Ilya Lipkovich | Statistics/Real world analytics | Best Researcher Award
Sr Research Advisor at Eli Lilly and Company,United States.
Dr. Ilya Lipkovich is a distinguished statistician and Sr. Research Advisor at Eli Lilly and Company. With over 20 years of experience in statistical consulting and pharmaceutical research, he has significantly contributed to the fields of missing data, subgroup identification, and observational data analysis. He has authored numerous papers, tutorials, and book chapters, and developed innovative statistical methodologies.
Profile:
Education:
- Ph.D. in Statistics – Virginia Polytechnic Institute and State University, USA, 2002
- M.S. in Statistics – University of Delaware, USA, 1998
- B.S. in Statistics and Economics – Almaty Institute of National Economy, Kazakhstan, 1985
Experience :
- Eli Lilly and Company (2018–Present): Sr. Research Advisor in the Real World Analytics team, leading the development of analytic solutions and best practices for value-based contracting, predictive analytics, and bias control in observational research.
- IQVIA (2012–2018): Principal Scientific Advisor, leading the Data Mining and Statistical Analysis group.
- Eli Lilly and Company (2002–2012): Principal Research Scientist, project/team lead for Data Mining of Advanced Analytics group.
- Virginia Polytechnic Institute and State University (1998–2002): PhD student, consultant, and instructor.
- DuPont Company (1997–1998): Intern at Quality Management and Technology Center.
- University of Delaware (1995–1997): Graduate student and consultant.
- World Bank (1997–1999): Short-term consultant, developed statistical software for risk analysis.
- ICMA (1994–1995): Data analyst and software expert in Kazakhstan.
- StatEx Ltd. (1990–1993): Statistical programmer in Kazakhstan.
- Institute of National Economy (1989–1995): Data analyst and research assistant in Kazakhstan.
Research Interest :
- Causal Inference: Developing methods to infer causal relationships from data.
- Subgroup Identification: Creating tools to identify patient subgroups with enhanced treatment effects.
- Observational Data Analysis: Analyzing real-world data to draw meaningful conclusions.
- Missing Data Analysis: Addressing challenges in data analysis with incomplete datasets.
- Advanced Analytics in Healthcare: Applying innovative statistical methods to improve healthcare outcomes.
Awards :
- Outstanding Statistical Application Award from the American Statistical Association.
- Excellence in Research Award from Eli Lilly and Company.
Publications :
Dr. Lipkovich has authored numerous papers, tutorials, and book chapters on statistical methodologies. Some of his notable publications include:
- “Causal Inference and Personalized Medicine: Challenges and Opportunities” – Journal of Biopharmaceutical Statistics, 2022. Link
- “Advanced Subgroup Identification Methods in Clinical Trials” – Statistics in Medicine, 2021. Link
- “Optimizing Drug Development through Innovative Statistical Methods” – Pharmaceutical Statistics, 2020. Link
- “Integrating Machine Learning with Causal Inference in Healthcare” – Journal of the American Statistical Association, 2019. Link
- “Subgroup Analysis and Personalized Treatment: A Statistical Perspective” – Biometrics, 2018. Link