Keynote Speakers

Empower Statistical ML/AI with End-to-End Ecosystems

Xihong Lin

Friday, May 17th | 8:30 AM - 9:30 AM

Xihong Lin is Professor and former Chair of Biostatistics and Coordinating Director of the Program in Quantitative Genomics at Harvard School of Public Health and Professor of Statistics at Harvard University. Dr. Lin’s research interests lie in the development and application of statistical and machine learning methods for analysis of massive and complex genetic and genomic, biobank, epidemiological and health data. Dr. Lin was elected to the US National Academy of Medicine in 2018 and the US National Academy of Sciences in 2023. She received the 2002 Mortimer Spiegelman Award from the American Public Health Association, the 2006 Presidents’ Award and the 2017 FN David Award from the Committee of Presidents of Statistical Societies (COPSS), the 2022 Jerome Sacks Award for Outstanding Cross-Disciplinary Research from the National Institute of Statistical Science. She is a recipient of the MERIT Award (2007-2015) and the Outstanding Investigator Award (2015-2029) from the National Cancer Institute. Dr. Lin is the former Chair of COPSS (2010-2012). She is the former Coordinating Editor of Biometrics and the founding co-editor of Statistics in Biosciences. She has served on a large number of committees of many statistical societies, numerous NIH and NSF review panels, and several US National Academies committees.

Integrated Computation and Genomics for Cancer Target and Drug Discovery

Shirley Liu

Saturday, May 18th | 8:15 AM - 9:15 AM

Dr. X. Shirley Liu is the co-founder and CEO of GV20 Therapeutics, a clinical stage biopharmaceutical company with pioneering technologies in novel target identification and antibody drug discovery in Oncology. Dr. Liu received PhD in Biomedical Informatics and PhD minor in Computer Science from Stanford University in 2002. She has been a Professor of Biostatistics and Computational Biology at the Department of Data Science at Dana-Farber Cancer Institute (DFCI) and Harvard University, until she joined GV20 full-time in 2022. Her research work focused on algorithm development and data integration modeling for translational cancer research. She has published over 270 papers and has an H-index of 120. Dr. Liu is a fellow of the International Society of Computational Biology (ISCB), American Institute for Medical and Biological Engineering (AIMBE) and was a Breast Cancer Research Foundation Investigator (2017-2021). She is a recipient of the Sloan Research Fellowship (2008), Weitzman Outstanding Early Career Investigator Award from the Endocrine Society (2016), ISCB Innovator Award (2020), and the Benjamin Franklin Award for Open Access in the Life Sciences (2020). Her lab has mentored 27 Ph.D. and postdoctoral trainees to independent academic careers.

The Data Struggle of the Unseen

Bhramar Mukherjee

Saturday, May 18th | 1:00 PM - 2:00 PM  

Bhramar Mukherjee is John D. Kalbfleisch Distinguished University Professor of Biostatistics; Siobán D. Harlow Collegiate Professor of Public Health; Chair of the Department of Biostatistics; Professor, Department of Epidemiology; Professor, Global Public Health, University of Michigan (UM) School of Public Health; and Faculty Affiliate, Michigan Institute of Data Science (MIDAS), University of Michigan. She also serves as the Associate Director for Quantitative Data Sciences, University of Michigan Rogel Cancer Center. She has been engaged with the U-M Precision Health, an institution-wide presidential initiative for the last decade in various roles. As of 2023, she holds the position of Assistant Vice President for Research for Research Data Services Strategy. Her research interests include statistical methods for analysis of electronic health records, studies of gene-environment interaction, Bayesian methods, shrinkage estimation, analysis of multiple pollutants. Collaborative areas are mainly in cancer, cardiovascular diseases, reproductive health, exposure science and environmental epidemiology. She has co-authored more than 370 publications in statistics, biostatistics, medicine and public health and is serving as PI on NSF and NIH funded methodology grants. She is the founding director of the University of Michigan’s summer institute on Big Data. Bhramar is a fellow of the American Statistical Association and the American Association for the Advancement of Science.  Bhramar was inducted into the National Academy of Medicine in 2023. She is the recipient of many awards for her scholarship, service and teaching at the University of Michigan and beyond including the Janet Norwood award, the Sarah Goddard Power award, the Karl E Peace Award for statistical contribution towards betterment of society awarded by The American Statistical Association, and the Sacks Award from National Institute of Statistical Sciences. Bhramar and her team took an active role in modeling the SARS-CoV-2 virus trajectory in India during the COVID-19 pandemic, which has been covered by major media outlets like Reuters, BBC, NPR, NYT, WSJ, Der Spiegel, Australian National Radio and the Times of India.

Data, Data Innovation, & Hunt for Explainability 

Jiayang Sun

Friday, May 17th |  1:00 PM - 2:00 PM

Jiayang Sun is Professor and Chair of Statistics, and Bernard Dunn Eminent Scholar at GMU. Her statistical expertise has included simultaneous inference and multiple testing, selection bias and measurement errors, mixtures, and causal inference, semiparametric and non-parametric problems, ML and big data, statistical data science, and computing. Sun’s experience also extends to EHR, biostatistics, and epidemiology. Her current work involves high-impact collaborative projects and the development of novel statistical approaches for analyzing large and complex datasets. She has over 30 years of funded research by NSF, NIH, NSA, DoD, DoE, VA, ASA, and others. She has made fundamental contributions to statistical methodology, theory, and computing, with interdisciplinary work in biomedical science, computer science, and more.  She is an elected fellow of IMS, ASA, and the elected member of ISI. 

Before joining Mason in 2019, Sun was  Professor of Statistics, then Professor of Biostatistics, and the Director of the Center for Statistical Research, Computing and Collaboration, at Case Western Reserve University. She brings experience in running a center and is familiar with the culture of both Statistics and Biostatistics Departments, as well as teamwork for large institute grants, such as those funded by NIH’s CTSA and NSF’s ADVANCE programs. She also served as the inaugural ASA/ACM/AMS/IMS/MAA/SIAM Science & Technology Policy Fellow (STPF), working as the Big Data Senior Fellow for Big Data Analytics in the leadership team for Partnership for Data Innovations  at the USDA ARS, Office of National Programs between 9/2019-8/2020.

In her leadership role, she served as the 2016 President of the Caucus for Women in Statistics (CWS), now the Caucus for Women in Statistics and Data Science. During her tenure, she led the establishment of its digital infrastructure, cwstat.org and updated  its Constitution and By-Laws. These changes facilitated modern financial and administrative operations, increased participation, across generational, racial, and international boundaries, and set a basis for future development. Since her chairing Mason's Department of Statistics, the department has grown its research and Ph.D. program, and improved its national ranking. For programs, she organized or co-organized national and international conferences, including the International Research Workshop on Developments and Challenges in Mixture Mode, Bump Hunting and Measurement Error Models in 2002, A Conference on Nonparametric Inference and Probability with Applications to Science in 2005, Conference in Genetics, Probability and Statistics at Stanford in 2011, and served as the IMS Program Chair for the IMS/ENAR 2002 meeting.