Event announcement as pdf-Download (https://tu-dresden.de/mn/phys ik/ressourcen/dateien/physikalisches-kolloquium/2026-06-16-Phys_Kolloq-DiV entra-SoSe2026.pdf).
Abstract: MemComputing is a new physics-based approach to computation that employs memory (time non-lo cality) to both process and store information on the same physical locatio n. After a brief introduction to this computing paradigm and the physics p rinciples behind it\, I will discuss how it can be utilized in the field o f Machine Learning\, by showing efficient supervised and unsupervised trai ning of neural networks\, demonstrating its advantages over traditional me thods and its usefulness in several science and engineering applications.< /p>
Short bio: Massimiliano Di Ventra obtained his un dergraduate degree in Physics summa cum laude from the University of Tries te (Italy) in 1991 and did his PhD studies at the Swiss Federal Institute of Technology in Lausanne in 1993-1997. Since 2004\, he is a professor of Physics at the University of California\, San Diego. Di Ventra has worked on a variety of topics in condensed matter physics such as the theory of q uantum transport in nanoscale and atomic systems\, non-equilibrium statist ical mechanics\, polymer dynamics/DNA sequencing in nanopores\, and memory effects in nanostructures. Recently\, he has introduced the MemComputing paradigm of computation. He has been invited to deliver more than 350 talk s worldwide on these topics including 20 plenary/keynote presentations. He has published more than 300 papers in refereed journals\, 5 textbooks\, a nd has 12 granted patents (5 US\, 7 foreign). He is a fellow of the Americ an Association for the Advancement of Science\, the American Physical Soci ety\, the Institute of Physics\, the IEEE\, a member of the National Acade my of Inventors and of Academia Europaea. In 2018 he was named Highly Cite d Researcher by Clarivate Analytics\; he is the recipient of the 2024 Humb oldt Research Award\, the 2020 Feynman Prize for theory in Nanotechnology\ , and is a 2022-2023 IEEE Nanotechnology Council Distinguished Lecturer. H e is the co-founder of MemComputing\, Inc. (http://memcpu.com/).