Welcome to my research page!

Currently, my research is themed around three major projects:

1) Data-Driven Modeling of Complex Systems

This has always been my passion: developing methods and algorithms to uncover the governing dynamics of complex systems. My work spans various applications, including understanding complex flow patterns, deriving coherence from video data, and designing a causality-informed machine-learning approach.

2) Complex Networks: Causality, Collective Behavior, and Synchronization

My research focuses on causality inference, network coupling structure recovery, discovering leadership structures, and controlling the synchronization of coupled networks.

3) Toward Trustworthy Machine Learning and Data Science

You know the case when your ML model fails after deployment or when you try all standard ways (and all Python’s ready-to-use code libraries 🙂 ) to create your deep learning model, but it still does horrible work? That’s when you ask me. My goal is to ensure systems and algorithms are reliable and trustworthy.

If you ever find yourself engaged in a discussion or presentation that sparks my interest (hint: mention an unsolved problem), you might witness my curiosity in action. I dive deep—really deep—into subjects that intrigue me, sometimes to the point of dreaming about them!

Feel free to reach out if you share similar interests or if you’d just like to chat about the wonders of complex systems and data science.

Research Projects and Grants:

[2023 – 2025] Cooperative Research and Development Agreement (CRADA) with the Air Force Research Laboratory (AFRL), In support of the project: “Geometric Information Theory and Causation Inference.
[2024 – 2025] Embry-Riddle Aeronautical University (ERAU), FIRST: Faculty Innovative Research in Science and Technology Program, Embry-Riddle Aeronautical University (ERAU), in support of the development of Community Detection and Clustering Algorithm using Boltzmann-Shannon Interaction Entropy.
[2024] Air Force Research Laboratory (AFRL), Griffiss Institute, Visiting Faculty Research Program (VFRP). In support of the project: Synchronization, Harmonizing Genes, and the Dynamical Systems Language Model.
[2023 – 2024] National Science Foundation (NSF), EAGER: North American Monsoon Prediction Using Causality Informed Machine Learning. As a Co-PI with Christopher Hennon (PI), Curtis James (Co-PI), and Ronny Schroeder (Co-PI).
[2024] Innovative Teaching Grant (ITG), Center of Teaching and Learning Excellence (CTLE), Embry-Riddle Aeronautical University (ERAU), in support of the development of a Data-Driven Approach in Teaching Calculus
[2022] Air Force Research Laboratory (AFRL), Griffiss Institute, Visiting Faculty Research Program (VFRP). In support of the project: Spectral Hierarchy Measure using Geometric Partition Entropy.