Dr. Jiaqi (Jackey) Gong
- Associate Professor
Areas of Research
- Artificial Intelligence
- Wearable and Mobile Technology
- Smart and Connected Health
- Human-Centered Computing
- Educational Data Mining
- B.S., Engineering, China University of Geoscience, 2004
- Ph.D., Engineering, Huazhong University of Science and Technology, 2010
The Sensor-Accelerated Intelligent Learning (SAIL) laboratory is founded and led by Dr. Jiaqi Gong starting from 2017. The research lab focuses on the convergence of human and artificial intelligence that spans the area of human-centered computing, cyber-physical systems, and smart and connected health, through inventing, developing, and applying mobile and wearable computing systems to examine and understand the coupled relationship between humans and intelligent systems towards advancing human capabilities: perceptual and cognitive, physical, and virtual. Specifically, the development of the novel framework for the convergence of human and artificial intelligence is crucial to tackling the challenges introduced by the characteristics of large amounts of big heterogeneous data and the new data science problems that arise in applications such as health and education. The research projects build logically on the prior findings and collaborations with interdisciplinary experts, such as Mechanism-Informed Multiscale Modeling and Machine Learning, Wearable and Mobile Technology for Behavior Change Intervention, Multimodal Sensing and Modeling for Human Movement Research, and Actionable Educational Data Mining.
Publications and Patents
- Baglione, Anna N., Mehdi Boukhechba, Laura E. Barnes, Jiaqi Gong, and Kristen J. Wells. “Leveraging Mobile Sensing to Understand and Develop Intervention Strategies to Improve Medication Adherence.” IEEE Pervasive Computing (2020).
- Ma, Rui, Jiaqi Gong, Guocheng Liu, and Qi Hao. “Enabling Cognitive Pyroelectric Infrared Sensing: From Reconfigurable Signal Conditioning to Sensor Mask Design.” IEEE Transactions on Industrial Informatics (2019).
- Jiaqi Gong, Yu Huang, Philip I. Chow, Karl Fua, Matthew S. Gerber, Bethany A. Teachman, and Laura E. Barnes. “Understanding behavioral dynamics of social anxiety among college students through smartphone sensors.” Information Fusion 49 (2019): 57-68.
- Mandalapu, Varun, and Jiaqi Gong. “Towards better affect detectors: Detecting changes rather than states.” In International Conference on Artificial Intelligence in Education, pp. 199-203. Springer, Cham, 2018.
- Jiaqi Gong, Yanjun Qi, Myla D. Goldman, and John Lach. “Causality analysis of inertial body sensors for multiple sclerosis diagnostic enhancement.” IEEE journal of biomedical and health informatics 20, no. 5 (2016): 1273-1280.
Honors and Awards
- Best Student Paper Award, International Conference on Body Sensor Networks, 2019
- Data Challenge Winning Team, The IEEE Conference on Biomedical and Health Informatics (BHI), 2018
- mHealth Scholarship, UCLA-NIH mHealth Summer Training Institute (mHTI), 2015
- Best Paper Award, International Conference on Body Area Networks, 2014
- Best Demonstration Award, IEEE Wireless Health Conference, 2014