1. Paper 'MDP Geometry, Normalization and Reward Balancing Solvers' accepted to AISTATS 2025.
2. Paper 'Analysis of Value Iteration Through Absolute Probability Sequences' under review, 2025.
3. Paper 'Closing the Gap Between SVRG and TD-SVRG with Gradient Splitting' accepted to TMLR 2024.
Research Experience
1. Worked on SemaFor DARPA project with BU team led by Prof. Kate Saenko.
2. Participated in a project on Explainable AI with Prof. Sarah Adel Bargal.
3. Visiting researcher at the University of Cyprus, presented MDP Geometry paper there.
Education
Degree: PhD; Institution: Boston University; Advisors: Prof. Alex Olshevsky, Prof. Yannis Paschalidis; Year: 6th year; Department: Computer Science.
Background
Research Interests: Reinforcement Learning (both theoretical and practical), other topics in Machine Learning including Computer Vision, Explainability, and Deep Fake Detection. Background: Completed PhD at Boston University and currently a postdoc at Aalto University.
Miscellany
Skills: Algorithmic - Reinforcement Learning, Deep Learning, classic Machine Learning algorithms, Time Series analysis; Software - PyTorch, Tensorflow (1&2), Linux (+git), SQL. Fluent in Mandarin, English, and native Russian.