Dr. Ming-Hui Chen is Board of Trustees Distinguished Professor and Head of the Department of Statistics at the University of Connecticut (UConn). He was elected to Fellow of International Society for Bayesian Analysis in 2016, Fellow of the Institute of Mathematical Statistics in 2007, Fellow of American Statistical Association in 2005. He also received the University of Connecticut AAUP Research Excellence Award in 2013, the UConn College of Liberal Arts and Sciences (CLAS) Excellence in Research Award in the Physical Sciences Division in 2013, the University of Connecticut Alumni Association's University Award for Faculty Excellence in Research and Creativity (Sciences) in 2014, and ICSA Distinguished Achievement Award in 2020. He has published over 428 statistics and biostatistics methodological and medical research papers in mainstream statistics, biostatistics, and medical journals. He has also published five books including two advanced graduate-level books on Bayesian survival analysis and Monte Carlo methods in Bayesian computation. He has supervised or been supervising 37 PhD students. He served as President of the International Chinese Statistical Association (ICSA) in 2013, Program Chair and Publication Officer of SBSS of the American Statistical Association (ASA) and the ASA Committee on Nomination for 2016-2017 to nominate candidates for ASA President/Vice President. Currently, he serves as the 2022 JSM Program Chair, Past President of the New England Statistical Society (nestat.org), Co Editor-in-Chief of Statistics and Its Interface, inaugurated Co Editor-in-Chief of New England Journal of Statistics in Data Science, and an Associate Editor of JASA, JCGS, and LIDA.
Dr. Ouhong Wang is currently Chief Development Officer at Angitia Biopharmaceuticals. He took on this expanded drug developer role in the summer of 2021 after close to 27 years as a pharmaceutical statistician with various companies including Lilly, Amgen, Boehringer Ingelheim, and most recently as VP, Head of Biostatistics at Vertex. Ouhong received his PhD in statistics from Iowa State University.
Jeff Palmer has been a statistics group head leading early clinical development in rare diseases at Pfizer for the past 5 years. Prior to Pfizer he had worked for over ten years with various other pharma and consulting companies supporting mainly rare diseases, oncology, and neurology. Jeff received his MS in statistics from the University of Chicago and conducted his doctoral research in statistics at Carnegie Mellon University.
Dr. Kun Chen is an Associate Professor in the Department of Statistics, University of Connecticut (UConn), and a Research Fellow at the Center for Population Health, UConn Health Center. Chen’s research mainly focuses on multivariate statistical learning, dimension reduction, high-dimensional statistics, and healthcare analytics with large-scale heterogeneous data. He has extensive interdisciplinary research experience in a variety of fields including insurance, ecology, biology, agriculture, medical imaging, and public health. Chen's research projects have received funding from the National Institutes of Health (NIH), the Simons Foundation, and the National Science Foundation (NSF). Recently Chen is funded by NSF for developing integrative multivariate methods and heterogeneous response regression, and he is a co-PI in an NIH-funded data-driven suicide prevention study which leverages integrated big data from disparate sources scattered in healthcare system. Chen was a Co-Editor of the 2015 ICSA Symposium Proceeding Book, and serves as an Associate Editor of Sankhya: The Indian Journal of Statistics since 2016. He has received Recognition for Teaching Excellence at UConn for multiple times.
Chen received his B.Econ. in Finance and Dual B.S. in Computer Science & Technology from the University of Science and Technology of China in 2003, his M.S. in Statistics from the University of Alaska Fairbanks in 2007, and his PhD in Statistics from the University of Iowa in 2011. Before joining UConn, he was on the faculty of Kansas State University from 2011 to 2013.
Andy Chi currently serves as Executive director of Statistics and Quantitative Sciences (SQS), Data Sciences Institute (DSI) at Takeda. He is a member of DSI Leadership team (LT) and SQS management team (MT), supporting development and commercialization of Takeda Oncology Portfolio. He has 18 years of drug development experience, and has been strong advocate for innovative trial design and quantitative decision making using diverse trial types and data sources in clinical trials, from Academia and RWD/RWE. Andy received his MS in biometry from University of Texas, Houston, and PhD in Medical Science from University of South Florida.
Ran Duan is the Sr. Director, Global Head of Biometrics at Angitia Biopharmaceuticals. Before joining Angitia, Ran worked at Alexion, AstraZeneca Rare Disease and Eli Lilly and Company, where she led multiple ophthalmology and diabetes pipelines. She is also an active member of the AGA pediatric working group. Her research interests include the innovative trial design for pediatric rare disease, RWE generation and digital solutions for health care. Ran obtained her Ph.D. in statistics from the University of Missouri-Columbia.
Dr. Jianan Hui is a Sr. Principal Biostatistician in Global Biostatistics at Servier Pharmaceuticals. She currently leads the global submission activities in hematology. Prior to her role at Servier, she was a Senior Biostatistician at Boehringer Ingelheim Pharmaceuticals. She has worked on various projects in immunology, oncology, cardiovascular and metabolism. Her research interests includes Bayesian statistics, adaptive design, statistical go/no-go decision making and statistical learning. Jianan received her Ph.D. in Applied Statistics at University of California, Riverside with research focuses in Markov chain Monte Carlo and spatiotemporal Bayesian Hierarchical modeling. Prior to that, she received two B.S. degrees in Mathematics from University of Texas at Arlington and in Information and Computational Science from University of Science and Technology Beijing.
Dr. Yang Song is currently Senior Director, Biostatistics Therapeutic Area Head for General Medicines (including gene therapies), Pain and Neurology, at Vertex Pharmaceuticals Inc., leading his statistical team on multiple rare disease pipeline development projects. Prior to joining Vertex, he was with Merck for nearly 10 years, rotated through its PA, Beijing, and NJ global sites, with increasing responsibilities for global drug development across multiple therapeutic areas. He also worked with Johnson & Johnson for oncology drug development early in his career. His research interests include rare disease clinical trial methodology, real world evidence, data integration, optimal clinical development strategy, statistical issues in oncology clinical trials, biomarker endpoints, and subgroup analyses. He is a member of the ASA Biopharmaceutical Scientific Working Group on Real World Evidence. Yang received his Ph.D. in Statistics from the University of Wisconsin - Madison.
Dr. Rui (Sammi) Tang is a leading expert of biostatistics/bioinformatics in the biotech/pharmaceutical industry and she is currently the Head of Biostatistics, Programming and Medical Writing Department at Servier Pharmaceuticals US. Prior to join Servier she was the Biostatistics Therapeutic Area head of Oncology, Transplants, Ophthalmology and prematurity neonates programs at Shire pharmaceutical. Prior to that she was at Vertex pharmaceutical leading Oncology and Hematology pipelines. Before that she also has worked at Amgen for about 8 years, Mayo clinical biostatistics and Merck shortly. Previously she served as the biostatistics lead of Companion Diagnostics and the Global Statistics Lead for multiple oncology clinical programs from early phase to late phase at Amgen. Sammi has great experience in CDRH, CBER, CDER, health Canada, EMA and Asian regulatory agencies interactions. Sammi’s research interests are primarily in the area of adaptive clinical trial design and biomarker subgroup related statistical issues in precision medicine. She has authored more than 30 articles in peer-reviewed scientific journals on methodology, study design, data analysis and reporting and is a co-inventor of several patents. Besides her daily work, she actively promotes data science through many of her volunteer activities: Sammi is co-founder of DahShu which is a 501(c)(3) non-profit organization, founded to promote research and education in data sciences with almost 5000 members internationally. She serves in the SCT (Society of Clinical Trials) scientific program committee and development committee since 2013 to help organize the annual international conference. She is leading teams in the DIA (Drug Information Association) Adaptive design working group of oncology drug development and small population working group for rare disease statistical methodology development. She is also an active member in ASA (American Statistics Association) and ICSA (International Chinese Statistics Association) to serve the biostatistics and data science professional community.
Sammi graduated from the University of Michigan Technology University with a PhD in statistics Genetics.
Dr. Susan Wang is the Global Head of Biostatistics and Data Sciences in Inflammation at Boehringer Ingelheim Pharmaceuticals. She has many years of experience working on new drug development and registration as a statistician as well as in various leadership roles. She is passionate about implementing efficient statistical methods and statistical modeling in clinical new drug development, in rare diseases. Susan has a Ph.D. in statistics from Stony Brook University in New York.
Richard Zhang is the Statistics Group Lead for late phase clinical development in rare diseases at Pfizer. He has been in the pharmaceutical industry for over twenty years with exposure to hundreds of clinical trials spanning multiple therapeutical areas: Neuroscience, Pain, Rheumatology, Endocrine and IEM. He has extensive knowledge and experience in regulatory interactions and submissions. His research interests include innovative trial design, real world evidence, meta-analysis, data mining and modeling. Richard received his PhD in statistics from the University of Kentucky.