Research
Pankaj Chouhan was a postdoctoral research associate in the PULSE Lab (2024–2025), working on machine learning and species distribution modeling for agriculture under climate change. The project used MaxEnt, a maximum-entropy method for species distribution modeling, to predict suitable habitats for invasive insect pests across the contiguous United States under current and future climate scenarios, in collaboration with Muhammad Haseeb at Florida A&M University and with funding from USDA NIFA. Pankaj presented this work at the FSU Scientific Computing colloquium in February 2025 ("Predicting Suitable Habitats for Pest Insects in the Continental US Under Current and Future Climate Conditions Using Maxent"). The code is available on GitHub.
Background
Pankaj earned a Ph.D. in Computational Science from Florida State University in 2024, advised by Sachin Shanbhag, with the dissertation "Surrogate Modeling with Gaussian Processes for Molecular Models of Viscoelasticity." During the Ph.D., Pankaj completed a summer internship with Argonne National Laboratory (2020) and taught ISC 2310 and ISC 3313 in the Department of Scientific Computing.
Selected publications
- P. Chouhan, O. Zavala-Romero, M. A. Haseeb, "Evaluating MaxEnt Modeling Strategies for Predicting Suitable Habitats of Invasive Insects Under Climate Change Scenarios," bioRxiv, 2026. doi:10.64898/2026.04.18.719331
- P. Chouhan, S. Shanbhag, "Surrogate Modeling with Gaussian Processes for an Inverse Problem in Polymer Dynamics," International Journal of Computational Methods, 2022. doi:10.1142/S0219876221430039
- P. Chouhan, S. Shanbhag, "Surrogate Modeling of Sparse Functional Data Obtained from Molecular Models of Polymer Viscoelasticity," SSRN preprint, 2024. doi:10.2139/ssrn.4853898
Software and methods
Gaussian process surrogate models, inverse problems, species distribution modeling (MaxEnt), Python, and climate-scenario data.