Projects
Here you’ll find a list of my research and applied projects😊.
If you’re interested in collaboration or want to know more details, please 📧contact me.
Research on Social Familiarity and Self in the Uncanny Valley: A Multidimensional Exploration (Master Thesis)
Author & Lead Researcher | Advisor: Prof. Guomei Zhou
Duration: Dec 2024 – Present
This project investigates the uncanny valley effect from the perspectives of social cognition and self-concept, focusing on emotional, cognitive, and social mechanisms. It also includes the development and validation of a new scale to measure human threat perception and defensive mechanisms toward robots.
Mapping Decision-Related Neural Dynamics Across the Mouse Brain Using Machine Learning Approaches
Lead Researcher | Neuromatch Academy - Computational Neuroscience
Duration: Jul 2025
Using open-access IBL data, this project applies machine learning to decode and map decision-related neural signals across the mouse brain.
Recency Effect in the Ensemble Perception of Average Facial Attractiveness
Author & Lead Researcher | Advisor: Prof. Guomei Zhou
Duration: Nov 2023 – Aug 2024
- Explored how recent stimuli influence ensemble perception of group facial attractiveness
- Designed and conducted four experiments using RSVP paradigms with morphed and real faces
- Demonstrated that later-presented faces exert disproportionate weight on group attractiveness judgments
- Established a weighted-processing model and linked the recency effect to memory constraints
User Mental Model Construction for 3D Virtual Fitting Room
Author & Researcher | Advisor: Associate Prof. Qi Wang
Duration: Apr 2024 – Jun 2024
- Developed a preliminary user mental model for 3D virtual fitting room applications
- Analyzed user needs, personas, and behavioral patterns in online apparel shopping
- Designed user-centered functionalities and usability testing scenarios
- Proposed solutions for optimizing shopping experience and reducing return rates
Bank Product Customer Subscription Prediction with LightGBM
Author & Researcher | Advisor: Associate Prof. Ying Lin
Duration: Oct 2024 – Jan 2025
- Built a machine learning system for predicting customer subscription to bank products
- Conducted comprehensive data preprocessing and feature engineering
- Compared and optimized Decision Tree, Random Forest, XGBoost, and LightGBM models using Optuna
- Performed model evaluation, stacking ensemble, and feature importance analysis
- Delivered actionable recommendations for marketing strategies