Curriculum Vitae
Raffaele Soloperto, Ph.D.
Lecturer at ETH Zurich / Innovation & Research Manager at Embotech AG
ETH Zurich / Embotech
Zurich, Switzerland
soloperto.raffaele@gmail.com
Bio
Raffaele Soloperto received his Bachelor’s and Master’s degrees in Automation Engineering from the University of Bologna, Italy, in 2014 and 2016, respectively. He earned his Ph.D. in 2022 from the University of Stuttgart, Germany, under the supervision of Prof. Frank Allgower, and in collaboration with the International Max Planck Research School (IMPRS). From 2022 to 2025, he was a Postdoctoral Researcher at the Automatic Control Laboratory, ETH Zürich, Switzerland, in the group of John Lygeros. Since 2025, he has been serving as Innovation Manager at Embotech AG. His research interests include model predictive control and game theory. Raffaele continues to serve as Lecturer for the MSc course “Nonlinear Systems and Control” at ETH Zurich. This website is still in progress.
Expertise
- Control theory for nonlinear systems
- Optimization & model predictive control (MPC)
- Learning-based MPC
- Reinforcement learning for safety-critical systems
- Generative AI for engineering workflows
- Autonomous driving & real-time decision algorithms
Highlights
Course: Nonlinear Systems & Control (MSc)Office hours: On requestPreferred contact: Email
Experience
03.2025 — Present
Innovation & Research Manager
Embotech, Zurich, Switzerland
- Lead strategic AI research and innovation (reinforcement learning, generative AI, and real-time decision algorithms) for safety-critical applications.
- Architect and evaluate AI models and optimization pipelines for autonomous driving.
- Capture and structure intellectual property from invention disclosure to patent filing.
- Secure public and private R&D funding; contribute to the company’s long-term research roadmap.
03.2023 — Present
Lecturer
ETH Zurich, Zurich, Switzerland
- Lecturer of the MSc course “Nonlinear Systems and Control” (~100 students).
- Teaching evaluation: 4.95/5.
11.2022 — 03.2025
Postdoctoral Researcher
ETH Zurich, Zurich, Switzerland
- Developed and analyzed optimization and machine learning algorithms for complex dynamical systems.
- Supervised MSc and PhD students on research projects and publications.
- Contributed to high-impact research with national and international partners.
05.2023 — 09.2024
Consultant in Machine Learning
Client: SBB – CFF – SFF
- Designed and validated ML-based control strategies for large-scale HVAC infrastructures.
- Delivered data-driven optimization improving efficiency and reducing energy use (~3M CHF annual savings).
- Collaborated with engineering teams supporting deployment and performance assessment.
01.2017 — 06.2017
Researcher
EPFL, Lausanne, Switzerland
- Proposed plug-and-play microgrid approaches enabling safe and spontaneous connection of agents (supervised by Prof. Giancarlo Ferrari Trecate).
Education
07.2017 — 10.2022
Ph.D. in Control Theory, Optimization, and Machine Learning
University of Stuttgart, Germany & UC Berkeley, USA
- Grade: Summa cum laude · Thesis: Learning-based Model Predictive Control
10.2014 — 10.2016
MSc in Robotics
University of Bologna, Italy
- Grade: 110/110 cum laude · Thesis at Robotic Systems Lab (RSL), ETH Zürich
10.2010 — 06.2014
BSc in Robotics
University of Bologna, Italy
- Grade: 99/110 · Thesis at TUM (Munich) · Erasmus at NTNU (Norway)
Teaching
2023 — Present
Nonlinear Systems & Control (MSc), ETH Zurich
Course lecturer (~100 students).
2023 — 2024
P&S RoboCup: Learning and Control (BSc), ETH Zurich
Course lecturer.
2018 — 2022
Nonlinear Control (MSc), University of Stuttgart
Course lecturer.
2018 — 2021
Model Predictive Control (MSc), University of Stuttgart
Teaching Assistant
2017 — 2020
Laboratory of Control Theory (BSc), University of Stuttgart
Course lecturer
Publications
- . Author and co-author of journal and conference papers in main venues including IEEE Transactions on Automatic Control, Automatica, and IEEE Control Systems Letters (L-CSS). See Google Scholar for a full list. I also serve as a reviewer for top journals and conferences in control and optimization.
Talks
(Add invited talks / presentations.)
Skills
Programming: MATLAB/Simulink, Python, C++Control & optimization: nonlinear systems, MPC, learning-based controlMachine learning: reinforcement learning, generative AILanguages: Italian (native), English (advanced), German (intermediate)