Michele Loreti

About

Michele Loreti is a leading researcher in formal methods for autonomous and collective systems, with a career dedicated to taming the complexity of modern software-intensive environments. His most influential work, "A Formal Approach to Autonomic Systems Programming" (144 citations), establishes foundational linguistic primitives and abstractions for programming systems that can self-manage, adapt, and heal—a cornerstone challenge in autonomic computing. Loreti extends this formal rigor to the physical world through contributions like "Towards a Formal Verification Methodology for Collective Robotic Systems" (30 citations), where he develops techniques to ensure correctness in swarms of autonomous robots. More recently, he has pioneered the formal evaluation of digital twins, introducing statistical model checking with feedback and perturbations to assess their effectiveness in real-time decision-making. His tools, including DT-Stark (2025), operationalize these concepts, enabling engineers to validate that a digital twin can safely direct its physical counterpart. With a career spanning foundational theory to practical verification tools, Loreti’s work empowers developers to build reliable, self-adaptive systems across domains from cloud computing to robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   A Formal Approach to Autonomic Systems Programming

   144 citations · 2014
2. 2
   Towards a Formal Verification Methodology for Collective Robotic Systems

   30 citations · 2012
3. 3
   On Programming and Policing Autonomic Computing Systems

   7 citations · 2014
4. 4
   Evaluating the Effectiveness of Digital Twins Through Statistical Model Checking with Feedback and Perturbations

   5 citations · 2024
5. 5
   DT-Stark: a tool for evaluating the effectiveness of digital twins through feedback and perturbations

   2 citations · 2025

Key Collaborators

Contact & Links