and novel variant caller designed for both DNA and RNA sequencing data. VarDict is widely recognized for its ability to simultaneously detect single nucleotide variants (SNVs), multi-nucleotide variants (MNVs), insertions and deletions (InDels), and complex variants, making it a critical tool in next-generation sequencing for cancer research. In his early industry career, he also participated in the Human Genome Project, and was one of the authors of the landmark Science publication on the human genome sequence in 2001. Dr. Lai is an expert in cancer genomes across multiple cancer types, including lung, breast, gastric, prostate and pancreatic cancers. His >10 year experience in development of olaparib, a PARP inhibitor, has made him a renowned scholar in BRCA mutation detection and interpretation. He has contributed significantly to the development of olaparib, osimertinib, durvalumab, tremelimumab, and T-DXd.

Qunhua Li is a professor in Dept of Statistics and Huck Institute of life sciences at Penn State University. She received her PhD from University of Washington and had her postdoc trading in University of California at Berkeley before joining Penn State University.

Hana Lee, PhD, is a Senior Statistical Reviewer in the Office of Biostatistics (OB) at the Center for Drug Evaluation and Research (CDER), FDA. She leads and oversees various FDA-funded projects that support the development of the agency’s real-world evidence (RWE) program. She also serves as a co-lead of the RWE Scientific Working Group of the American Statistical Association (ASA) Biopharmaceutical Section, FDA public-private partnership involving scientists from the FDA, academia, and industry to advance the understanding of real-world data (RWD) and RWE to support regulatory decision-making. In 2024, she received the FDA’s most prestigious award for excellence in advancing and promoting statistical innovation in the use of RWD/RWE for regulatory decision-making.

Zhengqing Ouyang is an Associate Professor of Biostatistics in the Department of Biostatistics and Epidemiology of the School of Public Health and Health Sciences at the University of Massachusetts Amherst. Dr. Ouyang obtained his PhD degree from Stanford University under the guidance of Prof. Wing Hung Wong followed by a postdoctoral training jointly mentored by Prof. Howard Chang and Prof. Michael Snyder at Stanford University School of Medicine. Dr. Ouyang has received several awards, including the Genome Technology Young Investigators of the Year Award from GenomeWeb, the Research Starter Grant in Informatics Award from PhRMA Foundation, and the NIGMS Maximizing Investigators' Research Award. Dr. Ouyang’s research lies in the development and application of statistical methods for analyzing the spatial interactions and configurations of the genome towards understanding gene regulation and cellular activities.

Fei Wang is a tenured Professor of Health Informatics in Department of Population Health Sciences at Weill Cornell Medicine (WCM), where he also holds a secondary appointment as a Professor in Department of Emergency Medicine. Dr. Wang holds several administrative roles at WCM, including the Associate Dean for Data Science and AI, and Division Chief of Health Informatics at the Department of Population Health Sciences, as well as the Founding Director of the WCM Institute of AI for Digital Health (AIDH). Dr. Wang is also a Senior Faculty Fellow of Clinical AI at Cornell Tech, a Senior Technical Advisor at New York Presbyterian Hospital, and an Adjunct Scientist at Hospital for Special Surgery (HSS). His research interest is machine learning and artificial intelligence in biomedicine. Dr. Wang has published over 350 papers on the major venues of AI and biomedicine, which have received more than 37K citations to date. His H-index is 86. Dr. Wang is an elected fellow of American Medical Informatics Association (AMIA), American College of Medical Informatics (ACMI) and International Academy of Health Sciences and Informatics (IAHSI), and a distinguished member of Association for Computing Machinery (ACM).

Dr. Hong Yu is an elected Fellow of the American College of Medical Informatics. She is the founding Director of the Center for Biomedical and Health Research in Data Sciences and a tenured Professor in the Miner School of Computer & Information Science at the University of Massachusetts Lowell (UML). She also holds adjunct faculty appointments at the University of Massachusetts Amherst and the UMass Chan Medical School, where she was a tenured full professor prior to joining UML. In addition, Dr. Yu serves as a Research Health Scientist and Principal Investigator at the Center for Healthcare Organization & Implementation Research at the VA Bedford Healthcare System. She earned her Ph.D. in Biomedical Informatics from Columbia University. Dr. Yu holds multiple U.S. patents and has authored more than 250 peer-reviewed publications in the areas of natural language processing, informatics, and artificial intelligence, published in leading journals and conference proceedings in computer science and biomedical informatics. She has mentored over 50 trainees, many of whom have gone on to become faculty members or leaders in industry.

Xiang Zhang leads Medical Affairs and HTA Statistics at CSL, co-leading the Forum for Observational Research Excellence. He oversees a team of statisticians, epidemiologists, and RWE scientists to generate RWE throughout the drug life cycle, including clinical development, regulatory submissions, product launches, and commercialization. This team also provides statistical support for HTA submissions and other activities related to market access and the demonstration of value for CSL products. He has authored or co-authored over 40 peer-reviewed publications and a book. He is currently a member of both ASA RWE and HTA scientific working groups.

Dr. Yao Zheng is an Assistant Professor of Statistics at the University of Connecticut. She is a recipient of the NSF CAREER Award, the Makuch Faculty Fellowship, and the IMS New Researcher Travel Award. She is particularly interested in advancing methodologies that address the challenges posed by temporal dependence and dynamic structure in modern datasets. Dr. Zheng earned her BS and PhD from the Department of Statistics and Actuarial Science at the University of Hong Kong. Before joining UConn in 2019, she spent two years at Purdue University as a postdoctoral researcher and Visiting Assistant Professor.