Sachin Shanbhag, PhD
Dr. Shanbhag works at the interface of soft matter and numerical algorithms. Over the past couple of years, he has started to apply machine learning methods to suitable problems in the area.
Lingjiong Zhu, PhD
Dr. Zhu is a professor and the Thinking Machines Eminent Scholar in Mathematics at FSU. As an applied probabilist, his research focuses on the theoretical study of stochastic algorithms for large-scale sampling and optimization problems in machine learning (AI). His work, which is applied to financial engineering, is published in top venues like NeurIPS and ICML.
Maxim Dulebenets, PhD
Dr. Dulebenet’s research group builds different types of AI-based algorithms (e.g., heuristics, meta-heuristics, hyper-heuristics, hybridized methods, swarm intelligence) for challenging decision problems.
Hristo Chipilski, PhD
Dr. Chipilski is a computational scientist focused on data assimilation for numerical weather prediction. His current research leverages generative AI to develop novel algorithms that improve the accuracy and efficiency of integrating observational data. Broadly interested in atmospheric dynamics, his work is interdisciplinary, spanning algorithmic theory and Earth system modeling.