Biosketch
After obtaining his Bachelor’s degree in System Analysis at the National Technical University of Ukraine ”Igor Sikorsky Kyiv Polytechnic Institute” and his Master’s degree in Data Science at LMU Munich, Valentyn decided to do research in causal inference and data-driven decision-making. Now, he is a PhD candidate at the Institute of AI in Management, LMU Munich, under the supervision of Prof. Stefan Feuerriegel.
relAI Research
Uncertainty quantification in causal machine learning
In my research, I apply tools of machine learning to develop new methods for causal inference problems, e.g., counterfactual prediction and treatment effect estimation. These methods, known under the term causal machine learning (causal ML), can be further employed for algorithmic decision-making in medicine, marketing, and policy-making. Specifically, I focus my attention on different open gaps in existing causal ML methods, which preclude them from application to real-world problems and, thus, hinder their reliability. Hence, the main directions of my research include
- (a) model validity (model selection, sensitivity analysis)
- (b) model flexibility (extensions to complex, multi-source, time-varying data)
(c) uncertainty quantification (uncertainty of estimation, predictive uncertainty)
In the future, I see myself working on both theoretical and applied aspects of the reliable causal ML, also beyond the mentioned directions (a-c).