XiaohongshuJackie’s Homepage
Hi! I’m Jackie — a ‘985’ Physics PhD dropout, ex-algorithm engineer, now PhD researcher @ HKU, and Founder of Psycho (AI真人心灵社交平台) and DopaMine (0滑动香港线下大学生 AI dating 平台) — cumulative funding raised: HK$ 1M (≈ USD 128K).
I’m currently a first-year PhD student at The University of Hong Kong, working with Prof. Ben Cowling and Prof. Sheikh Taslim Ali. I obtained my M.Sc. in Systems Science in 2024 and my B.Eng. in Information Systems and Technology in 2021.
My research interests lie in Infectious disease modeling (IDM) and AI for health (AI4health).
Founder · Psycho is an AI-driven social networking platform dedicated to revolutionizing how people form meaningful, soulful connections — helping individuals find their true soulmate through authentic AI-powered interaction.
📱 Download (Android) · 📄 Pitch Deck · 🎬 Product Intro (中文) · 🎬 Product Intro (English)
Founder · DopaMine is an AI-driven offline dating platform for Hong Kong university students — no swiping, no chatting, no anxiety. Every Wednesday 7 PM, DopaMine delivers one real, carefully curated date.
Key milestones: 🚀 DopaMine official launch (Jun 2026) 🏅 12th HK University Student I&E Competition Finals (May 2026) 📱 Psycho Closed Beta Launch (May 2026) 🚀 HKSTP Ideation Seed Funding [HK$100K, 0% equity] 💻 Cyberport Incubation Finals 🎓 HKU Techno-Entrepreneurship Core 🏆 Merit Award · Hong Kong Techathon+ Finals 💰 Cumulative funding: HK$ 1M (≈ USD 128K)
Develop new multiscale modeling methods to characterize cross-scale infectious disease dynamics
Develop a new Bayesian machine learning framework to examine the impact of macroscopic policies on microscopic pathogen dynamics, and to identify generation time as a key mechanistic link bridging micro-level viral load dynamics and macro-level epidemic growth rates.
Unravel how population immunity and viral co-circulation influence each other to predict future pandemics and viral evolution
Integrating multi-source surveillance and behavioural data to reveal the bidirectional interplay between population immunity and viral co-circulation.
AI-Based Framework for Early Detection and Intervention in Multiple Respiratory Disease Epidemics
Illustration of the predictive frameworks with data-driven hypotheses, methodological and implicative improvement for early prediction of epidemics, severity, burden for multiple respiratory viruses using an integrated interface of AI-Model and epidemic models for real-time interventions.