About

I’m a registered pharmacist, epidemiologist (Ph.D.), health data scientist (postdoc) and R enthusiast and currently work as an Instructor in Medicine at Harvard Medical School and Investigator in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital in Boston, USA.

Research interests

My research interests focus on the development and application of machine and deep learning methods to improve causal inference from multimodal clinical data dimensions combining electronic health records (EHR), imaging data, unstructured notes, and administrative claims databases. Over the years, I have also developed deep domain expertise in the clinical fields of cancer research as well as cardiovascular medicine and neuroscience. I’m a big advocate of transparent and reproducible research and have a passion for developing software to enable others to learn, grow and be impactful. At a glance:

• Multimodal fusion deep learning (EHR, claims data, imaging, NLP)
• Causal inference and comparative effectiveness research
• Cancer research/oncology
• Transparency and reproducibility in research methods
• Software development in quantitative research

I recently served as invited panelist at the 2023 International Society for Health Economics and Outcomes Research (ISPOR) closing panel, sharing some innovative work on overcoming frequently encountered isssues in US electronic health record data:

Some other recent projects centered around missing data approaches in EHR, prognostics scores in oncology (Ann Oncol 2021, Front Artif Intell 2021) and applications of machine learning and deep learning networks (autoencoders) to improve confounding control in comparative effectiveness research (Epidemiology 2021). He has further conducted and published multiple studies on drug repurposing in oncology (Sci Rep 2017, Int J Cancer 2017), time-dependent biases (Eur J Epidemiol 2017, Clin Epidemiol 2018) and long-term population level cancer survival using national and European cancer registries (Haematologica 2017, Eur Heart J 2018, Cancer 2019) for which he received the Stephan-Weiland prize and the Advancement Award in Epidemiology by the German Association for Medical Informatics, Biometry and Epidemiology.

Training

• 2018-2020 - Postdoctoral training in machine and deep learning in electronic health records (EHR), Roche Innovation Center Munich, Germany
• 2019 - Ph.D. in Epidemiology, Medical Faculty, University of Heidelberg, Germany
• 2018 - Board certification as specialized pharmacist in drug information, Germany
• 2015 - Pharmacy degree (Registered Pharmacist), College of Pharmacy, Philipps-University Marburg, Germany