Ingrid Moerman received her degree in Electrical Engineering (1987) and the Ph.D. degree (1992) from the Ghent University, where she became a part-time professor in 2000. She is a staff member at IDLab, a core research group of imec with research activities embedded in Ghent University and University of Antwerp. Ingrid Moerman is coordinating the research activities on mobile and wireless networking, and she is leading a research team of more than 30 members at Ghent University. Her main research interests include: collaborative and cooperative networks, intelligent cognitive radio networks, real-time software defined radio, flexible hardware/software architectures for radio/network control and management, Internet of Things, Low Power Wide Area Networks (LPWAN), High-density wireless access networks, Next generation wireless networks, and experimentally-supported research. Ingrid Moerman has a longstanding experience in running and coordinating national and EU research funded projects. At the European level, Ingrid Moerman is in particular very active in FP7/H2020, where she has coordinated and is coordinating several FP7/H2020 projects (CREW, WiSHFUL, eWINE, ORCA).
Ingrid Moerman has received 15 awards and prizes during her career, of which 9 best paper awards, 2 prizes awarded by FWO (Research Foundation - Flanders), the IMEC Prize of excellence 2001, one MSc Thesis Award (as promoter), and one best demo/exhibit award (at ICT 2013). The most recent award is a prize of 750 000 USD in the Preliminary Round of the DARPA Spectrum Collaboration Challenge with team SCATTER consisting of researchers from imec-IDLab and Rutgers University (https://www.darpa.mil/news-events/2017-12-21a). In this challenge top teams enhance radio networks with artificial intelligence (AI) that can autonomously collaborate and reason about how to share the increasingly congested electromagnetic (EM) spectrum.
Ingrid Moerman is author or co-author of more than 700 publications in international journals or conference proceedings.
M Kulin, C Fortuna, E De Poorter, D Deschrijver, I Moerman, “Data-driven design of intelligent wireless networks: An overview and tutorial”, 2016, SENSORS, 16 (6), 790
M Kulin, T Kazaz, I Moerman, E De Poorter, “End-to-end learning from spectrum data: A deep learning approach for wireless signal identification in spectrum monitoring applications, 2018, IEEE Access 6, 18484-18501
V Maglogiannis, D Naudts, A Shahid, I Moerman, A Q-learning Scheme for Fair Coexistence Between LTE and Wi-Fi in Unlicensed Spectrum, 2018, IEEE Access 6, 27278 – 27293
FAP de Figueiredo, X Jiao, W Liu, R Mennes, I Jabandžić, I Moerman, A Spectrum Sharing Framework for Intelligent Next Generation Wireless Networks, 2018, IEEE Access, 60704-60735
W Liu , J Santos, X Jiao, F Paisana, LA DaSilva and I Moerman, Using deep learning and radio virtualisation for efficient spectrum sharing among coexisting networks, Crowncom2018, the International Conference on Cognitive Radio Oriented Wireless Networks, 18-10 Sept. 2018, Ghent, Belgium