{"id":2296,"date":"2025-12-17T17:50:11","date_gmt":"2025-12-17T16:50:11","guid":{"rendered":"https:\/\/www.esi.fau.de\/?p=2296"},"modified":"2026-03-20T19:12:05","modified_gmt":"2026-03-20T18:12:05","slug":"best-paper-award-at-ieee-mcsoc-2025","status":"publish","type":"post","link":"https:\/\/www.esi.fau.de\/en\/2025\/12\/17\/best-paper-award-at-ieee-mcsoc-2025\/","title":{"rendered":"Best Paper Award at IEEE MCSOC 2025"},"content":{"rendered":"\n

Pierre-Louis Sixdenier, Mark Deutel, and ESI spokesperson Prof. Dr.-Ing. J\u00fcrgen Teich received the Best Paper Award at this year’s 18th IEEE International Symposium on Embedded Multicore\/Many-Core Systems-On-Chip (MCSOC 2025). The award was given for their paper \u201cEarly-Exit Neural Architecture Search for Energy-Harvesting Edge Computing.\u201d The award was presented during the event (December 15-18, 2025) in Singapore. In their award-winning work, the authors present a simulation-based framework for searching for neural architectures for exploring EE-DNN architectures and an online energy manager that dynamically decides which early exit to choose based on the available energy and the reliability of the EE-NN predictions, while ensuring energy-neutral operation (ENO).<\/p>\n\n\n\n

\"\"