About me

Here this is who I am.

Chang Ye (Eric)

Contact Information

About Me

I earned my Ph.D in Electrical Engineering from the University of Rochester, specializing in statistical modeling, machine learning, and deep learning for relational data. I am also pursuing a M.Sc in Financial Engineering.

My expertise lies in developing machine learning algorithms, statistical analysis, predictive modeling, and optimization. I also have hands-on experience in financial data processing and implementing Large Language Model (LLM) for financial forecasting.

Skills & Expertise

  • Machine Learning & AI: Large Language Models (LLMs), Deep Learning (DL), Graph Neural Networks (GNNs), LightGBM
  • Financial Modeling: Backtesting, Option Pricing, Fixed Income Securities
  • Programming & Development: Python, TensorFlow, PyTorch, NumPy, Pandas
  • Data Analytics & Finance: Certified in Data Analytics and Finance & Quantitative Modeling

Research & Work Experience

During my doctoral studies, I worked extensively on statistical modeling and deep learning techniques. My research on blind deconvolution for graph signals showcases my ability to design and implement sophisticated mathematical models. Additionally, I developed an efficient and interpretable deep neural network (DNN) architecture that outperformed state-of-the-art GNNs in source localization tasks on real-world datasets.

I specialize in the core quantitative workflow: building predictive models from market data and deploying algorithms for global exchanges. As a Quantitative Research Intern at Junli Capital, I developed a cryptocurrency basis arbitrage strategy using a low-latency WebSocket pipeline and a fine-tuned time-series transformer for forecasting short-term dynamics on 100ms-level order book data.

Projects & Contributions

I am an active contributor to open-source projects and frequently share my work on GitHub. My projects include implementations of advanced statistical models, deep learning algorithms, and financial data analysis techniques.

Closing Thoughts

I am excited about opportunities where I can apply my technical expertise, analytical mindset, and problem-solving skills. I look forward to collaborating with professionals and contributing to innovative projects in machine learning and quantitative finance.

My photo

To know more about me, check my beautiful photos at 500px!