I am a is a Postdoctoral Research Associate in Department of Computer Science, Dartmouth College, working with Prof. Andrew Campbell. Previously, I received my Ph.D. in Computer Science at University of Cambridge, advised by Prof. Cecilia Mascolo.
My research focuses on the development of multisensory AI systems to enhance healthcare applications. I specialize in creating generalizable, deep learning models that integrate multiple mobile and wearables signals, such as EEG, ECG, and PPG, to monitor and improve well-being.
🔥 News
- 2025.05: Invited as the Web Chair of ACM MobiSys’26.
- 2024.10: I joined MSRA-shanghai as a intern mentored by Prof. Lili Qiu.
Publications
ArxivBeyond Hearing: Learning Task-agnostic ExG Representations from Earphones via Physiology-informed Tokenization, Hyungjun Yoon, Seungjoo Lee, Yu Yvonne Wu, Xiaomeng Chen, et al. (* equal contribution)NeurIPS 2024Towards open respiratory acoustic foundation models: Pretraining and benchmarking, Yuwei Zhang, Tong Xia, Jing Han , Yu Yvonne Wu, Georgios Rizos, et al.CIKM 2024StatioCL: Contrastive Learning for Time Series via Non-Stationary and Temporal Contrast, Yu Wu, Ting Dang, Dimitris Spathis, Hong Jia, Cecilia MascoloMLHC 2023Udama: Unsupervised domain adaptation through multi-discriminator adversarial training with noisy labels improves cardio-fitness prediction, Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas I Gonzales, Soren Brage, Nicholas Wareham, Cecilia MascoloNPJ digital medicineLongitudinal cardio-respiratory fitness prediction through wearables in free-living environments, Dimitris Spathis, Ignacio Perez-Pozuelo, Tomas I Gonzales, Yu Wu, Soren Brage, Nicholas Wareham, Cecilia Mascolo
💬 Invited Talks
- 2025.11, Towards Accessible, Effective, and Trustworthy Human-Centered Digital Healthcare System, University of Melbourne
- 2025.04, Generalizable Representation Learning for Time-Series in Mobile Health:Advancements and Applications, Singapore Management University