COPRA: Conditional Parameter Adaptation with Reinforcement Learning for Video Anomaly Detection
Annual Conference on Neural Information Processing Systems, 2026.
Ph.D. Student · Computer Science & Software Engineering
Darryl Cherian Jacob
I work at the intersection of reinforcement learning and explainable systems, with a focus on improving reasoning—latent or verbalized—through independent exploration.
Selected Work
Publications
Quantum-Inspired RF Pulse Optimization
Presented at 27th Annual Meeting of International Society for Magnetic Resonance in Medicine.
Experience
Industry & Research
Present
Ph.D. Student, Auburn University
Advisor: Dr. Pan He
Research focused on machine learning, explainability, and intelligent systems.
Aug 2023
Graduate R&D Intern, Southwest Research Institute
Created traffic simulation systems for the U.S. EPA Energy Efficient Mobility Systems program and trained reinforcement learning agents for urban traffic control.
Aug 2022
Technical Program Manager, Microsoft
Led privacy and transparency initiatives across Windows experiences, Azure DevOps KPIs, and compliance work for age-appropriate design requirements.
Jul 2019
KBR Intern, NASA Ames Research Center
Research Advisor: Dr. Salvatore Mandrà
Deployed physics-based optimization solvers on Linux HPC resources and built a Node.js interface for quantum optimization workflows.
Jul 2018
AI and Research Intern, Microsoft
Developed high-performance C++ simulation tools for magnetic resonance fingerprinting and presented work with Case Western Reserve University at Microsoft Build.
May 2020
Research Assistant, Texas A&M
Research Advisor: Dr. Helmut G. Katzgraber
Undergraduate Thesis Advisor: Dr. Fang Song
Worked with the Computational and Data Intensive Physics Group on MCMC optimization, HPC workflows, and sampling algorithms.
Education
Auburn University
Ph.D. Computer Science and Software Engineering · 2024—Present
Georgia Institute of Technology
M.S. Computer Science, Machine Learning · 2024
Texas A&M University
B.S. Computer Science, Minor in Mathematics · 2020
Teaching
CSE 6740 · Data Analysis
Georgia Tech · taught online learning, regret, generalization risk, and exponential weights.
MATH 442 · Mathematical Modeling
Texas A&M · taught ODE modeling, UNIX, Git, and stochastic modeling projects.
Skills & Methods
Machine learning, reinforcement learning, optimization, high-performance computing, Python, C++, Node.js, Docker, data analysis, simulation, and research communication.
Contact
Let's connect.
I'm always open to research conversations, collaborations, and opportunities related to machine learning, explainable systems, reinforcement learning, and applied AI.