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Computational Neuroengineering and Control Lab

We are an interdisciplinary research group working at the intersection of computational neuroscience, dynamical systems, control theory, machine learning, and neural engineering.

Our work brings together computational modeling, simulation, signal analysis, and experimental approaches to understand and control complex biological systems.

Principal Investigator

Gautam Kumar, Ph.D.

Associate Professor
Department of Chemical and Materials Engineering
San José State University

Dr. Gautam Kumar leads the Computational Neuroengineering and Control Lab at San José State University. His research integrates computational neuroscience, dynamical systems, control theory, and machine learning to develop predictive and feedback-control approaches for neural and physiological systems.

Current research includes closed-loop neurostimulation, computational modeling and control, neural-state estimation, auditory stimulation and affective dynamics, and data-driven approaches to adaptive therapies.

Email → Faculty Profile → Google Scholar → Curriculum Vitae →

Current Lab Members

Our group brings together students and researchers interested in computational neuroscience, neural engineering, dynamical systems, machine learning, and control.

Jeremy Janssen

Graduate Student, Chemical Engineering

Research Focus: Closed-loop optimal neurostimulation for regulating neuronal synchronization in excitatory-inhibitory networks

Nathan Hyatt

Graduate Student, Materials Engineering

Research Focus: Auditory stimulation intervention for stress management, EEG signal processing

Daniel M. Lee

Graduate Researcher

M.S. in Software Engineering

Research Focus: Deep-learning predictions of gait events from neural data

Jeffrey Gu

Graduate Researcher

M.S. in Software Engineering

Research Focus: Closed-loop optimal deep brain stimulation (DBS) strategies for Parkinson's disease

Ragavardhini Pattangi

Undergraduate Researcher

Research Focus: Deep-learning predictions of human walking performance from neural data

Lab Alumni

Joe Schmalz

Ph.D. in Chemical Engineering, 2021 (University of Idaho)

Current Position: Computational biologist at Adaptive Biotechnologies

Andrew Branen

M.S. in Chemical Engineering, 2021 (University of Idaho)

Current Position: Applied machine learning engineer at Bayer

Benjamin Plaster

M.S. in Chemical Engineering, 2021 (University of Idaho)

Current Position: Machine learning and AI engineer at Neogen Corporation

Aanuoluwapo Olumuyiwa

M.S. in Chemical Engineering, 2025

Former Graduate Researcher

Thi Tuyet Bach Giang

M.S. in Statistics

Former Research Associate, 2024-2025

Duc Quang Tran

M.S. Software Engineering, 2026

Former Graduate Researcher, 2024-2025

Richard Ky

M.S. in Computer Engineering, 2024

Former Graduate Researcher

Current Position: Ph.D. Candidate at UC Irvine

Rachel V. Quinarez

B.S. in Aerospace Engineering

Former Undergraduate Researcher, 2022-2024

John Clear

B.S. in Software Engineering, 2025

Former Undergraduate Researcher

Jacquelin Martinez-Alvarez

Undergraduate Student, Chemical Engineering (University of Idaho)

Outreach Neural Engineering, 2017-2019

Research Collaborators

Professor Doris D. Wang, Ph.D.

University of California, San Francisco

Collaborative research on neural-data-driven prediction of gait events during deep brain stimulation.

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