Working on AI Security Research and Vulnerability Response, with a focus on Agentic Security.

Worked on Decentralized Machine Learning for my Ph.D. at EPFL as part of the Doctoral Program in Computer and Communication Sciences (EDIC).

Designed deterministic security guardrails for autonomous AI agents.

Designed and investigated infrastructure for autonomous collaborative agentic AI.

Refactored Fixed Data Table 2 Resize and Reorder functionalities into plugins to make the React-JS based library modular, more customizable and maintainable.

Received Full-Time Offer for the Member-Technical profile on the basis of excellent performance during the internship.

Implemented methods to perform gradient-based attack and adversary transfer on character-based Deep Neural Networks for malicious DGA generated domain names by emulating and inverting the non-differentiable embedding layer.

Used Iterative adversarial training to improve the robustness of the classifier using adversaries generated from the gradient based attacks.

Formulated the scheduling of a freight train in the german railway network as a satisfiability problem in propositional logic and implemented the solution using Z3 Solver.

Optimized the various steps of the problem formulation to reduce the problem blow-up from quadratic to linear and improved the feasibility of the approach in real-life railway network.