Michele Lora

Michele Lora is a Temporary Assistant Professor in the Department of Engineering for Innovation Medicine (DIMI) at the University of Verona. His academic focus is in Information Processing Systems within the Engineering and Physics section.

• Position: Temporary Assistant Professor
• Academic Sector: IINF-05/A - Information Processing Systems
• Research Sectors: PE6_1 (Computer architecture, embedded systems), PE6_2 (Distributed systems, cyber-physical systems), PE7_3 (Simulation engineering)
• Office: Ca' Vignal 2, Floor 1, Room 69
• Telephone: 0458027847

Dr. Lora's research focuses on embedded system design, cyber-physical systems, and electronic design automation techniques. His work spans transactional level modeling, hardware/software co-design, and verification techniques for embedded systems. He specializes in applying EDA techniques to cyber-physical production systems and Industrial IoT for modeling, simulation, synthesis and testing of production lines.

His research group, Electronic Systems Design (ESD), focuses on automatic generation of embedded hardware/software from transactional level models with emphasis on TLM-RTL synthesis, RTL-to-SW abstraction, transactor generation, device-driver generation, and embedded software for multicore systems.

Dr. Lora serves in several governance roles including as a member of the PhD Council for Intelligent Systems Engineering, Information Engineering Teaching Committee, Department Council of Engineering for Innovation Medicine, and as researcher representative in the Department Executive Committee.

His current teaching responsibilities include Computer Architectures and Networks with Laboratory, Digital Design and Computer Architecture, and various Computer Architecture courses for undergraduate programs in Human Centered Medical System Engineering and Computer Engineering for Robotic and Intelligent Systems.

Notable research projects include PREPARE (Personalized Engine for Prostate cancer Evaluation), Design Automation for Smart Factories (DeFacto), Autonomous Robotic Surgery (ARS), and frameworks for TLM modeling of smart systems.