Alberto De Marchi

Alberto De Marchi is a Research Associate at the Institute of Applied Mathematics and Scientific Computing at Universität der Bundeswehr München (UniBw M) in Germany. He holds a doctoral degree (Dr.rer.nat.) in Applied Mathematics from UniBw M (2021), an M.Sc. in Mechatronics Engineering (2016), and a B.Sc. in Industrial Engineering (2014) from the University of Trento (UniTn) in Italy. In Fall 2022, he was a Visiting Research Associate with Ryan Loxton at Curtin University, Australia.

• Education
  • Dr.rer.nat., Applied Mathematics, UniBw M (2021)
  • M.Sc., Mechatronics Engineering, UniTn (2016)
  • B.Sc., Industrial Engineering, UniTn (2014)

His research spans computational optimization, mathematical modeling, numerical analysis, and control systems, with a focus on developing robust numerical optimization tools. Recent work includes applications in IoT digital twins, blockchain-based anonymity frameworks, and hybrid optimal control methods.

His 2025–2023 publications emphasize nonlinear and mixed-integer optimization techniques, constrained composite optimization, and advanced algorithms for control systems. These works explore topics like augmented Lagrangian methods, proximal gradient approaches, collision avoidance, and blockchain ethics.

• Scientific Awards
  • COAP 2022 Best Paper Prize

Alberto collaborates internationally and is intellectually curious about interdisciplinary topics, including the philosophy of mind and literature.