Science Spotlight: Machine Learning

#Communications #Robotics #Neuromorphism #ML

We will have three different views on Machine learning research concerning different fields in electrical engineering: Communication, Robotics, and Hardware.

Detailed announcements of the event content will be available at


  Date and Time




  • Date: 20 Mar 2023
  • Time: 04:00 PM to 07:00 PM
  • All times are (UTC+01:00) Berlin
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  • Institut für Nachrichtentechnik (CEL)
  • Hertzstraße 16
  • Karlsruhe, Baden-Wurttemberg
  • Germany
  • Building: 06.45
  • Room Number: 213/214

  • Contact Event Host
  • Starts 24 February 2023 03:30 PM
  • Ends 20 March 2023 10:00 AM
  • All times are (UTC+01:00) Berlin
  • No Admission Charge


Tim O'Shea


AI-Native Wireless: Transforming Wireless Design with Deep Learning

Over the past decade, deep learning has revolutionized signal processing in fields like speech, language, and vision. But it's also transforming the world of wireless signal transmission quickly. In this talk, we'll explore how data-driven approaches are used to design machine learning-based radio signal detection, identification, and localization. We'll also discuss how machine learning is being used to create signal transmitters, receivers, and encodings for wireless signals. This exciting area of research has already yielded some impressive prototypes and results and is sure to play a significant role in the future of OpenRAN 5G, 5G Advanced, and 6G wireless systems. Join us to learn more about the software challenges and research trends in this field, and how AI-native communications create disruption.


Meet Tim O'Shea - CTO and Co-Founder at DeepSig Inc, and a Research Assistant Professor at Virginia Tech. He's passionate about using machine learning and data-driven approaches to improve wireless physical layer performance and intelligence. With previous experience at wireless startups Hawkeye 360 and Federated Wireless, and as an R&D engineer with USG and Cisco Systems, Tim has authored over 100 academic works and patents in this field. His involvement in IEEE COMSOC, IEEE MLC ETI, Next-G Alliance, and OpenRAN initiatives highlights his involvement in accelerating adoption of AI-driven communication systems technology.

Prof. Dr. Gerhard Neumann of Karlsruhe Institute of Technology


Policy Learning for Robotics