Mengyuan (Millie) Wu

HCI Researcher | Full-Stack Engineer | CS PhD Student at Columbia University

HAI x Behavioral Health

About Millie

My research journey began in computational neuroscience and psychology, under Prof. Kiyohito Iigaya at Columbia’s Zuckerman Institute, where I explored how aesthetic emotions relate to psychiatric patterns. I later worked with Prof. Sam Gershman at Harvard as summer intern, studying reinforcement learning and anhedonia using multimodal health datasets. 

To bring these insights into real-world systems, I joined the XR and BCI groups led by Prof. Steve Feiner and Prof. Paul Sajda, where I conducted multi-visit XR studies and contributed to the development of a large-scale physiological foundation model. 

Currently, I work with Prof. Xuhai “Orson” Xu on applied ML and HCI for behavioral health. In collaboration with Equa Health.

Looking ahead to the Ph.D. and beyond, my work aims to unify three research threads:

  1. AI Agents for Self-Exploration and Introspection 

  2. Optimizing Behavioral Patterns through the Quantified Self

  3. AI-assisted Creative Manifestation of Self

Publications

Wu, Mengyuan, Fan, Y., Jiang, Z., Feng, R., Dharmavaram, S., Fallon, S., Polowitz, M., Islam, B., Benson, L., Tung, I., Creswell, J. D., & Xu, X. MindfulAgents: Personalizing Mindfulness Meditation via an Expert-Aligned Multi-Agent System. Submitted to the ACM CHI 2026 (under R&R)

Li, Z.*, He, X.*, Wu, Mengyuan, Tong, Z., Wei, H., Yang, B., Sajda, P., Feiner, S. SwEYEpinch: Exploring Intuitive, Efficient Text Entry for Extended Reality via Eye and Hand Tracking. ACM CHI 2026 (under R&R)

Projects

Expert-Aligned Personalized AI Meditation

Multi-Agent System that generates live, personalized meditation under Expert Aligned Framework

CHI 2026 (Under Review)

Emotion-Aware LLM Psychiatry Session Support

Smart glove enabling real-time affective-aware connection between patients and clinicians via multimodal sensor data.

Law of Attraction AI Journalling

Context aware law-of-attraction LLM that helps user manifest their ideal future 
Won HooHack 2024 2nd Place (Intel AI Track)

EEG-Art for Mindfulness

EEG-derived generative art produced during mindfulness practice.

Won 1st Place NeuReality 2024 Hackathon

Teachings

  • Applied Machines Learning, Course Assistant, Columbia University
  • Advanced Optimization, Course Assistant, Columbia University 
  • Corporate Finance, Teaching Assistant, Columbia University

Interested in Collaboration?

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