WiMNet PhD student Tingjun Chen has been selected as one of 200 young researchers from around the world to attend this year’s Heidelberg Laureate Forum, which took place Sept. 23–28, in Heidelberg, Germany. Tingjun’s research interests include PHY/MAC layer algorithms, optimization, and system implementation in Internet-of- Things (IoT), energy-harvesting networks, full-duplex wireless, and mmWave and 5G networks.
Attendees at the highly selective Heidelberg Laureate Forum have the opportunity to meet and interact with recipients of the most prestigious awards in mathematics and computer science, including the Abel Prize, the Fields Medal, the ACM A.M. Turing Award, and the ACM Prize in Computing. The one-week event combines scientific, social, and public outreach activities.
“Besides meeting with brilliant researchers and scholars,” says Tingjun, “I view this as an opportunity to see what’s going on in research in other outstanding groups in computer science and math—some of which I expect to be familiar with, and some not at all. In particular, I’m interested in learning about advanced algorithms for efficiently solving complex large-scale problems that can be applied to the next-generation wireless systems and networks.”
At the Heidelberg Laureate Forum, Tingjun presented a poster on his work on throughput maximization in ultra-low-power networks. This work was performed jointly with Professors Javad Ghaderi, Dan Rubenstein, and Gil Zussman. Tingjun also shared his thoughts on IoT and 5G networks during an interview on “What is the most exciting thing in computing in the next 10 years”.
Tingjun received his BEng in electronic engineering from Tsinghua University, Beijing, China, in 2014 and his MS in electrical engineering from Columbia in 2015. He has received a number of awards, including the Wei Family Private Foundation Fellowship, the Columbia EE Armstrong Memorial Award and Millman Outstanding Teaching Assistant Award, the Columbia Engineering Oscar and Verna Byron Fellowship, as well as the ACM CoNEXT 2016 Best Paper Award.
Original article can be found here.