About Me Skills Experience Projects Certifications Education





Hello, I'm Wei Yang 杨炜.

  • Data Scientist at The AES Corporation, supporting commodity trading, EVSE planning, grid simulations and HR analytics.
  • Amateur Photographer, I love to take pictures of architectures, landscapes and wild lifes. Currently, 57% done with my goal of visit all the 7 continents.

  • 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).
  • Graduated from Baruch College, with studies concentrated in Economics, Financial and Actuarial Mathematics.

  • Proficient in multiple scripting languages, including Python, R, Javascript and Julia.
  • A.I. in my dictionary stands for artificial idiot. Overestimating A.I. is essentially underestimating human intelligence.

  • On this website, we 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 -- 20xy, Houston TX
    • Power Forecasting
      • Develop and maintain a seasonal champion model to forecast wind power output with weather data.
    • Commodity Trading
      • Studied and combined DART, demand and generation data to optimize trading strategies.
    • EVSE planning
    • Grid Simulations
    • HR Analytics with LLM
      • Applied LLM in a multi-layer process to rank all (applicant, department) pairs.
      • Developed an error detection model to identify potential errors in the LLM outputs in all stages of the process.
      • Devised a catch-and-retry mechanism to ensure the LLM process is robust, reliable and fair.

    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.
    • Created model to forecast wind power output with weather data. Scaled the model to all 10 AES US wind sites.
    • Worked with teams of engineers and traders to leverage AI/ML for daily operations.
    Forecasting Commodity Trading
    Renewable Energy
    Machine Learning
  • Binghamton University - Department of Mathematics and Statistics
    Teaching Assistance / Instructor
    2016 - Present
    • Taught over 300 students in courses in Statistics, Linear Algebra and Calculus.
    • Produced over 200 pages of supplementary notes to help students in understanding concepts.
    • Devise quiz questions based performance data, observed an average increase of 20% in scores between first and final exam.
    • Conduct tutoring sessions during office hours. Reach out to students to give suggestion and timely feedback.
    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
  • 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 (Expected Spring 2023)
    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