Henrik Hellström

I am PhD candidate in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, supervised by Carlo Fischione and Viktoria Fodor. Currently, I am residing in California where I am working as a Visiting Student Researcher under Ayfer Özgür. My research interests are physical layer wireless, distributed machine learning, optimization theory, estimation theory, software-defined radio, and industrial communications.

I have a bachelor's degree in Electrical Engineering '16, a master's degree in Information and Network Engineering '18, and a licentiate's degree in Electrical Engineering '22, all from KTH Royal Institute of Technology. Previously, I worked as a temporary contractor for ABB Corporate Research, assisting in the development of a novel PHY-layer protocol for ultra-low latency industrial communications called WirelessHP.

My current research focus is Wireless for Machine Learning, i.e., wireless network protocols that are tailored to support distributed machine learning. Particularly, I focus on over-the-air computation to combine the gradients of deep neural networks by utilizing the superposition property of electromagnetic waves. I also serve as the secretary of the IEEE emerging technology initiative on Machine Learning for Communications (ETI MLC).

Recent News

• October 2023: Our paper titled "Unbiased Over-the-Air Computation via Retransmissions" won the IEEE Sweden VT/COM/IT Best Student Conference Paper Award. 
• September 2023: I have moved to Palo Alto, California to begin my new position as a Visiting Student Researcher at Stanford University. At Stanford, I am working together with Professor Ayfer Özgür.
• August 2023: One of my papers have been nominated for the IEEE Sweden VT/COM/IT Best Student Conference Paper Award.
• July 2023: I have been invited to serve as a Technical Program Committee member for the IEEE International Conference on Communications (ICC).
• June 2023: I have been invited to be the speaker in a webinar session with the IEEE Bangalore Section. The title of the talk is "Exploiting Electromagnetic Interference to Compute Functions in the Air".
• May 2023: I have received a grant from the Ericsson Research Foundation to fund an upcoming research exchange with Dr. Ayfer Özgür at Stanford University.
• April 2023: I have been invited to serve as a Technical Program Committee member for the 2023 Swedish National Computer Networking and Cloud Computing Workshop (SNCNW).
• March 2023: I have been appointed Webmaster of the 2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN). This will be the first edition of the conference.
• January 2023: For the purpose of exploring joint research and education opportunities, I traveled to Chennai, India to participate in the partnership workshop between KTH and IIT Madras.
• November 2022: I successfully defended my Licentiate Thesis titled "Over-the-Air Computation for Machine Learning: Model Aggregation via Retransmissions".
• August 2022: Our latest conference paper got accepted for presentation at the IEEE Global Communications Conference, which will be held in Rio de Janeiro, Brazil in December this year.
• June 2022: Our survey paper got published in NOW Foundations and Trends in Signal Processing "Wireless for Machine Learning: A Survey"
• May 2022: We gave a tutorial titled "Wireless for Machine Learning" at IEEE International Conference on Communications (ICC) Seoul, South Korea
• May 2022: I have been awarded a scholarship from Lindstrands stiftelse with the intent of presenting my work at the IEEE Global Communications Conference 2022 in Rio de Janeiro
• Dec 2021: We gave a tutorial titled "Wireless for Machine Learning" at IEEE GLOBECOM Virtual Conference
• Nov 2021: We released a preprint of our journal paper titled "Over-the-Air Federated Learning with Retransmissions (Extended Version)"
• Oct 2021: I have been appointed secretary of the IEEE Emerging Technology Initiative of Machine Learning for Communications (ETI MLC)
• Sep 2021: We gave a tutorial titled "Wireless for Machine Learning" at IEEE PIMRC Virtual Conference
• Jul 2021: Our paper titled "Over-the-Air Federated Learning with Retransmissions" has been accepted for presentation at SPAWC Lucca, Italy
• Jun 2021: We gave a tutorial titled "Wireless for Machine Learning" at IEEE ICASSP Toronto, Canada
• Nov 2020: Supervised Oscar Olli in his master thesis titled "Big Data in Small Tunnels: Turning Alarms Into Intelligence"
• Sep 2020:We released a preprint of our survey paper titled "Wireless for Machine Learning"
• Jun 2020: Started as a teaching assistant for "EP1200 - Introduction to Computing Systems Engineering"
• May 2020: Supervised Linus Pekkanen and Patrik Johansson for their bachelor thesis titled "Simulating Broadband Analog Aggregation for Federated Learning"
• Dec 2019: Our paper titled "Software-defined wireless communication for industrial control: A realistic approach" got published in IEEE Electronics Magazine
• Sep 2019: Participated in IEEE ComSoc's "Training School on Machine Learning for Communications" in ISEP Paris, France