CV

Education

• B.S. in Telecommunications Engineering, Beijing University of Posts and Telecommunications (BUPT), 2014 ～ 2018
• M.E. in Systems and Information Engineering, University of Virginia (UVa), 2018 ～ 2019
• Ph.D in Systems and Information Engineering, University of Virginia (UVa), 2020 ～ Present

Experience

• Research Assistant:
  • Human-AI Technology Lab (HAI) Lab, University of Virginia, Spring 2020 ~ Present
• Teaching Assistant:
  • SYS 4581/6581: AI for Social Good, Fall 2020
  • SYS 2202: Data and Information Engineering, Spring 2022

Areas

Ubiquitous and mobile computing, Time series model, Machine learning, Deep learning, Smart health.

Published Papers

• Runze Yan, Xinwen Liu, Janine Dutcher, Michael Tumminia, Daniella Villalba, Sheldon Cohen, David Creswell et al. “A Computational Framework for Modeling Biobehavioral Rhythms from Mobile and Wearable Data Streams.” ACM Transactions on Intelligent Systems and Technology (TIST) 13, no. 3 (2022): 1-27.
• Runze Yan, Whitney R. Ringwald, Julio Vega, Madeline Kehl, Sang Won Bae, Anind K. Dey, Carissa A. Low, Aidan GC Wright, and Afsaneh Doryab. “Exploratory machine learning modeling of adaptive and maladaptive personality traits from passively sensed behavior.” Future Generation Computer Systems (2022).
• Runze Yan, and Afsaneh Doryab. “Towards a Computational Framework for Automated Discovery and Modeling of Biological Rhythms from Wearable Data Streams.” In Proceedings of SAI Intelligent Systems Conference, pp. 643-661. Springer, Cham, 2021.
• Cai Mingyi, Runze Yan, and Afsaneh Doryab. “Daily Trajectory Prediction Using Temporal Frequent Pattern Tree.” In Proceedings of Sixth International Congress on Information and Communication Technology, pp. 333-343. Springer, Singapore, 2022.
• Nikseresht Fateme, Runze Yan, Rachel Lew, Yingzheng Liu, Rose M. Sebastian, and Afsaneh Doryab. “Detection of Racial Bias from Physiological Responses.” In International Conference on Applied Human Factors and Ergonomics, pp. 59-66. Springer, Cham, 2021.

Preprint

• Runze Yan, Matthew Landers, and Afsaneh Doryab. “Transferable Convolutional Neural Wavelet Transform for Granular and Interpretable Behavior Modeling.” (Submitted, under review).
• Runze Yan, Xinwen Liu, Janine Dutcher, Michael Tumminia, Daniella Villalba, Sheldon Cohen, David Creswell et al. “Identifying Links between Productivity and Biobehavioral Rhythms Modeled from Multimodal Sensor Streams.” (Submitted, under review).
• Runze Yan, Matthew Landers, and Afsaneh Doryab. “Similarity Measurement of Cyclic Multimodal Mobile Time Series Data with Case Studies in Biobehavioral Rhythms.” (Submitted, under review).
• Jingyi Gao, Runze Yan, and Afsaneh Doryab. “TrFHB: Transformer-Based Multi-Modal Cyclic Time Series Forecasting for Human Behavior.” (Submitted, under review).

Patent

• Afsaneh Doryab, Runze Yan, and Xinwen Liu. “System, Method and Computer Readable Medium for Modeling Biobehavioral Rhythms from Mobile and Wearable Data Streams.” U.S. Patent Application No. 17/398,097.

Related Courses

• SYS 6582 Reinforcement Learning
• STAT5330 Data Mining
• SYS 6021 Statistical Modeling
• DS6559 Bayesian Machine Learning
• CS 6501 Text Mining
• SYS 6003 Optimization Models & Method

Skills

• Machine Learning Techniques: Sensor Signal Processing, Multimodal Time-Series Analysis, Image Processing, Statistical Model, Deep Learning Model, Transfer Learning Model, Reinforcement Learning Model
• Programming Languages: Python (Sklearn, Tensorflow, Pytorch, Keras, NumPy, SciPy, Pandas, Seaborn, NLTK), R, Java, SQL
• Database: MySQL
• Cloud: Amazon AWS (Computing Services, Storage Services, Database Services)