Overview

(Coming Soon!)

Speakers

Dr. Junshui Ma, Associate VP, Head of Biometrics Research, BARDS, MRL, at Merck and Co., Inc.

Dr. James Zou, Associate professor of Biomedical Data Science and, by courtesy, CS and EE at Stanford University

Dr. Bin Zhu (NIH/NCI) 

Moderator

Dr. Richard Baumgartner, Senior Director, Biometrics Research Department, Biostatistics and Research Decision Sciences (BARDS) at Merck and Co., Inc.

Abstracts 

Talk Title TBA - Dr. Junshui Ma, Associate VP, Head of Biometrics Research, BARDS, MRL, at Merck and Co., Inc.

Abstract: (Coming Soon!)

Talk Title TBA - Dr. James Zou, Associate professor of Biomedical Data Science and, by courtesy, CS and EE at Stanford University

Abstract: (Coming Soon!)

Talk Title TBA - Dr. Bin Zhu (NIH/NCI) 

Abstract: (Coming Soon!)

About the speakers

Dr. James Zou is an associate professor of Biomedical Data Science and, by courtesy, CS and EE at Stanford University. He is also the faculty director of Stanford AI4Health. He works on both improving the foundations of ML–-by making models more trustworthy and reliable–-as well as in-depth scientific and clinical applications. Many of his innovations are widely used in tech and biotech industries. He has received a Sloan Fellowship, an NSF CAREER Award, two Chan-Zuckerberg Investigator Awards, a Top Ten Clinical Achievement Award, several best paper awards, and faculty awards from Google, Amazon, Tencent and Adobe. His research has also been profiled in popular press including the NY Times, WSJ, Washington Post and WIRED. See Profile 

Dr. Junshui Ma is currently Associate VP, Head of Biometrics Research, BARDS, MRL, at Merck. He obtained his Ph.D. from Ohio State University in 2001. He worked in Los Alamos National Lab, Aureon Bioscience and Ohio Supercomputer Center, before he joined Merck in January 2005. In the past 16 years of working at Merck, he engaged in all phases of drug Research & Development (R&D), including preclinical discovery, clinical development, regulatory filing, and translational medicine. His research interests include machine learning in pharmaceutical R&D, stratified medicine, and survival analysis. He coauthored 30 peer-reviewed journal papers, along with many conference abstracts and posters. See Profile

Dr. Bin Zhu received a Ph.D. in biostatistics from the University of Michigan, Ann Arbor, in 2010 and then spent two years as a postdoctoral associate at the Department of Statistical Science and the Center for Human Genetics at Duke University, North Carolina. He joined DCEG as a tenure-track investigator in the Biostatistics Branch in 2012 and was awarded NIH scientific tenure and promoted to senior investigator in 2023. At DCEG, Dr. Zhu has developed novel statistical methods and computational packages to address scientifically important and statistically challenging research problems. In addition, he has led statistical analyses for multiple DCEG cancer genomic studies, as well as several national and international cancer genomic consortia. Research Interests: Dr. Zhu integrates statistics and genomics to understand the etiology of mutational signatures and reveal tumor heterogeneity. He develops statistical methods/tools and leads the scientific investigations to: (a) Extract mutational signatures and characterize their etiologies across different study designs and platforms, and (b) Uncover inter- and intra-tumor heterogeneity with translational and clinical implications. See Profile

About the Moderator

Dr. Richard Baumgartner is a Senior Director with the Biometrics Research Department, Biostatistics and Research Decision Sciences (BARDS) at Merck and Co., Inc. in Rahway, NJ. During his time at Merck, he has supported early clinical and preclinical studies with imaging components, including functional Magnetic Resonance Imaging (fMRI), dynamic contrast-enhanced MRI (DCE-MRI), and Positron Emission Tomography (PET) imaging, in the fields of neuroscience, inflammation, and cardiovascular therapeutics. He is currently involved also in several projects in the field of Artificial Intelligence and Machine Learning (AIML). Previously, he held the position of Associate Research Officer at the Institute for Biodiagnostics, National Research Council Canada in Winnipeg, Canada, where he worked on the development of methods for exploratory analysis of fMRI. At the Institute for Biodiagnostics, he also worked on metabolomic applications to develop diagnostic biomarkers for the prediction of pathogenic fungi and breast cancer. Richard holds a PhD in Electrical Engineering from the University of Technology Vienna, Austria. See Profile

About the NISS/Merck Meet-up Series

The NISS/Merck Meet-Up Series is an ongoing collaborative forum designed to bring together biostatisticians, statisticians, epidemiologists, and data scientists working in or alongside the pharmaceutical industry. Since 2017, the series has provided a dynamic space for experts to explore emerging methodological challenges, share innovative research, and discuss real-world applications that shape drug development and healthcare decision-making.

Each meet-up focuses on a timely topic at the intersection of statistics, data science, and pharmaceutical practice—ranging from foundational issues in clinical trials to cutting-edge advances in AI and machine learning. The series has a long history of spotlighting both established and emerging ideas, encouraging open dialogue among industry leaders, academic researchers, and government scientists.