Pierluigi Nuzzo

About

Pierluigi Nuzzo is a researcher whose work sits at the intersection of formal methods, cyber-physical systems, and autonomous robotics. His research focuses on developing mathematically rigorous frameworks for reasoning about complex systems that blend discrete computational logic with continuous physical dynamics — a challenge central to modern autonomous systems design. Nuzzo's most influential contribution is the development of Satisfiability Modulo Convex (SMC) programming, a powerful framework that extends Boolean satisfiability solving to handle convex constraints over real numbers. This work, cited nearly 90 times across multiple publications, has become a foundational tool for hybrid system verification and control synthesis. Building on this, he has made substantial advances in multi-robot motion planning under Linear Temporal Logic (LTL) specifications, producing scalable algorithms capable of handling realistic robot dynamics, safety constraints, and even adversarial conditions like denial-of-service attacks. More recently, Nuzzo has expanded into reinforcement learning for Markov decision processes under formal temporal logic specifications, bridging data-driven and formal approaches to autonomous system control. His CROME framework and contract-based mission specification work further demonstrate his commitment to making formal methods accessible and practical for robotic mission design. Together, his contributions represent a coherent research vision: making autonomous systems provably correct, scalable, and resilient.

Research Focus

Key Achievements

Top Papers

1. 1
   SMC: Satisfiability Modulo Convex Programming

   49 citations · 2018
2. 2
   Linear temporal logic motion planning for teams of underactuated robots using satisfiability modulo convex programming

   48 citations · 2017
3. 3
   SMC

   42 citations · 2017
4. 4
   Scalable lazy SMT-based motion planning

   32 citations · 2016
5. 5
   Model-Free Reinforcement Learning for Optimal Control of Markov Decision Processes Under Signal Temporal Logic Specifications

   11 citations · 2021
6. 6
   Optimal Control of Discounted-Reward Markov Decision Processes Under Linear Temporal Logic Specifications

   8 citations · 2021
7. 7
   DoS-Resilient Multi-Robot Temporal Logic Motion Planning

   8 citations · 2019
8. 8
   CROME: Contract-Based Robotic Mission Specification

   7 citations · 2020
9. 9
   Contract-Based Specification Refinement and Repair for Mission Planning

   5 citations · 2023
10. 10
    Task Assignment, Scheduling, and Motion Planning for Automated Warehouses for Million Product Workloads

    5 citations · 2023

Key Collaborators

Contact & Links