Biography
I am a first year PhD student at the University of California, San Diego (UCSD) in Computer Science and Engineering Department. I am currently a graduate researcher at System Energy Efficiency Lab, where I fortunately have been working with Prof. Tajana Rosing. My research interests are efficient and theoretically founded machine learning algorithms applicable in practical settings. Prior to my PhD, I received my B.S. degree in Computer Science also from UCSD in 2023. Feel free to contact me via Email: quzhao@ucsd.edu
For more details, see my CV.
Research Interest
- Machine learning, Kernel method.
- Novel learning paradigms: Online, Few-shot, Federated, Continual, Unsupervised, Multimodal Learning.
- Efficient neuromorphic computing methods: Vector Symbolic Architecture/Hyperdimensional Computing.
News
- (Jan 2025) One paper accepted by SenSys 2025.
- (Dec 2024) One paper accepted by AAAI 2025.
- (Aug 2024) I joined UCSD CSE department for my PhD.
- (Dec 2023) One paper accepted by DATE 2024.
- (Oct 2023) One workshop paper accepted by MLNCP @ NeurIPS 2024.
- (Jun 2023) I won the UCSD CSE 2023 Undergraduate Excellence in Research award.
Publications
.Le Zhang^, Quanling Zhao^ (equal contribution), Run Wang, Shirley Bian, Onat Gungor, Flavio Ponzina, and Tajana Rosing, "Offload Rethinking by Cloud Assistance for Efficient Environmental Sound Recognition on LPWANs" - ACM Conference on Embedded Networked Sensor Systems (SenSys), 2025 [pdf] [code] [link]
Quanling Zhao, Anthony Thomas, Ari Brin, Xiaofan Yu, Tajana Rosing , "Bridging the Gap between Hyperdimensional Computing and Kernel Methods via the Nyström Method" - AAAI Conference on Artificial Intelligence (AAAI), 2025 [pdf] [code] [link]
Quanling Zhao, Xiaofan Yu, Shengfan Hu, Tajana Rosing, "MultimodalHD: Federated Learning Over Heterogeneous Sensor Modalities using Hyperdimensional Computing" - Design, Automation, and Test in Europe (DATE), 2024 [pdf] [code] [link]
Xiaofan Yu, Ludmila Cherkasova, Harsh Vardhan, Quanling Zhao, Emily Ekaireb, Xiyuan Zhang, Arya Mazumdar, Tajana Rosing, "Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks" - ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI), 2023 [pdf] [code] [link]