About me
Jingxuan Wu is an undergraduate in the School of Data Science (SDS) at The Chinese University of Hong Kong, Shenzhen (CUHKSZ). He is pursuing a Bachelor’s degree in Data Science and Big Data Technology and has been consistently recognized for his academic excellence, including being named to the Dean’s List and receiving the Undergraduate Research Assistantship. Jingxuan has also been actively involved in the Statistics Society at CUHKSZ.
Jingxuan is passionate about applying advanced machine learning, reinforcement learning, and operations research to solve complex, real-world problems. His research interests include the practical applications of deep learning, large language models, and optimization models. He has collaborated with faculty members from CUHKSZ and the University of North Carolina at Chapel Hill on various research projects, aiming to address significant operational challenges.
He is actively seeking a Ph.D. position for Fall 2025 to further his research and continue exploring innovative solutions in the fields of data science and machine learning.
Feel free to connect with him on LinkedIn and check out my projects on GitHub.
Research Experience
- Resource Prediction and Allocation for Machine Learning Tasks
- May 2024 - Present, University of North Carolina at Chapel Hill
- Predicted runtime and energy consumption of ML tasks on GPUs using LLMs.
- Research on Airport Congestion Contagion
- Dec 2023 - Present, The Chinese University of Hong Kong, Shenzhen
- Improved SIS models to predict and manage airport congestion using adaptive graph learning and ODE function.
- Optimization of Guangzhou Bus Rapid Transit (BRT) Public Road Usage
- Jan 2024 - Present, University of North Carolina at Chapel Hill
- Combined stochastic optimization model and machine learning to enhance public road usage.
- Study on Flight Delay Propagation Modeling
- Oct 2023 - Mar 2024, The Chinese University of Hong Kong, Shenzhen
- Authored a review on airport delay propagation methods, accepted by Transportation Research Part E.
- Lithology Based Rock Prediction
- Mar 2023 - Jun 2023, The Chinese University of Hong Kong, Shenzhen
- Predicted rock properties using SVM and HMM models based on depth curves.
Work Experience
- Quantitative Trading Intern
- Jun 2023 - Aug 2023, Maxtor Big Data, Hangzhou, China
- Developed and tested options trading and arbitrage strategies; implemented backtesting tools.
- COSCO Shipping Analysis
- Sept 2022 - Feb 2023, The Chinese University of Hong Kong, Shenzhen
- Enhanced maritime intelligent systems through clustering, route prediction, and congestion analysis.