News
2026
August 2026 — I joined the University of South Florida as an Assistant Professor in the Department of Industrial and Management Systems Engineering and launched the Learning-enabled Autonomy (LEA) Lab.
June 2026 — Our paper “Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees” was published in TMLR.
May 2026 — My research was featured by Boston University Engineering: “Building Smarter, Safer AI: Vittorio Giammarino’s Research Journey”.
May 2026 — Our paper “Beyond Domain Randomization: Event-Inspired Perception for Visually Robust Adversarial Imitation from Videos” was presented at ICRA 2026.
April 2026 — Our workshop “Hybrid Architectures for Embodied Autonomy: Bridging Learning, Planning, and Control” was accepted to IROS 2026.
April 2026 — Our paper “Goal Reaching with Eikonal-Constrained Hierarchical Quasimetric Reinforcement Learning” was presented at ICLR 2026.
February 2026 — I gave a talk at the University of South Florida entitled “From Control to Reinforcement Learning and Back: Structured Learning for Reliable Autonomy.”
February 2026 — I gave a talk at the University of Central Florida entitled “From Control to Reinforcement Learning and Back: Structured Learning for Reliable Autonomy.”
January 2026 — Our survey “Formal Methods in Robot Policy Learning and Verification: A Survey on Current Techniques and Future Directions” was published in TMLR.
2025
December 2025 — Our papers “Automaton Constrained Q-Learning” and “Physics-informed Value Learner for Offline Goal-Conditioned Reinforcement Learning” were presented at NeurIPS 2025.
November 2025 — I gave a talk at the PEARL Lab, TU Darmstadt entitled “From Data-Driven Control to Physics-Informed RL: Toward Efficient Policy Learning.”
May 2025 — Our paper “Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning” was presented at ICRA 2025.
2024
December 2024 — Our paper “Reinforcement Learning-based Receding Horizon Control using Adaptive Control Barrier Functions for Safety-Critical Systems” was presented at CDC 2024.
December 2024 — Our paper “A Model-Based Approach for Improving Reinforcement Learning Efficiency Leveraging Expert Observations” was presented at CDC 2024.
September 2024 — I joined the Department of Computer Science at Purdue University as a Postdoctoral Research Associate.
September 2024 — Our paper “Adversarial Imitation Learning from Visual Observations using Latent Information” was accepted for publication in TMLR.
July 2024 — I successfully defended my Ph.D. thesis, “On the Use of Expert Data to Imitate Behavior and Accelerate Reinforcement Learning”.