Overview

(Coming Soon)

Speakers

Dean Li, Senior Director, Nonclinical Statistics, Pfizer

Thomas Jemielita, Merck

Wiebke Dammann/Jorg Rahnenfuhrer, TU Dortmund.

Moderator

Richard Baumgartner, Merck

About the Speakers

(Coming Soon)

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.