Maximilian Egger
Doctoral Researcher
Institute for Communications Engineering
Technical University of Munich
Theresienstr. 90, Building N4, Room 3416
80333 Munich
Phone: +49 89 289 29052
Email: maximilian.egger@tum.de
Recent News:
April 2023: Our paper Hide and Seek: Using Occlusion Techniques for Side-Channel Leakage Attribution in CNNs was accepted for presentation at Artificial Intelligence in Hardware Security Workshop 2023 in Tokyo.
April 2023: Our four papers were accepted to be presented at International Symposium on Information Theory (ISIT) 2023 in Teipei. Details will follow.
March 2023: Awarded DAAD Scholarship for Research Stay at Imperial College London, Great Britain.
March 2023: Co-Organizer of the Joint Workshop on Communications and Coding 2023 in Garmisch, Germany.
October 2022: Elected as doctoral representative for the Department of Computer Engineering and the TUM School of Computation, Information and Technology.
August 2022: Our paper Efficient Private Storage of Sparse Machine Learning Data was presented at Information Theory Workshop (ITW) 2022 in Mumbai.
August 2022: Main organizer of TUM ICE Workshop 2022 in Raitenhaslach, Germany.
Short Biography:
Since February 2023: Three-Months Research Stay with Prof. Dr. Deniz Gündüz at Imperial College London, Great Britain.
Since January 2022: Doctoral Researcher at the Institute for Communications Engineering under supervision of Prof. Dr.-Ing. Antonia Wachter-Zeh
February 2022: Master of Science degree in Electrical Engineering and Information Technology from the Technical University of Munich with high distinction (final grade: 1.0)
February 2020: Bachelor of Engineering degree in Electrical Engineering from University of Applied Sciences with high distinction (final grade: 1.0)
January 2019: Successfully completed professional education as electronics technician for industrial systems with 99 of 100 reachable points
September 2015 - February 2020: Dual Studies (bachelors combined with apprenticeship and multiple temporary engineering positions) at Hilti AG, Kaufering, Germany
Research Interests:
Distributed Machine Learning
Efficiency in distributed matrix multiplication and (stochastic) gradient descent
Privacy preserving coded distributed computing and federated learning
Security in decentralized learning
Awards:
March 2023: DAAD Scholarship for Research Stay at Imperial College London.
November 2020: VDE Award Bavaria 2020.
September 2019: Best vocational qualification 2019 - Chamber of Industry and Commerce (IHK) of Munich and Upper Bavaria.
March 2019 - December 2021: Scholarship recipient of the "Studienstiftung des deutschen Volkes" (German Academic Scholarship Foundation).
November 2018: Participant at the gP Primus promotion program of the University of Applied Sciences in Augsburg.