Hello, I am
Han Yu
Machine Learning, Wearable Computing, Mental Health ...
Han Yu
Ph.D. Student @ Rice University, Houston, TX
​
Department of Electrical and Computer Engineering
About
MY BACKGROUND
As a doctoral student in the Department of Electrical and Computer Engineering at Rice University, I am working with Dr. Akane Sano and researching the application of machine learning in the field of human health. Before that, I was a professional master student in electrical engineering at Rice University.
Education
WHAT I’VE LEARNED
2019 – Present
Rice University – Houston, TX; Advisor: Akane Sano
Ph.D., Electrical and Computer Engineering
2017 – 2018
Rice University – Houston, TX; Major: Data Science
M.Eng., Electrical and Computer Engineering
2013 – 2017
University of Electronic Science and Technology of China, Chengdu, China
B.Eng., Electrical Engineering
Experience
WHERE I’VE WORKED
May. 2018–Present
CompWell Research Group @ Rice University,
Research Assistant
May 2021 – Aug 2021
Apple Inc.
PhD Intern, AI/ML in Health Technology
Dec 2016 – May 2017
AV2C Lab @ UESTC,
Research Intern
Publications
WHAT I'VE FINISHED
Yu, H., Yang, H., & Sano, A. (2022). LEAVES: Learning Views for Time-Series Data in Contrastive Learning. arXiv preprint arXiv:2210.07340.
Yang, H., Yu, H., & Sano, A. (2022). Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep Learning. arXiv preprint arXiv:2210.06701.
Zanna, K., Sridhar, K., Yu, H., & Sano, A. (2022). Bias Reducing Multitask Learning on Mental Health Prediction. arXiv preprint arXiv:2208.03621.
Yu, H. & Sano, A. (2022). Semi-Supervised Learning and Data Augmentation in Wearable-based Momentary Stress Detection in the Wild. preprint,
Yang, H., Yu, H., Sridhar, K., Vaessen, T., Myin-Germeys, I., & Sano, A. (2022). More to Less (M2L): Enhanced Health Recognition in the Wild with Reduced Modality of Wearable Sensors. arXiv preprint arXiv:2202.08267.
Yu, H., Vaessen, T., Myin-Germeys, I., & Sano, A. (2021, September). Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the Wild. In 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII) (pp. 1-8). IEEE.
Yu, H., Itoh, A., Sakamoto, R., Shimaoka, M., & Sano, A. (2020, December). Forecasting health and wellbeing for shift workers using job-role based deep neural network. In International Conference on Wireless Mobile Communication and Healthcare (pp. 89-103). Springer, Cham.
Yu, H., & Sano, A. (2020, July). Passive Sensor Data Based Future Mood, Health, and Stress Prediction: User Adaptation Using Deep Learning. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 5884-5887). IEEE.
Li, B., Yu, H., & Sano, A. (2019, September). Toward End-to-end Prediction of Future Wellbeing using Deep Sensor Representation Learning. In 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) (pp. 253-257). IEEE.
Yu, H., Klerman, E. B., Picard, R. W., & Sano, A. (2019, May). Personalized Wellbeing Prediction using Behavioral, Physiological and Weather Data. In 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) (pp. 1-4). IEEE.
Awards
WHAT I'VE ACHIEVED
Rice University IBB Travel Award -- Rice University, Houston, USA
Outstanding Student Award -- UESTC, Chengdu, China
People’s Scholarship of China -- UESTC, Chengdu, China
Interests
OUT OF OFFICE
Cooking
Hiking
Travel
Gaming
Basketball
Reading