Seyedsaeed Razavikia

Seyedsaeed Razavikia is a Ph.D. candidate at the KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Division of Network and Systems Engineering. His work is supervised by Carlo Fischione, with co-supervision by Mairton Barros, and funded by the WASP project.

• B.Sc. and M.Sc. in Electrical Engineering from Iran University of Science and Technology and Sharif University of Technology, respectively.
• Visiting researcher at Imperial College London with Deniz Gündüz in the Information Processing and Communications Lab.

Research interests span machine learning over networks, optimization, statistical signal processing, and communication theory. His work focuses on over-the-air computation, federated learning, and low-rank matrix recovery.

Publications highlight advancements in digital communication, networked machine learning, and signal processing, with applications in massive connectivity and blind demixing.

• Awards:
  • IEEE Sweden VT-COM-IT Best Student Journal Paper Award 2024
  • IEEE Sweden VT-COM-IT Top-5 Student Conference Paper Award 2024
  • Hans Werthén Foundation Visiting Abroad Scholarship
  • Wallenberg AI, Autonomous Systems and Software Program Ph.D. Admission

Collaborations include institutions like Imperial College London and Ericsson Research, with contributions to patents on digital channel computation.