Current Postdoctoral Fellows
Anastasia Bizyaeva (2022-present)
Research Area: Dynamical Systems and Control, Collective Behaviors
PhD 2022 - Mechanical and Aerospace Engineering - Princeton University (Advisor - Naomi Leonard)
Thesis - Nonlinear dynamics of multi-agent multi-opinion belief and opinion formation
PhD 2022 - Mechanical and Aerospace Engineering - Princeton University (Advisor - Naomi Leonard)
Thesis - Nonlinear dynamics of multi-agent multi-opinion belief and opinion formation
Olga Dorabiala (2023-present)
Research Area: Data-Driven Modeling and Machine Learning
PhD 2023 - Applied Mathematics - University of Washington (Advisor - J. Nathan Kutz and Sasha Aravkin)
Thesis - Robust Approaches for Unsupervised Learning
PhD 2023 - Applied Mathematics - University of Washington (Advisor - J. Nathan Kutz and Sasha Aravkin)
Thesis - Robust Approaches for Unsupervised Learning
Megan Ebers (2023-present)
Research Area: Data-Driven Discrepancy Modeling and Bio-Mechanics
PhD 2023 - Mechanical Engineering - University of Washington (Advisor - J. Nathan Kutz and Kat Steele)
Thesis - Machine Learning for Dynamical Models of Human Movement
PhD 2023 - Mechanical Engineering - University of Washington (Advisor - J. Nathan Kutz and Kat Steele)
Thesis - Machine Learning for Dynamical Models of Human Movement
Andrei Klishin (2022-present)
Research Area: Dynamical Systems, Networks, Systems
PhD 2020 - Physics - University of Michigan (Advisor - Greg van Anders)
Thesis - Statistical physics of design
PhD 2020 - Physics - University of Michigan (Advisor - Greg van Anders)
Thesis - Statistical physics of design
Zachary Nicolaou (2021-present)
Research Area: Networks, Multi-scale Physics and Dynamical Systems
PhD 2017 - Physics - California Institute of Technology (Advisor - Sandra Troian)
Thesis - Symmetry and variational analysis of fluid interface equations in the thin film limit
PhD 2017 - Physics - California Institute of Technology (Advisor - Sandra Troian)
Thesis - Symmetry and variational analysis of fluid interface equations in the thin film limit
Samuel Otto (2022-present)
Research Area: Dynamical Systems, Data-driven modeling
PhD 2022 - Mechanical and Aerospace Engineering - Princeton University (Advisor - Clancy Rowley)
Thesis - Advances in data-driven modeling and sensing for high-dimensional nonlinear systems
PhD 2022 - Mechanical and Aerospace Engineering - Princeton University (Advisor - Clancy Rowley)
Thesis - Advances in data-driven modeling and sensing for high-dimensional nonlinear systems
Prerna Patil (2022-present)
Research Area: Uncertainty Quantification, Model Reduction
PhD 2022 - Mechanical Engineering - University of Pittsburg (Advisor - Hessam Babaee)
Thesis - Real-time reduced order modeling of high-dimensional partial differential equations via time dependent subspaces
PhD 2022 - Mechanical Engineering - University of Pittsburg (Advisor - Hessam Babaee)
Thesis - Real-time reduced order modeling of high-dimensional partial differential equations via time dependent subspaces
Amin Rahman (2021-present)
Research Area: Dynamical Systems and Quantum Analog Systems
PhD 2017 - Mathematics - New Jersey Institute of Technology (Advisor - Denis Blackmore)
Thesis - Qualitative modeling and analysis of chaotic logical circuits and walking droplets: A dynamical systems approach
PhD 2017 - Mathematics - New Jersey Institute of Technology (Advisor - Denis Blackmore)
Thesis - Qualitative modeling and analysis of chaotic logical circuits and walking droplets: A dynamical systems approach
Ryan Raut (2021-present with Allen Institute)
Research Area: Computational Neuroscience
PhD 2021 - Neuroscience - Washington University (Advisor - Marcus Raichle)
Thesis - On arousal and the internal regulation of brain function: theory and evidence across modalities and species
PhD 2021 - Neuroscience - Washington University (Advisor - Marcus Raichle)
Thesis - On arousal and the internal regulation of brain function: theory and evidence across modalities and species
Doris Voina (2022-present)
Research Area: Computational Neuroscience, Data-Driven Modeling
PhD 2022 - Applied Mathematics - Washington (Advisor - Eric Shea-Brown)
Thesis - A discovery of neural network architectures for context-dependent computations
PhD 2022 - Applied Mathematics - Washington (Advisor - Eric Shea-Brown)
Thesis - A discovery of neural network architectures for context-dependent computations