FACULTY
J. Nathan Kutz, Director
Robert Bolles and Yasuko Endo Professor
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Department of Applied Mathematics, Physics, Mechanical Engineering, Electrical Engineering & eScience Institute
Robert Bolles and Yasuko Endo Professor
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Department of Applied Mathematics, Physics, Mechanical Engineering, Electrical Engineering & eScience Institute
Research: Data-driven modeling, dynamical systems & machine learning, optical and atomic physics, neuroscience
Steven L. Brunton, Associate Director
James B. Morrison Endowed Career Development Professor in Mechanical Engineering
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Department of Mechanical Engineering, Applied Mathematics & eScience Institute
James B. Morrison Endowed Career Development Professor in Mechanical Engineering
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Department of Mechanical Engineering, Applied Mathematics & eScience Institute
Research: Data-driven modeling, control theory, dynamical systems & machine learning, fluid dynamics and turbulence
Krithika Manohar, Thrust Lead: Sensing and Optimization
Assistant Professor
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Department of Mechanical Engineering
Assistant Professor
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Department of Mechanical Engineering
Research: Data-driven modeling, sensors & sensor placement, dynamical systems & machine learning
David Beck
Research Associate Professor
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Department of Chemical Engineering, Computer Science & eSciences Institute
Research Associate Professor
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Department of Chemical Engineering, Computer Science & eSciences Institute
Research: Data intensive biology and chemistry, data mining, open-source biological data
Maryam Fazel
Moorthy Family Professor
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Department of Electrical Engineering, Mathematics, Statistics and Computer Science
Moorthy Family Professor
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Department of Electrical Engineering, Mathematics, Statistics and Computer Science
Research: Data science, optimization, robotics and control
Daniela Witten
Dorothy Gilford Endowed Chair of Mathematical Statistics
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Department of Biostatistics & Statistics
Dorothy Gilford Endowed Chair of Mathematical Statistics
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Department of Biostatistics & Statistics
Research: Statistical learning, optimization, high-dimensional data
STAFF
VISITING FACULTY
Cássio Oishi (Associate Professor, São Paulo State University, Brazil)
Fall 2022 — Summer 2024
Research Area: Computational Fluid Dynamics, Non-Newtonian Mechanics, Data-driven modeling
Research Area: Computational Fluid Dynamics, Non-Newtonian Mechanics, Data-driven modeling
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
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
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 Pittsburgh (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 Pittsburgh (Advisor - Hessam Babaee)
Thesis - Real-time reduced order modeling of high-dimensional partial differential equations via time dependent subspaces
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
Joe Bakarji (2020-2023)
Research Area: Stochastic and Multiscale Modeling
PhD 2020 - Mechanical Engineering - Stanford University (Advisor - Daniel Tartakovsky)
Thesis - Stochastic multiscale modeling of complex materials
PhD 2020 - Mechanical Engineering - Stanford University (Advisor - Daniel Tartakovsky)
Thesis - Stochastic multiscale modeling of complex materials
Ryan Raut (2021-present)
Research Area: 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
Urban Fasel (2021-2022)
Research Area: Data-Driven Modeling
PhD 2020 - Mechanical Engineering - ETH Zurich (Advisor - P. Ermanni)
Thesis - Reduced-order aeroelastic modeling of morphing wings for optimization and control
PhD 2020 - Mechanical Engineering - ETH Zurich (Advisor - P. Ermanni)
Thesis - Reduced-order aeroelastic modeling of morphing wings for optimization and control
Shaowu Pan (2021-2022)
Research Area: Deep Learning and Reduced Order Models
PhD 2020 - Aerospace Engineering - Michigan (Advisor - Karthik Duraisamy)
Thesis - Robust and interpretable learning for operator-theoretic modeling of nonlinear dynamics
PhD 2020 - Aerospace Engineering - Michigan (Advisor - Karthik Duraisamy)
Thesis - Robust and interpretable learning for operator-theoretic modeling of nonlinear dynamics
POSTBACCALAUREATE
Mel Mashiku
Research Scientist/Engineer, January — December 2023
GRADUATE STUDENTS
Sam Anhert (ME)
PhD 2027 (Expected)
Research Area: Fluid Dynamics and Turbulence
Research Area: Fluid Dynamics and Turbulence
Nicholas Zolman (ME)
PhD 2027 (Expected)
Research Area: Machine Learning for Physics and Engineering
Research Area: Machine Learning for Physics and Engineering
Jan Williams (ME)
PhD 2027 (Expected)
Research Area: Optimization and Sensors
Research Area: Optimization and Sensors
Mars Gao (CSE)
PhD 2024 (Expected)
Research Area: Machine learning and statistical learning
Research Area: Machine learning and statistical learning
Mike Wendels (AMATH)
PhD 2024 (Expected)
Research Area: Machine learning and statistical learning
Research Area: Machine learning and statistical learning
Yuxuan Bao (AMATH)
PhD 2025 (Expected)
Research Area: Machine learning and model discovery
Research Area: Machine learning and model discovery
Frank Mei (AMATH)
PhD 2024 (Expected)
Research Area: Optimization and Sensors
Research Area: Optimization and Sensors
Joey Williams (AMATH)
PhD 2024 (Expected)
Research Area: Fluids and Granular Materials
Research Area: Fluids and Granular Materials
Jake Stevens-Haas (AMATH with Sasha Aravkin)
PhD 2023 (Expected)
Research Area: Optimization and Machine Learning
Research Area: Optimization and Machine Learning
Olga Dorabiala (PhD 2023 - AMATH)
Research Area: Optimization and Sensors
Aleksei Sholokov (PhD 2023 - AMATH)
Research Area: Optimization and Machine Learning
Yue Sun (PhD 2022 - ECE)
Thesis — Nonconvex Optimization and Model Representation with Applications in Control Theory and Machine Learning
Isabel Scherl (PhD 2022 - ME)
Thesis — Experimental optimization, modeling and control of cross-flow turbine arrays
Andy Goldschmidt (PhD 2022 - Physics)
Thesis — Data driven modeling and control of quantum dynamics
Katherine Owens (PhD 2022 - AMATH)
Thesis — Life Together: Modeling the Collective Behavior of Cellular Communities
Diya Sashidhar (PhD 2021 - AMATH)
Thesis — Data-driven methods for time series forecasting, classification and uncertainty quantification
GRADUATE STUDENT VISITORS
Pauline Brumm (University of Darmstadt)
Fall 2022
Gabriele Bufolo (University of Brasilia)
Fall 2022
Paolo Conti (Milan Polytechnic)
Fall 2022 — Spring 2023
Jonas Kneifl (University of Stuttgart)
Summer 2022 — Fall 2022
Raphael Leitritz (University of Stuttgart)
Summer 2022
Marco Pizzoli (University of Rome "La Sapienza")
Spring 2022 — Summer 2022