Jiyao Liu is currently (June 2025) a final-year Ph.D. candidate with the Department of Computer and Information Sciences at Temple University, advised by Dr. Yu Wang.

His research mainly focuses on future networking systems, especially quantum networking, distributed quantum computing, network foundation models, and distributed machine learning. His work at Temple University earned him two Outstanding Research Assistant Awards from the department and college. In Fall 2023, he interned at Toyota NA, delivered two projects within 3.5 months and received an Exceeded rating. Notably, he designed a transformer-based model for electric vehicle battery prediction, achieving ∼10% MAPE—outperforming Tesla’s deployed service.

Prior to his Ph.D. study, he obtained his B.Eng. in Information Security from North China University of Technology in Jun. 2020. While pursuing his Ph.D., he also earned M.S. in Computer Science from Temple University in 2024.

News

04-2025 Our paper on joint swapping and purification optimization in quantum networks is accepted by IWQoS 2025!
02-2025 Our paper on network topology and qubit allocation co-optimization for distributed quantum computing is accepted by QCNC 2025!
12-2024 I’m thrilled to receive the 2024 Outstanding Graduate Research Assistant Award from our College of Science and Technology!
10-2024 Our paper on topology design for quantum networks was accepted by SECON 2024!
10-2024 Our paper on group-based federated learning was accepted by Transactions on Cloud Computing!
08-2024 Our paper on federated learning and blockchain was accepted by VTC2024-Fall!
05-2024 Our paper on hybrid quantum-classic optimization was accepted by ICCCN 2024!
05-2024 Our paper on satellite-based entanglement distribution was accepted by IEEE Network!
04-2024 Glad to receive the CIS Outstanding Research Assistant Award (one from the whole department)!
12-2023 Finished my internship with Exceeded rating!
08-2023 Received travel award to Salt Lake City to attend ICPP 2023!
07-2023 Received an internship offer from Toyota InfoTech Labs!
06-2023 Our paper on group-based federated learning was accepted by ICPP 2023!