I am an Assistant Professor of Computer Science & Engineering at Louisiana State University (LSU), with a joint appointment in the LSU Center for Computation & Technology (CCT). I lead two overlapping research thrusts: (1) modern and emerging deep learning—especially transformers and large language models (LLMs)—applied to intelligent sensing and decision support, with emphasis on national security use cases such as intrusion detection, radioactive source search and identification, and other high-stakes time-series problems; and (2) neuromorphic computing algorithms (spiking neural networks), spanning both applied work on ultra-low-power, spike-native models for edge sensing and foundational work on training methods, robustness, and design principles for spike-based architectures. I am the lead designer and developer of MikeGPT, LSU’s in-house LLM agent for interacting with the university’s broad data ecosystem. Prior to LSU, I was a staff research data scientist at Oak Ridge National Laboratory (ORNL), where I led applied deep learning and neuromorphic projects for federal sponsors. At LSU, I teach an upper-division course on LLMs and a graduate course on advanced deep learning focused on transformers and emerging architectures. Across my projects, I’m motivated by mission-driven AI that advances capability while approaching the efficiency of biological neural systems.

Research Areas

1. Modern deep learning for intelligent sensing
2. Neuromorphic computing with spiking neural networks
3. LLM Systems

MSc Thesis

A Neuroscience-inspired Approach to Training Spiking Neural Networks

PhD Dissertation

A Datacentric Algorithm for Gamma-ray Radiation Anomaly Detection in Unknown Background Environments