About Me Skills Experience Projects Certifications Education





Hello, I'm Wei Yang 杨炜.

  • Data Scientist at The AES Corporation, leading the Renewable Generation Forecasting platform, supporting LNG Optimization, Turbine Fault Detection, LLM-based resume evaluation, and EVSE planning. Recommendations from peer and direct manager can be found on my LinkedIn profile 📩.

  • A self-proclaimed photographer. I love capturing pictures of architecture, landscapes, stars, and wildlife. These photos not only showcase the world but also reflect a part of myself at that moment. I've set foot on six continents, with Antarctica being the only one left to explore.

  • Interested in Random Matrix Theory, Data Science and Machine Learning.
  • Taught various courses in Mathematics and Statistics while doing Ph.D at Binghamton University. My notes for Linear Algebra and Calculus 3, can be found at the following links : 🔖(LinAlg), 🔖(Cal3) and 🔖(Stat).
  • Graduated from Baruch College, with studies concentrated in Economics, Financial and Actuarial Mathematics.

  • Skilled in multiple scripting languages, including Python, R, Javascript and Julia.

  • On this website, I will be creating notes on various materials for myself and others to learn or review.
Mathematics Random Matrix Data Science Machine Learning Programming Commodity Trading Finance Economics
Renewable Energy
    The AES Corporation - Digital Solutions and Innovation Data Scientist
    May 2023 -- Present, Houston TX
    • Wind & Solar Generation Forecasting
      • Spearheaded development of the AES Farseer renewable generation forecasting system for 30+ AES wind and solar sites across the Americas. Achieved 30.4% mean absolute error reduction compared to vendor models, generating $12.2M in operational savings by improving forecast accuracy.
      • Researched the impact of extreme weather events such as icing on wind generation, calibrated models to the local weather patterns, and achieved a 45% reduction in forecast error under extreme weathers.
      • Enhanced model interpretability and strengthened stakeholder trust through the use of explainable AI (XAI) techniques.
    • Solar Panel Dust Detection & Fault Detection System
      • Implemented EfficientNet architecture in PyTorch for solar panel dust detection, achieving a 16% improvement over traditional CNN models.
      • Developed turbine fault detection models using Moving Window PCA, reducing fault detection time from 7 days to under 48 hours. The models reduced maintenance costs by over 45%.
    • LNG Optimization Model
      • Created stochastic dual dynamic programming (SDDP) models in Python/OR-Tools to optimize LNG procurement strategy, increasing profit by 24% through dynamically balancing inventory, obligations, and price volatility.
    • Other Projects
      • Collaborated with HR specialists on resume scoring models using Large Language Models (LLMs) & Natural Language Processing (NLP) techniques. The model reduced the resume screening time of 300 applications from 2 weeks to 1 day.
      • Forecasting Commodity Trading
      Renewable Energy
      EVSE Locational Valuation LLMs NLP
    Data Science Intern
    May 2022 - Aug. 2022 , Indianapolis IN
    • Leveraged Random Matrix Theory and Modern Portfolio Theory to develop an internal package for solving various portfolio optimization problems.
    • Worked with teams of engineers and traders to leverage AI/ML for daily operations.
      • Portfolio Optimization Random Matrix Theory Modern Portfolio Theory Machine Learning
    Binghamton University - Department of Mathematics and Statistics Teaching Assistance / Instructor
    2016 - Present
    • Taught over 1000 students in Data Science, Probability, Statistics, Linear Algebra, and single/multivariate Calculus
    • Created comprehensive study materials and interactive learning resources that improved student comprehension of advanced mathematical concepts
    • Implemented data-driven assessment strategies, resulting in 20% average improvement in student performance from initial to final exams
    • Provided individualized support through regular office hours and proactive student outreach, maintaining consistently high student satisfaction
      • Instructor Binghamton
    Graduate Student Organization at Binghamton
    Student Senator
    Sep. 2021 - Present
    • Attend senate meetings and committee meetings, on behalf of over 70 graduate students in department.
    • Attend Senate meetings and committee meetings, on the behalf of over 70 graduate students in the department. Communicate with colleagues in math department on pertinent issues raised during meetings.
      • Student Senator Graduate Student Organization
    Queensborough Community College
    Math Tutor
    Feb. 2014 - Aug. 2016
    • Worked with students from disadvantaged backgrounds.
    • Guided students in developing study strategies and good study habits. Led group and one-on-one tutoring session for struggling students.
    • Tutored students in courses including algebra, trigonometry, calculus and linear algebra.
      • Tutor Queensborough
  • Electricity Market Portfolio Optimization
    • Collected over 100 gigabytes of data from Independent System Operators (ISOs) through API and web scraping.
    • Cleaned, transformed, and filtered data using results on random covariance matrices.
    • Generated recommendations for portfolios of long and short positions using filtered covariance matrices. The results are demonstrated to be more stable and outperforms unfiltered portfolios for over 93% of the time.
    • Portfolio Optimization
  • Handwriting Recognition Web Application
    • Balanced an unbalanced image data set by generating randomly perturbed images from the existing ones, the resulted data set contains over 2,500,000 28 × 28 pixel images with 62 labels.
    • Trained a Convolutional Neural Network model with the generated data set in Python with TensorFlow, achieving 90% accuracy. The model is then exported as a JavaScript object, for web deployment.
    • Created a Handwriting Recognition Web Application with the trained model, and deployed to the project web page.
    • The deployed app can be found on the page Neural Networks 🔗.
    • Handwriting Recognition Imbalanced Data TensorFlow Convolutional Neural Network Interactive Web App
  • S&P 500 Market Sectors Reclassification
    • Performed Web Scraping on Wikipedia and Yahoo Finance to extract the data of the S&P 500 companies over the last 10 years.
    • Cleaned, transformed the data, and denoised the transformed data using results from Random Matrix Theory.
    • Performed hierarchical clustering on the denoised data.
    • The Reclassification provides a better understanding of the market, and enabled additional options for portfolio optimization.
    • Clustering Random Matrix Theory S&P 500
  • RandomMatrix.jl (a registered Julia package)
    • Developed a package to work with matrix-valued distributions.
    • Documented functionalities and deployed the documentation to the package documentation page 🔗.
    • Random Matrix Package Documentation
  • Personal Website & Interactive Demos (This website 😊)
    September 2021 - Present
    • Designed a personal website from scratch using JavaScript and HTML, with the purpose of sharing my projects and write about Mathematics and Data Science.
    • Created Interactive Demos to demonstrate ideas in Mathematics and Data Science.
    • This is a long term project, and I will be continuing to update the pages on this website.
    • Interactive Data Science Mathematics HTML JavaScript
  • Google Cloud Big Data and Machine Learning Fundamentals 🔗
  • How Google does Machine Learning 🔗
  • Launching into Machine Learning🔗
  • TensorFlow on Google Cloud🔗
  • Feature Engineering🔗
  • Sequence Models for Time Series and Natural Language Processing🔗
  • Master Python for Data Science, LinkedIn Learning 🔗
  • Master SQL for Data Science, LinkedIn Learning 🔗
  • Learning Regular Expressions, LinkedIn Learning
  • EXAM P Probability, Society of Actuaries 🔗
  • EXAM FM Financial Mathematics, Society of Actuaries 🔗
    • Google Cloud ☁ Python SQL Data Science Probability Financial Mathematics
  • Binghamton University, SUNY
    Ph.D. in Mathematics and Statistics (2023, ABD)
    Master of Science in Mathematics and Statistics (2018)
    Dissertation Fellowship
    GPA : 3.91/ 4.00
    • Ph.D. Fellowship Mathematics Statistics Binghamton
  • Baruch College, CUNY
    Bachelor of Art in Economics (2016)
    Bachelor of Art in Mathematics with a minor in Philosophy (2016)
    Dean's List
    GPA: 3.77/4.00
    • Mathematics Economics Philosophy Baruch Dean's List
  • Francis Lewis High School
     High School Diploma (2011)
    Math Team