Indrasis Chakraborty joined the Center for Applied Scientific Computing (CASC) in December 2019 as a data scientist. His research interests include data-driven system identification, dimensionality reduction, artificial data generation, and reinforcement learning.

Indrasis is currently leading a 3-year Department of Energy, Office of Electricity funded project (total funding $300K), on developing machine learning algorithms for quantum hardware, applied to power system fault detection.

Indrasis has proven technical capability in machine learning-based modeling and transfer learning-based control development through several Lab-Directed projects (total funding $2.5M) and projects from Office of Science (total funding $1M)

Ph.D. Mechanical Engineering, University of Florida, Gainesville, Florida

M.A. Applied Mathematics, University of Florida, Gainesville, Florida

M.S. Mechanical Engineering, University of Florida, Gainesville, Florida

Kelley, B.M., Chakraborty, I., Gallagher, B.J. and Merl, D.M., Lawrence Livermore National Security LLC, 2025. Industrial control system device classification. U.S. Patent 12,259,717.

Bhattacharjee, K., Kundu, S., Chakraborty, I. and Dasgupta, A., 2025, January. Who should I trust? A Visual Analytics Approach for Comparing Net Load Forecasting Models. In 2025 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge) (pp. 1-5). IEEE.

Azhar, A., Chakraborty, I., Visser, A., Liu, Y., Lerback, J.C. and Oerter, E., 2025. Machine learning prediction of tritium‐helium groundwater ages in the Central Valley, California, USA. Water Resources Research, 61(1), p.e2024WR038031.

Yu, S., Chakraborty, I., Anderson, G.J., Lucas, D.D., Lops, Y. and Galea, D., 2024. UFNet: Joint U-Net and fully connected neural network to bias correct precipitation predictions from climate models. Artificial Intelligence for the Earth Systems, 3(3), p.e230076.

Goswami, B., Chakraborty, I. and Chatterjee, A., 2023. Small in-plane oscillations of a slack catenary using assumed modes. arXiv preprint arXiv:2310.01308.

Chakraborty, I., Dasgupta, A., Rubio-Herrero, J., Nandanoori, S.P., Kundu, S. and Chandan, V., 2023. Application of Machine Learning for Energy-Efficient Buildings. In Handbook of Smart Energy Systems (pp. 1-22). Cham: Springer International Publishing.

Ladd, A. and Chakraborty, I., 2022, June. gridds: a data science toolkit for energy grid machine learning. In Proceedings of the Thirteenth ACM International Conference on Future Energy Systems (pp. 542-551).

Chakraborty, I., Kelley, B.M. and Gallagher, B., 2021. Industrial control system device classification using network traffic features and neural network embeddings. Array, 12, p.100081.