• Digital mental health
• Artificial intelligence
• Natural language processing
• Electronic media use

Tim Li’s specialized research focuses on leveraging artificial intelligence – particularly machine learning and natural language processing – to tackle critical challenges in digital mental health. He has developed AI models to detect depression, suicidal ideation, and predict patient engagement with digital cognitive behavioral therapy. By analyzing app-based and multimodal digital data, his work identifies behavioral and linguistic markers associated with sleep and mental disorders. Tim also examines the influence of electronic media on mental health and explore innovative technology-driven interventions. Through this interdisciplinary approach, he aims to advance early detection and personalized intervention in mental health care.

Tim Li’s research focuses on artificial intelligence (AI) and digital mental health. He has published more than 60 peer-reviewed articles in international journals. With extensive experience as a lead AI engineer in R&D companies, he specializes in designing, developing, and evaluating AI systems for mental health applications. His work was recognized with the INFORMS ISS Design Science Award in 2020. As PI, Tim has secured competitive research grants, including ECS, GRF, HMRF, and ITF, to advance AI applications for mental health care, and he also serves as Co-PI on CRF and TRS projects.

1. The Design Science Award, INFORMS Information Systems Society (2020)

1. So RWL, Chan KY, Cheng CCW, Chan NY, Li SX, Chan JWY, Chau SWH, Wing YK, Li TMH. Predicting adherence to fully-automated, chatbot-delivered digital cognitive behavioral therapy for insomnia (dCBT-I) using machine learning: A pilot real-world study. PLOS Digital Health. 2026;5(1):e0001170. doi:10.1371/journal.pdig.0001170.
2. Lam C, Xian L, Huang R, Chen J, Chan KY, Chan JWY, Chau SWH, Chan NY, Li SX, Wing YK, Li TMH. Deep learning for detecting depression in individuals with and without alexithymia. Communications Medicine. 2026;6(1):123-. doi:10.1038/s43856-026-01393-0.
3. Cheung T, Lam JYT, Fong KH, Cheng CPW, Xiang YT, Li TMH. Efficacy of electrical vestibular stimulation (VeNS) on adults with insomnia: A double-blind, randomized, sham-controlled trial. Dialogues in Clinical Neuroscience. 2025;27(1):236-248. doi:10.1080/19585969.2025.2526547.
4. Lam C, Chen J, Chan KY, Chan JWY, Chan NY, Li SX, Huang B, Wing YK, Li TMH. Identifying multimodal digital features of insomnia using an app in Hong Kong: An ecological momentary assessment study. Sleep Medicine. 2025;136:106825. doi:10.1016/j.sleep.2025.106825.
5. Yu DJ, Wing YK, Li TMH, Chan NY. The impact of social media use on sleep and mental health in youth: A scoping review. Current Psychiatry Reports. 2024;26(3):104-119. doi:10.1007/s11920-024-01481-9.
6. Chen J, Chan NY, Li CT, Chan JWY, Liu Y, Li SX, Chau SWH, Leung KS, Heng PA, Lee TMC, Li TMH, Wing YK. Multimodal digital assessment of depression with actigraphy and app in Hong Kong Chinese. Translational Psychiatry. 2024;14(1):150-. doi:10.1038/s41398-024-02873-4.
7. Huang R, Yi S, Chen J, Chan KY, Chan JWY, Chan NY, Li SX, Wing YK, Li TMH. Exploring the role of first-person singular pronouns in detecting suicidal ideation: A machine learning analysis of clinical transcripts. Behavioral Sciences. 2024;14(3):225. doi:10.3390/bs14030225.
8. Cheung T, Li TMH, Lam JYT, Fong KH, Chiu LY, Ho YS, Tse ACY, Li CT, Cheng CPW, Beisteiner R. Effects of transcranial pulse stimulation on autism spectrum disorder: A double-blind, randomized, sham-controlled trial. Brain Communications. 2023;5(5). doi:10.1093/braincomms/fcad226.
9. Li TMH, Chen J, Law FOC, Li CT, Chan NY, Chan JWY, Chau SWH, Liu Y, Li SX, Zhang J, Leung KS, Wing YK. Detection of suicidal ideation in clinical interviews for depression using natural language processing and machine learning: Cross-sectional study. JMIR Medical Informatics. 2023;11(1):e50221. doi:10.2196/50221.
10. Li TMH, Chan NY, Li CT, Chen J, Chan JWY, Liu Y, Li SX, Li AM, Zhang J, Wing YK. The associations of electronic media use with sleep and circadian problems, social, emotional and behavioral difficulties in adolescents. Frontiers in Psychiatry. 2022;13:892583. doi:10.3389/fpsyt.2022.892583.