Department of Statistics
Statistics in Pharmaceuticals 2024

Organizing Committee

Supporting Team

Ming-Hui Chen, University of Connecticut

Ming-Hui Chen 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, 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.

CG Wang, Regeneron

CG Wang Dr. CG Wang is the Head of Statistical Innovation in BDM. Previously, Dr. Wang was an Associate Professor at Johns Hopkins University. He also worked as a Mathematical Statistician at CDRH, FDA. Dr. Wang has extensive experience in clinical trial design and analysis, especially in regulatory settings, and in statistical software development.

Yulia Sidi, Merck

CG Wang Yulia Sidi is a Principal Scientist in Merck, where she supports various oncology trials across different stages of drug-development. Prior to joining Merck, Yulia worked in Takeda and Teva Pharmaceuticals. Yulia received her PhD in Statistics from University of Connecticut and is passionate about scientific collaborations that could improve patient lives.

Revathi Ananthakrishna, BMS

Revathi Ananthakrishnan Revathi Ananthakrishnan works as a Biostatistician at Bristol-Myers Squibb on designing, analyzing and interpreting immuno-oncology trials. She has a broad interdisciplinary background of Mathematics, Statistics, Physics and Biology. She did her PhD in Theoretical (Bio)Physics and her post-doc in Biomathematics. All her work in academia on modeling cell elasticity, cell movement and cell division had relevance to cancer. After her post-doc, she started working as a clinical trials Biostatistician in Industry, and did her PhD in Biostatistics while working in Industry. She is interested in various aspects of Oncology clinical trials and clinical trial methodology, especially in the design of early phase Oncology trials, and has published in this area. She has worked on several early phase Oncology trials as well as trials for regulatory submission for solid tumors and blood cancers.

Meizi Liu, Takeda

Revathi Ananthakrishnan Meizi Liu currently serves as a Statistics Manager at Takeda, where she is the study lead for several early-phase trials in oncology and cell therapy. Prior to her role at Takeda, Meizi earned her Ph.D. in biostatistics from the University of Chicago. With a strong foundation in statistical science, Meizi has co-authored various publications in peer-reviewed statistical journals, focusing on areas such as dose optimization, Bayesian dynamic borrowing, and Bayesian adaptive designs in clinical trials.

Charles Liu, Gilead Sciences

Revathi Ananthakrishnan Charles Liu is currently a Statistical Advisor in the Biostatistics Innovation Group at Gilead Sciences. Previously, he held positions at Alexion Pharmaceuticals, Cytel, and Boston University. His current research interests include model selection, dose response modeling, and portfolio decision making.

Glen Laird, Vertex

Glen Laird A practicing pharmaceutical industry statistician for over 20 years, Glen Laird is currently the head of Biostatistics Methodology and Innovation at Vertex Pharmaceuticals, having previously led the GMA Biostatistics group at Vertex. Prior to his 6 years at Vertex, Glen worked in oncology biostatistics at Novartis, BMS, and Sanofi, assuming roles with increasing responsibility across early and full development. Glen graduated with a PhD in Statistics from Florida State University and worked as a survey statistician for RTI International before joining the pharmaceutical industry.

Dacheng Liu, Boehringer Ingelheim

Liu Dacheng Dacheng Liu serves as the Highly Distinguished Therapeutic Area and Methodology Statistician at Boehringer Ingelheim with 18 years of experience in the pharmaceutical industry. In this role, he provides leadership in driving the statistical quality and fostering innovation of companywide clinical development programs. As the chair of the statistical strategy and review committee, he is instrumental in shaping the organization’s statistical practices. Dacheng represents Boehringer Ingelheim at industry-wide groups, such as PhRMA clinical development working group, and leads collaborations with partners in the US from both industry and academia. Prior to his current role, Dacheng served as the Global Head of Clinical Data Sciences, and the US Head of Statistics, leading both US and global teams in clinical drug developments of the entire pipeline of Boehringer Ingelheim. He has extensive experience leading early and late-phase projects in multiple disease areas, including landmark studies, regulatory submissions, and FDA advisory committee meetings. He played a key role in harmonizing SOP processes and standardizing statistical methodologies within Boehringer Ingelheim. Dacheng has over 40 publications in areas of clinical research, trial design, statistical methodologies, and machine learning.

Jeremy Hunter, Amgen

Jeremy Hunter As an employee of Amgen Inc. since 2015, Jeremy has spearheaded efforts related to trial randomization and blinding, including helping establish standard operating procedures and controlled documentation critical to trial integrity and minimizing operational bias. Jeremy’s contributions also include cross-functional training, on-going study team consultation and expertise related to restricted data access and sharing. In addition, Jeremy continues to oversee the randomization and blinding aspects of several concurrent large-scale interventional trials.
After receiving a Master of Arts from Columbia University (MA ’06), Jeremy spent five years as a statistician for the University of California, Los Angeles (UCLA) Integrated Substance Abuse Programs (ISAP), contributing his statistical skillset to diverse research topics including HIV/AIDS, substance abuse and prison recidivism.

Gaohong Dong, BeiGene

Gaohong Dong Gaohong Dong, PhD has 20 years of experience in the pharmaceutical industry. He is a Director of Biostatistics at BeiGene. Prior to joining BeiGene, he worked at Novartis, then worked as a consultant under his own entity of iStats Inc. Gaohong has been supporting drug development in multiple therapeutic areas including oncology, solid organ transplant, stem-cell transplant, and infection disease. He is a co-author of many highly cited medical papers. Gaohong has a great passion on statistical research. He published peer-reviewed statistical journal papers and book chapters on Bayesian-Frequentist design, adaptive design, missing data imputation, meta-analysis, and composite of prioritized multiple outcomes. During the recent years, he has been focusing on the win statistics (win ratio, win odds, and net benefit). His research of the stratified win ratio and the win odds have been applied to designs and analyses of clinical trials including phase III studies. Gaohong has been serving as an Associate Editor of the Journal of Biopharmaceutical Statistics since 2017.

Claude Petit, Astellas

Gaohong Dong After earning her PhD in Biostatistics related to Bayesian Analyses, Claude joined the Pharmaceutical Industry 25 years ago to bring her stone to clinical trials design and analysis. Lecturer at Yale School of Public Health for a decade and VP Statistical & Real Word Data Science at Astellas since 2021, she is leading a global team of talented Statisticians, Real World Data Scientists and Programmers.
Eternal learner, she has a passion for leadership, growth and teaching. In 2021, she became a certified Executive Coach and funded Creating & Coaching Essential Leaders, LLC to empower one woman at a time. In 2024, Dr Petit became the President of the Leadership in Practice Committee (LiPCom) part of the Biopharmaceutical section of the American Statistical Association.

Vivek Mohan, Regeneron

Vivek Mohan, Regeneron Vivek Mohan is an Associate Director of Statistical Programming overseeing Standards and Processes at Regeneron Pharmaceuticals. His current responsibilities include governing standards, leading process improvement initiatives, ensuring compliance and managing vendors.
Prior to Regeneron Vivek has worked at other pharmaceutical companies and CROs in a career spanning over 20 years. He has experience managing small to large biometrics teams and has a passion for people development and process excellence.

Archie Sachdeva, BMS

CG Wang Archie Sachdeva received Ph.D. in Biostatistics from University of Florida and Master’s in Applied Statistics and Informatics from Indian Institute of Technology, Bombay. She is currently working as a biostatistician at Bristol Myers Squibb, Princeton, New Jersey. Her research interests include application of Bayesian methods in clinical trials, augmenting randomized control trials with real-world data, Dynamic borrowing methods for hybrid control arms, predictive probability of trial success, survival analysis, and analysis of high-dimensional microbiome data.
Along with statistics, she is passionate about music and social good. She enjoys singing, cooking, organizing cultural and social events, and practicing yoga.

Mary Lai Salvaña, University of Connecticut

CG Wang Mary Lai Salvaña is an Assistant Professor in Statistics at the University of Connecticut (UConn). Prior to joining UConn, she was a Postdoctoral Fellow at the Department of Mathematics at University of Houston. She received her Ph.D. in Statistics at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia. She obtained her BS and MS degrees in Applied Mathematics from Ateneo de Manila University, Philippines, in 2015 and 2016, respectively. Her research interests include extreme and catastrophic events, risks, disasters, spatial and spatio-temporal statistics, environmental statistics, computational statistics, large-scale data science, and high-performance computing.

Heeju Lim, University of Connecticut

CG Wang Heeju is a Ph.D. student in Statistics at the University of Connecticut under the guidance of Professor Victor Hugo Lachos. She holds a Master's degree in Statistics from Korea University and a Bachelor's degree in Statistics from Sejong University. Her academic interests include Mixture Models, Financial Statistics, Time Series Analysis, and Bio Statistics.