Biography and education
Aniruddha Bora is an Assistant Professor in the Department of Computer Science at Texas State University. His research lies at the intersection of scientific machine learning, scientific reinforcement learning, agentic AI, data-driven scientific computing, and numerical methods, with a focus on developing intelligent, physics-grounded computational approaches for complex scientific and engineering systems.
His research interests include scientific machine learning, physics-informed neural networks, neural operators, reinforcement learning, agentic AI, deep learning, mathematical modeling, computational fluid dynamics, climate and Earth-system modeling, and multiscale heat transfer. A central theme of his research is integrating physical knowledge, machine learning, and autonomous decision-making to develop reliable AI systems for scientific discovery, prediction, optimization, and control.
Prior to joining Texas State University, Dr. Bora was a Postdoctoral Research Associate in the Department of Applied Mathematics at Brown University, where he worked on scientific machine learning and physics-informed computational methods. He has also served as a J. Tinsley Oden Faculty Fellow at the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin.
Dr. Bora received his Ph.D. in Computational Analysis and Modeling from Louisiana Tech University, where his doctoral research focused on numerical and neural-network-based methods for multiscale heat conduction and thermal transport. He earned an M.S. in Applied Mathematics from South Asian University in New Delhi, India, and a B.Sc. in Mathematics from Cotton College in Guwahati, India.
Ph.D., Computational Analysis and Modeling
Louisiana Tech University, Louisiana, USA, 2021
Dissertation: Gradient Preserved Method and Neural Network Method for Solving Heat Conduction Equation with Variable Thermal Conductivity in Double Layered Structures
Advisor: Prof. Weizhong Dai
M.S., Applied Mathematics
South Asian University, New Delhi, India, 2015
Thesis: Finite Difference Method of Order Two in Time and Four in Space for the Solution of Non-Linear Parabolic Equation
Advisor: Prof. Ranjan K. Mohanty
B.Sc., Mathematics
Cotton College, Guwahati, Assam, India, 2013
His research interests include scientific machine learning, physics-informed neural networks, neural operators, reinforcement learning, agentic AI, deep learning, mathematical modeling, computational fluid dynamics, climate and Earth-system modeling, and multiscale heat transfer. A central theme of his research is integrating physical knowledge, machine learning, and autonomous decision-making to develop reliable AI systems for scientific discovery, prediction, optimization, and control.
Prior to joining Texas State University, Dr. Bora was a Postdoctoral Research Associate in the Department of Applied Mathematics at Brown University, where he worked on scientific machine learning and physics-informed computational methods. He has also served as a J. Tinsley Oden Faculty Fellow at the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin.
Dr. Bora received his Ph.D. in Computational Analysis and Modeling from Louisiana Tech University, where his doctoral research focused on numerical and neural-network-based methods for multiscale heat conduction and thermal transport. He earned an M.S. in Applied Mathematics from South Asian University in New Delhi, India, and a B.Sc. in Mathematics from Cotton College in Guwahati, India.
Ph.D., Computational Analysis and Modeling
Louisiana Tech University, Louisiana, USA, 2021
Dissertation: Gradient Preserved Method and Neural Network Method for Solving Heat Conduction Equation with Variable Thermal Conductivity in Double Layered Structures
Advisor: Prof. Weizhong Dai
M.S., Applied Mathematics
South Asian University, New Delhi, India, 2015
Thesis: Finite Difference Method of Order Two in Time and Four in Space for the Solution of Non-Linear Parabolic Equation
Advisor: Prof. Ranjan K. Mohanty
B.Sc., Mathematics
Cotton College, Guwahati, Assam, India, 2013
Teaching Interests
Research Interests
Featured grants
- Zhang, Shixuan (Principal), Bora, Aniruddha (Co-Principal), Tai, Sheng-lun (Co-Principal), Li, Lingcheng. Drift-Aware Initialization of Coupled Earth System Models for Scalable Subseasonal-to-Seasonal Prediction Using Agentic Al, Department of Energy (Genesis Mission), Federal. (Submitted: May 1, 2026, Funded: August 2026 - Present). Grant.
- Bora, Aniruddha. BobCatalyst POC Grant (TrashFormer), Texas State University, $22450. (Submitted: 2026, Funded: July 2026 - May 2027). Grant.
- Bora, Aniruddha. BobCatalyst Innovation Accelerator Program (BIAP) Award, Texas State University, $5000. (Funded: June 2026 - Present). Grant.
- Bora, Aniruddha. PIER: Physics-Informed, Energy-efficient, Risk-aware routing, Texas State University, Texas State University, $12000. (Submitted: May 1, 2025, Funded: January 1, 2026 - Present). Grant.
- Bora, Aniruddha. Physics-Informed Generative AI (PIGAN) – ALCF Director’s Discretionary Allocation, Argonne National Laboratory, Argonne Leadership Computing Facility (ALCF), U.S. Department of Energy. (Submitted: 2025, Funded: 2025 - 2026). Grant.

Featured scholarly/creative works
- Bora, A., Zhang, S., Shukla, K., Harrop, B. E., Karniadakis, G., & Leung, L. R. (2026). Inception UNet (IUNet) and Multi-scale Multi-branch (M&M) UNet Plug-In Neural Operators for Online Bias Correction in E3SM Atmosphere Model. Journal of Computational Physics, 115294. https://doi.org/10.1016/j.jcp.2026.115294
- Oommen, V., Khodakarami, S., Bora, A., Wang, Z., & Karniadakis, G. (n.d.). Learning turbulent flows with generative models: Super-resolution, forecasting, and sparse flow reconstruction. Nature Communication. https://doi.org/https://doi.org/10.1038/s41467-026-70145-4
- Bora, A., Alvarez, I., Chalfant, J., & Chryssostomidis, C. (2026). Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic Study on Coolant Velocity Estimation. Elsevier BV. https://doi.org/10.2139/ssrn.6429612
- Bora, A. (2026, January 24). HeatEnergyDecay: Lean 4 proof of energy decay for linear heat-type flows. https://doi.org/https://doi.org/10.5281/zenodo.18362473
- Oommen, V., Bora, A., Zhang, Z., & Karniadakis, G. E. (2025). Integrating neural operators with diffusion models improves spectral representation in turbulence modelling. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 481(2309). https://doi.org/10.1098/rspa.2024.0819
Featured awards
- Award / Honor Recipient: Nucleate Activator Program – Finalist (2026 Cohort), Nucleate (Activator Program). October 2025 - May 2026
- Award / Honor Recipient: Audience Choice Award, Nucleate Texas. October 2025 - May 2026
- Award / Honor Recipient: Bobcat Innovation Challenge, Texas State University. April 11, 2026
- Award / Honor Recipient: BobCatalyst Innovation Accelerator Program Award, Texas State University. April 2026 - April 8, 2026
- Award / Honor Recipient: College of Engineering and Science Scholarship, Louisiana Tech University. 2019 - 2020

Featured service activities
- Reviewer / Referee
Nature Machine Intelligence
- Reviewer / Referee
Neural Networks
- Reviewer / Referee
Engineering applications of artificial intelligence
- Reviewer / Referee
Neural computation
- Reviewer / Referee
Journal of computational physics
- Reviewer / Referee
Neurocomputing
