Xin Wang 王鑫

• GPA: 3.81 / 4.00
• Selected coursework: Psychological Statistics 96; Experimental Psychology Laboratory 95; Psychology of Emotion 93; Cognitive Neuroscience 95; Physiological Psychology 95; Perspectives in Modern Psychology 100

Emotion Regulation and Self-Verification Research Series

• Participate throughout the research series, initially focusing on data analysis (E-Prime) and conducting experiments; now lead the experimental design and PsychoPy implementation of Study 3, distinguishing negative self-schema from negative emotion, and recruit research-team members and experiment participants

Undergraduate thesis

• Drawing on self-verification and emotion-regulation motivation theories, examine beliefs about deserving a good mood and cognitive emotion-regulation strategies as serial mediators
• Responsible for data collection, statistical analysis and thesis writing; construct structural equation models using SPSS and Mplus

PROM development · Provincial undergraduate innovation project

• Developed the conceptual framework, interview guide and project proposal; conducted data analysis and contributed to cognitive interviews, documentation and item revision
• The project team cumulatively interviewed 283 patients and 100 family members and consulted 17 interdisciplinary experts, producing a preliminary measure. Provincial-level undergraduate innovation project completed in 2025

Local game library software

• Lead requirements and interaction design, using AI to assist implementation, debugging and validation. Implement folder scanning, candidate review, classification and launching, and iterate local storage and the desktop interface
• The Unity loader adaptation and on-demand confirmation fix received an invitation for inclusion in XERJ Corpus Hub; inclusion is pending

fnOS native application

• Core features include SHA-256 exact-duplicate detection, frame-based perceptual-hash visual similarity detection and incremental scan caching

Godot independent game

• Lead gameplay, interaction design and feature selection with AI-assisted development; build a runnable prototype around shopping, cooking, resource management and roommate interactions
• Design dish ratings, risk and relationship feedback; iterate saves, tutorials and interactions with logic tests and runtime validation

BuildArena · Human–AI collaboration

• Used GLM-5.3 in ZCode to build a Besiege machine for BuildArena; the project won Most Creative Machine in the Build with Agents track.

Digital Employee Benchmark

• Contributed to task design and expert-assessment alignment for requirements and product-documentation assistants; translated business needs into observable tasks and distinguished objective constraints, expert judgment and user preferences
• Evaluated citation authenticity, completeness, assessment consistency and real-world feedback, developing a layered evaluation approach