Davide Corsi

Postdoctoral Research Associate

 
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📍 Irvine, CA, USA

I am a Postdoctoral Researcher at University of California: Irvine, in the Intelligent Dynamics Lab under the supervision of Prof. Roy Fox. Previously, I worked as a visiting researcher under the supervision of Prof. Guy Katz at the Hebrew University of Jerusalem. I obtained my PhD at the University of Verona advised by Prof. Alessandro Farinelli.

My research interests centers on advancing Deep Reinforcement Learning (DRL) for robotics, with a focus on creating safe and reliable systems in critical settings. I tackle this from two sides: safe training through constrained reinforcement learning and validation with formal verification of neural networks. Lately, I’ve also been diving into model-based RL and world modeling —- working toward systems that can not only react but also predict what’s next. Merging theory with real-world robotic challenges is key to my approach, aiming to push boundaries in practical, forward-looking AI. For more information on my research activity, you can visit the publications page.

Places (📍) :
  • 🇺🇸 University of California: Irvine, United States
  • 🇮🇱 The Hebrew University of Jerusalem, Israel
  • 🇮🇹 University of Verona, Italy


News 📢

2024 September
  • The result of my collaboration with the Hebrew University of Jerusalem has been accepted at ICONIP 2024, we are excited to present our new paper Enforcing Specific Behaviours via Constrained DRL and Scenario-Based Programming! 🚀
July
  • Excited to share that my first work at the University of California: Irvine has been accepted in RLC 2024 😍. What an amazing collaboration with colleagues from all over the world Verification-Guided Shielding for Deep Reinforcement Learning!
January
  • Start of a new job at the University of California: Irvine in the Intelligent Dynamics Lab headed by Prof. Roy Fox. Really excited about this new adventure! 🇺🇸
  • Delight to share that our new paper “Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees” has been accepted at AAAI 2024 ✈️.
2023 July
  • Our paper “Formal Explainability of DNN-Based Reactive Systems” has been accepted at FMCAD 2023 😍.
June
  • Our paper “Constrained Reinforcement Learning and Formal Verification for Safe Colonoscopy Navigation” has been accepted at IROS 2023 🤖.
May April
  • Our paper “The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks” has been accepted at IJCAI 2023 (15% acceptance rate) 🤩.
January
  • Our paper “Verifying Learning-Based Robotic Navigation Systems” in collaboration with The Katz Lab has been accepted at ETAPS TACAS 2023 🚀.
2022 September
  • As a result of the research visit at the Hebrew University of Jerusalem, we submitted the papers “Verifying Learning-Based Robotic Navigation Systems” and “Constrained Reinforcement Learning for Robotics via Scenario-Based Programming” at two international conferences.
February January
  • Our paper “Exploring Safer Behaviors for Deep Reinforcement Learning” has been accepted at AAAI 2022 (15% acceptance rate) 🤩.
2021 June
  • Our two papers “Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation” and “Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery” have been accepted at IROS 2021 🤖.
May
  • Proud to share that my first main author paper “Formal Verification of Neural Networks for Safety-Critical Tasks in Deep Reinforcement Learning” has been accepted at UAI 2021 😍.
  • Our paper “Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning” has been accepted at ICLR 2021.


Selected publications 📚

  1. RLC
    Davide Corsi, Guy Amir, Andoni Rodriguez, Cesar Sanchez, Guy Katz, and Roy Fox
    In The 1st Reinforcement Learning Conference, 2024
  2. TACAS
    Guy Amir*, Davide Corsi*, Raz Yerushalmi, Luca Marzari, Alessandro Farinelli, David Harel, and Guy Katz
    In Tools and Algorithms for the Construction and Analysis of Systems, 2023
  3. IROS
    Ameya Pore*, Davide Corsi*, Enrico Marchesini*, Diego Dall’Alba, Alicia Casals, Alessandro Farinelli, and Paolo Fiorini
    In IEEE International Conference on Intelligent Robots and Systems, 2021
  4. UAI
    Davide Corsi, Enrico Marchesini, and Alessandro Farinelli
    In The 37th Conference on Uncertainty in Artificial Intelligence, 2021