Hulya Seferoglu
ProfessorDepartment of Electrical and Computer EngineeringUniversity of Illinois Chicago
Contact
Department of ECE (MC 154)1037 SEO, 851 S Morgan St., Chicago, IL, 60607E-mail: hulya{at}uic.eduEmbedded Files
ProfessorDepartment of Electrical and Computer EngineeringUniversity of Illinois Chicago
Biography
Hulya Seferoglu is a Professor in the Electrical and Computer Engineering Department of University of Illinois at Chicago. Before joining University of Illinois at Chicago, she was a Postdoctoral Associate at Massachusetts Institute of Technology. She received her Ph.D. degree in Electrical and Computer Engineering from University of California, Irvine, M.S. degree in Electrical Engineering and Computer Science from Sabanci University, and B.S. degree in Electrical Engineering from Istanbul University. She worked as a summer intern in AT&T Labs Research, Docomo USA Labs, and Microsoft Research, Cambridge. She served as associate editors for IEEE Transactions on Mobile Computing (2022-2024) and IEEE/ACM Transactions on Networking (2017–2021). She received the NSF CAREER award in 2020. Her CV is here.
Recent News
10/13/2025, Our work on "Differentiated Aggregation to Improve Generalization in Federated Learning" is accepted by Transactions on Machine Learning Research (TMLR).
08/04/2025, Our work on "Efficient and Privacy-Preserving Binary Dot Product via Multi-Party Computation" is accepted by Allerton 2025.
07/08/2025, Our work on "Model-Distributed Inference for Large Language Models at the Edge" received the best paper award in IEEE LANMAN.
05/26/2025, Fatemeh will present our work on "Privacy-Preserving Hierarchical Model-Distributed Inference" in the 2025 Midwest Machine Learning Symposium (MMLS).
05/04/2025, Our work on "Model-Distributed Inference for Large Language Models at the Edge" is accepted by IEEE LANMAN, July 2025.
02/09/2025, Our work on "Priority-Aware Model-Distributed Inference at Edge Networks" is accepted by IEEE ICMLCN, May 2025.
12/15/2024, Our work on "Differentiated Aggregation to Improve Generalization in Federated Learning" is accepted by SEAS and FLUID workshops of AAAI 2025.
Page updated
Report abuse