EDUCATION
- Ph.D., Industrial and Systems Engineering, Lehigh University, PA, USA, 2014 - 2018
- M.B.A., McNeese State University, LA, USA, 2011 - 2013
- B.S., Applied Mathematics and Computer Science, Lomonosov Moscow State University, Moscow, Russia, 2004 - 2008
WORK HISTORY
- Staff Research Scientist, IBM Research, Thomas J. Watson Research Center, 06/2022 - Present
- Research Staff Member, IBM Research, Thomas J. Watson Research Center, 04/2021 - 06/2022
- Principal Investigator, MIT-IBM Watson AI Lab, 09/2020 - Present
- Research Scientist, IBM Research, Thomas J. Watson Research Center, 10/2018 - 03/2021
- Research Intern, IBM Research, Thomas J. Watson Research Center, 05/2018 - 08/2018
- Research Co-op, IBM Research, Thomas J. Watson Research Center, 08/2017 - 05/2018
- Research Intern, IBM Research, Thomas J. Watson Research Center, 06/2017 - 08/2017
- Research Assistant, Lehigh University, 08/2014 - 05/2017
- Teaching Assistant, Lehigh University, 08/2014 - 05/2015
- Research Assistant, McNeese State University, 01/2012 - 12/2013
- Teaching Assistant, McNeese State University, 01/2012 - 12/2013
- Software Engineer, FPT Software Company, 09/2008 - 08/2009
- Teaching Assistant, Lomonosov Moscow State University, 09/2007 - 05/2008
RPI-IBM PROJECT
- Principal Investigator, "Interpretable Foundation Models for General-Purpose Time Series Analysis": 01/2025 - 12/2025
MIT-IBM PROJECTS
- Principal Investigator, "Safe Learning for Time Series Problems: Data, Structure and Optimization": 01/2023 - 12/2025
- Principal Investigator, "Safe AI Certification": 01/2022 - 12/2022
- Principal Investigator, "Safety Structures, Certification, and Training for AI in the Feedback Loop": 01/2021 - 12/2021
- Co-Principal Investigator, "Hierarchical Disentangled Representations for Scalable Multi-agent Reinforcement Learning": 09/2020 - 09/2021
IBM RESEARCH ACCOMPLISHMENTS
- Granite Time Series Foundation Models (O-level), 2024
- Research Contributions to Time Series Foundation Models (A-level), 2023
- Federated Learning Security and Privacy (O-level), 2022
- Dynamic Approaches for Machine Learning (A-level), 2022
- Regression Optimization for Heavy Processing Industries (A-level), 2022
- Combinatorial Sparsity for AI (A-level), 2022
- Stochastic Gradient Methods: Theory and Applications (A-level), 2021
- SROM: Smarter Resource & Operations Management (A-level), 2019
HONORS & AWARDS
- INFORMS Senior Member, 2024
- 2022 Pat Goldberg Memorial Best Paper Award, 2023
- IBM 9th Plateau Invention Achievement Award, 2023
- IBM Outstanding Technical Achievement Award, Dynamic Approaches for Machine Learning, 2023
- IBM Outstanding Technical Achievement Award, Regression Optimization for Heavy Processing Industries, 2023
- IBM Outstanding Technical Achievement Award, Federated Learning Security and Privacy, 2023
- IBM Outstanding Technical Achievement Award, Combinatorial Sparsity for AI, 2023
- IBM 8th Plateau Invention Achievement Award, 2023
- IBM Master Inventor, 2022
- IBM 7th Plateau Invention Achievement Award, 2022
- IBM 6th Plateau Invention Achievement Award, 2022
- IBM Outstanding Technical Achievement Award, Stochastic Gradient Methods: Theory and Applications, 2022
- IBM 5th Plateau Invention Achievement Award, 2022
- IBM 4th Plateau Invention Achievement Award, 2022
- IBM 3rd Plateau Invention Achievement Award, 2021
- IBM 2nd Plateau Invention Achievement Award, 2020
- IBM Research Division Award, 2020
- IBM Outstanding Technical Achievement Award, SROM: Smarter Resource & Operations Management, 2020
- IBM 1st Plateau Invention Achievement Award, 2020
- NeurIPS 2019 Top Reviewers, 2019
- Elizabeth V. Stout Dissertation Award, Lehigh University, PA, USA, 2019
- Van Hoesen Family Best Publication Award, Lehigh University, PA, USA, 2018
- Dean’s Doctoral Fellowship (RCEAS), Lehigh University, PA, USA, 2016 - 2017
- Beta Gamma Sigma (Academic Honor), McNeese State University, LA, USA, 2014
