CV

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Education

• M.S.E. in Data Science, Johns Hopkins University, Jan 2026 – Present
  Department of Applied Mathematics and Statistics, Baltimore, MD

• B.E. in Data Science and Big Data Technology, Tongji University, Sep 2019 – Jun 2023
  College of Electronics and Information Engineering, Shanghai, China · GPA: 3.55 / 4.0
  Key Courses: C/C++/Python Programming, Operating System, Data Mining, Data Structure and Algorithm Design, Big Data Management Systems, Cloud Computing, Machine Learning, Artificial Intelligence

Research Experience

• Loss Landscape Analysis of Scientific Machine Learning Models, Mar 2025 – Present
  Advisor: Prof. Yaoqing Yang, Dartmouth College
  • Developed measurement of mode connectivity in PINNs; characterized optimization regimes based on Hessian, CKA, and mode connectivity.
  • Conducted systematic comparisons of soft and hard constraint methods (Fourier parameterization, penalty method, Augmented Lagrangian Method, Trust-Region SQP) to analyze performance across different regimes.
  • Identified and explained several pathological phenomena in SciML that differ from those observed in computer vision, from a loss landscape perspective.
  • Measured overlap of Hessian top subspace of loss items to identify trivial solutions.
  • Paper accepted at ICML 2026.
• Low-light Image Enhancement Based on Attention Mechanism, Mar 2023 – Jun 2023
  • Reproduced Illumination Adaptive Transformer and Multi-Axis MLP; conducted experiments on LOL and SICE datasets.
  • Optimized deep convolution enhancement module in the local branch by incorporating SWIN attention.
  • Attempted to incorporate black level correction transformation matrices from ISP into the global branch.
  • Project received 50+ forks on Kaggle; achieved PSNR of 0.65 and SSIM of 20.45.

Professional Experience

• Software Development Engineer, Beijing Dajia Internet Information Technology (Kuaishou), Jul 2023 – Mar 2025, Beijing, China
  • Built performance analysis, monitoring, and traffic replay tools for large-scale mobile systems, enabling rapid diagnosis of memory and performance issues.
  • Maintained and developed UI components (images, animations, listviews) to support large-scale events on Kuaishou, including Singles’ Day and Chinese New Year.
  • Designed ETL pipelines and dashboards to analyze JSVM memory usage, reducing issue attribution time from hours to minutes.
  • Identified and resolved performance and memory inefficiencies in layout, image, animation components and property export; reduced peak memory usage by 56% and rendering time by 11% in dynamic stages for e-commerce and local services scenarios.

Publications

Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization

Yuxin Wang, Yuanzhe Hu, Xiaokun Zhong, Xiaopeng Wang, Haiquan Lu, Tianyu Pang, Michael W. Mahoney, Yujun Yan, Pu Ren, Yaoqing Yang. (2026). "Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization." ICML 2026.

Skills

• Programming Languages: C/C++, Python, Objective-C, JavaScript, Scala, SQL
• Databases: MySQL, HBase, PostgreSQL
• Big Data: Hive, Hadoop, Spark, Kafka, Flink, PowerBI, Tableau
• Operating Systems: Linux
• ML / SciML: PyTorch, PINNs, Fourier Neural Operators, Neural ODEs, Hessian analysis