I am a Post-Doctoral researcher in CMU Cylab hosted by Dr. Corina Pasareanu. I graduated with a PhD from the School of Computer Science at Georgia Tech in December 2020. [rmangal@andrew.cmu.edu] [CV] [LinkedIn] [Google Scholar]

Research Interests:
I am interested in developing formal methods for analyzing the correctness and safety of software systems. In recent years, I have focused on Trustworthy Machine Learning , i.e., robustness, safety, and explainability analysis of AI/ML components. Deploying AI in safety-critical applications like autonomous vehicles demands techniques for establishing trust in ML models and I believe that formal methods provide a powerful set of tools to address this trust deficit.

In my past and ongoing research, I have leveraged my formal methods expertise for developing tools and techniques that (i) analyze the robustness of ML models to adversarial perturbations of the data, (ii) repair ML models to ensure their compliance with user-provided safety specifications, (iii) quantify the uncertainty of ML models for risk-aware downstream decision-making, and (iv) automatically extract high-level descriptions explaining the internal behavior of ML models.

Papers:
(* indicates equal contribution)