CV

Education

Exchange Program in Quantitative Finance, Hong Kong University of Science and Technology (HKUST), 2023.1 – 2023.6
- School of Business and Management
B.S. in Quantitative Finance, Xi’an Jiaotong University (XJTU), 2021.9 – 2025.6
- Jinhe Center for Economic Research (an Elite School of XJTU)
- GPA: 87.04/100

Youxing, L., & Zihen, C. (2026). Riemannian Sliced Wasserstein Distance on Correlation Matrix. submitted to IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026). Review scores: 5/4/5. Confidence: 4/2/2.
Youxing, L. & Zihen, C. Geometry-Aware Second-Order Pooling for Fine-Grained Visual Recognition currently under review.

Agent Algorithms Engineer — Bauhinia AI Limited / Prof. Kani Chen’s Lab @ HKUST (Sept 2025 – Feb 2026)
- Led end-to-end development of TradingNews.press product from inception, encompassing algorithm design, system architecture, and production deployment. The platform is currently live and serving active users for automated financial news analysis and investment signal generation.
- Architected CRDR workflow orchestration (Channel→Relevant→Decision→ReAct) using LangGraph state machines with parallel processing.
- Developed 7 specialized financial analysis agents with custom prompt engineering and Pydantic output schemas for structured reasoning chains.
- Implemented text-grad architecture with stock price tracking and prompt propagation computation graph via LLM-as-a-judge framework.

President, Business Career Club, Xi’an Jiaotong University (2024 – 2025)
- Organized monthly roundtable discussions with employed alumni and quarterly networking events featuring 20+ senior professionals from finance, consulting, and tech sectors.
- Facilitated knowledge sharing with 100+ student members through career panels and industry speaker sessions.
Team Leader, Tsinghua Economic Hotspot Analysis Competition — Top 1% (July – Oct 2023)
- Led team research on AI-enabled coal mining transformation. Built Cobb-Douglas model analyzing 2000–2022 data, revealing 23.6% increase in technology contribution rate.
- Conducted field research at 6 enterprises, mapping AI applications across 12 scenarios. Proposed “Four-in-One” transformation framework.

Research Areas: Multimodal Learning, Reinforcement Learning, Data Mining, Riemannian Deep Learning
Technical: Python, LangGraph, LLM Agent Development, Optimal Transport, Riemannian Geometry
Hobbies: Music, Playing the Drum Kit, Fitness, Running