研究领域
目前的研究兴趣主要包括人工智能算法在移动边缘计算不同领域中的应用及推广，相关算法及框架包括联邦学习，主动学习，深度学习，移动边缘计算系统中的人机交互技术，及其在智能手机及可穿戴设备等IoT终端的实现与应用。
主要荣誉
CHASE 2021 Best Paper Award 2021 Commonwealth Cyber Initiative (CCI) 2020 Seeding Grant, $50,000 2020 CHASE 2019 Travel Grant, $600 2019 CHASE 2018 Travel Grant, $500 2018 SIE Student Travel Fellowship, $1000 2018 弗吉尼亚大学全额奖学金 2014-2020
代表性论文
Boukhechba, M., Cai, L., Chow, P. I., Fua, K., Gerber, M. S., Teachman, B. A., Barnes, L. E. (2018). Contextual Analysis to Understand Compliance with Smartphone-based Ecological Momentary Assessment. Proceedings of the 2018 ACM PervasiveHealth.
Cai, L., Boukhechba, M., Kaur, N., Wu, C., Barnes, L. E., Gerber, M. S. (2019, June). Adaptive passive mobile sensing using reinforcement learning. In 2019 IEEE 20th International Symposium on” A World of Wireless, Mobile and Multimedia Networks”(WoWMoM) (pp. 1-6). IEEE.
Boukhechba, M., Cai, L., Wu, C., Barnes, L. E. (2019). ActiPPG: using deep neural networks for activity recognition from wrist-worn photoplethysmography (PPG) sensors. Smart Health, 14, 100082.
Cai, L., Barnes, L. E., Boukhechba, M. (2021). Designing adaptive passive personal mobile sensing methods using reinforcement learning framework. Journal of Ambient Intelligence and Humanized Computing, 1-22.
Guimin Dong, Mingyue Tang, Zhiyuan Wang, Jiechao Gao, Sikun Guo, Lihua Cai, Robert Gutierrez, Bradford Campbell, Laura E. Barnes, Mehdi Boukhechba. Graph Neural Networks in IoT: A Survey, ACM Transactions on Sensor Networks.
代表性项目
诠释训练对减少焦虑的有效性：评估基于技术的实现模式和方法用以减少流失。（Effectiveness of interpretation training to reduce anxiety: Evaluating technology-based delivery models and methods to reduce attrition.） 2017 – 2021 Key Personnel PI: Bethany Teachman, 5R01MH113752, $2, 039, 218
REaDI Sense：可靠的疾病指标分析 (对战士使用智能手机进行分析的健康计划)。（REaDI Sense: Reliable Analytics for Disease Indicators）(Warfighter Analytics using Smartphones for Health Program.) 2018-2021 Key Personnel PI: Laura Barnes, DARPA-HR001117S0032, $2, 068, 752
使用移动传感监测和改善乳腺癌护理人员的心理健康。（Monitoring and Improving Mental Health of Breast Cancer Caregivers Using Mobile Sensing.） 2018-2019 Key Personnel PI: Philip Chow, Engineering in Medicine, $89, 170
Biography： Dr. Lihua Cai graudated from the Department of System and Information Engineering at the University of Virginia (UVa) in 2020 and has conducted postdoctoral research at UVa in the Link Lab and Sensing Systems for Health Lab for about 2 years before joining SCNU as a faculty member in the Aberdeen Institute of Data Science and Artificial Intelligence, and School of Software. He held numerous positions in the industry including UCSF and Ancestry.com before he returned to pursue his Ph.D. in academia. His main research interests lie in the interdisciplinary area of mobile edge computing and Internet of Things (IoTs) with focus on various learning frameworks including Deep Learning, Active Learning, Federated Learning, and Human Computer Interaction (HCI) in the mobile computing settings.
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