As one of well-known principles, it has become Dr. Zhou’s belief the earlier statistics gets involved in Drug Research & Development, the better outcome will be. Over years of work, Dr. Zhou has incorporated the principles and techniques of statistics as a discipline into the full cycle of Drug R&D, including the successful market applications of oncology immunotherapy Keytruda and cervical cancer vaccine Gardasil, as well as the publication of several articles in top medical journals.

Graduated with a B.S. in Statistics from Nankai University in 2006 and a Ph.D. from The George Washington University in 2011, Dr. Zhou has enriched his comprehension of statistics via a unique career pathway in Drug R&D. His internship at FDA and postdoc research experiences at drug toxicity (Ohio State University) and clinical trials data analyses (Duke University) have opened his door to Drug R&D. He later joined MSD (2015-2018) as a statistician for Phase I & III Drug Development Projects in Oncology and Vaccine areas, including successful filings of Keytruda and Gardasil.

Bearing the open problem regarding a more effective approach to Drug R&D, he went to Sun Yat-Sen university for a grand theory on the full chain Drug R&D (from lab discovery all the way to post-market surveillance) with focuses on the usage of machine learning and causal inference. His teaching on core statistical courses on both undergraduate and graduate levels, including machine learning, has promoted his pursuit on the fundamentals of machine learning via equivariance criterion. Meanwhile, he has conducted several research projects on medical data with the extensive usage of optimal treatment regime methods in precision medicine, including a methodology development project on oncology clinical trials.

During the Covid 19 pandemic, he has participated in several Covid-19 vaccine development projects as the independent statistician, where he has witnessed successes and failures and gained first-hand-on experiences over vaccine development, especially on the early-stage planning. Those experiences have further stimulated him into the development of a statistical theory over the full chain Drug R&D.

• Statistics in Drug Research & Development
• Applications and Fundamentals of Machine Learning
• Statistical Inference with a Special Focus on the Equivariance Criterion
• Methodology Development on Medical Data Analyses
• Precision Medicine

Research Intern                                                                                       Jun 2009 - Aug 2009

U.S Food and Drug Administration, Silver Spring, Maryland

• Worked on two projects on clinical trials in oncology setting with oncology biologics group
• Explored the potential informativeness of censorings in progression-free survival (PFS) due to loss-to-follow- up
• Studied comparison-level (group-wise) correlation vs. patient-level (individual) correlation

Postdoctoral Researcher                                                                              Oct 2011 – Jul 2013

Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio

• Applied random forests method to analyze high dimensional data for a pharmaceutical classification project of toxicity of chemical compounds
• Leveraged nonparametric methods to improve accuracy and introduced dimension reduction
• Developed weight-of-evidence approaches to estimate and detect uncertainties in predictions

Postdoctoral Associate                                                                             Aug 2013 – Aug 2014

Department of Biostatistics and Bioinformatics, Duke University, Durham, NC

• Worked on prostate cancer trials data analysis
• Developed related methodologies in survival analysis

Senior Scientist                                                                              Jan 2015 – Apr 2018

Biostatistics and Research Decision Sciences – Asia & Pacific, Merck Research Laboratory, Beijing, China

• Worked on Phase I & III Drug Development Projects in CV, Oncology and Vaccine areas: Authoring protocols, Conducting Analysis & Report Activities and Supporting Publications
  • HPV vaccine Gardasil in mid-aged women and men
  • Phase I Study of Pembrolizumab in Chinese Subjects with Non-Small-Cell Lung Cancer
  • Diabetes
• Conducted research on Multiple Region Clinical Trial

Associate Professor/Lecturer                                                                             Apr 2018 – May 2023

Department of Statistics, School of Mathematics, Sun Yat-Sen University

• Taught undergraduate and graduate courses
  • Mathematical Statistics, Multivariate Statistics, Machine Learning, Complex Data Analysis
• Conducted Academic Research
  • Statistical Inference: Equivariance Principle and Its Usage in Linear Model and Multivariate Analysis
  • Precision Medicine: Big Data Analysis and Optimal Treatment Regime
  • Survival Analysis: A Novel Statistical Theory and Its applications on Oncology Clinical Trials
  • Privacy and Confidentiality Protection and Its Implications in Design and Analysis

Independent Unblinded Statistician                                                                             Apr 2020 - Feb 2023

• Participated in Covid-19 Vaccine Development and Provided DSMB Statistical Analysis Reports
  • Recombinant New Coronavirus Vaccine (CHO Cells) to Prevent SARS-CoV-2 Phase I Clinical Trial & Phase II Clinical Trial (NCT04961359)
  • SARS-CoV-2 mRNA Vaccine Phase I Clinical Trial, Phase Ib Clinical Trial & Phase II Clinical Trial (NCT05364047)
  • Recombinant New Coronavirus Fusion Protein Vaccine Phase I Clinical Trial & Phase II Clinical Trial (NCT04445194)
• Participated in Oncology Medicine Development and Provided iDMC Statistical Analysis Reports
  • Phase 2 Study of KH903 in Patients With Advanced Gastric or Gastroesophageal Junction Adenocarcinoma As Second-Line Therapy (NCT04555304)

Assistant Professor/Adjunct Associate Researcher                                    June 2023 – Present

Academy of Pharmacy, Xi'an Jiaotong-Liverpool University

• Teaching undergraduate and graduate biostat courses
• Conducting Academic Research
  • Statistical Inference: Equivariance Principle and Its Usage in Linear Model and Multivariate Analysis
  • Clinical Trial Data Modeling and Analysis: A Novel Statistical Theory and Its applications on Oncology Clinical Trials