Wei Yang 杨炜

• Data Scientist at Kemper.
• Previously at The AES Corporation, led the AES Farseer Renewable Generation Forecasting platform, supported 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.


• Taught various courses in Mathematics and Statistics while doing my Ph.D. at Binghamton University. My notes for Linear Algebra, Calculus 3 and Statistics can be found at the following links: 🔖(LinAlg), 🔖(Cal3) and 🔖(Stat).
• Studied Mathematics and Statistics, researched in Random Matrix Theory at Binghamton University.
• Studied Economics and Mathematics, with a focus on Financial, Actuarial and Computational Mathematics at Baruch College.
  
  
• Skilled in multiple scripting languages, including Python, R, JavaScript and Julia. Lately I have been trying to use shell and bash commands to do as much as possible.


• On this website, I will be creating notes on various materials for myself and others to learn or review.
  

Mathematics

Insurance

Probability

Risk Management

Machine Learning

Commodity Trading

Economics

Renewable Energy

Finance

Notes I keep for myself, and for anyone learning along the way — the mathematics first, then the data science built on it, most of them with interactive demos.

Mathematics

• Linear Algebra — vector spaces, linear maps and the spectral theorem, from my Binghamton teaching notes.
• Calculus 3 — multivariable calculus: partial derivatives, multiple integrals and vector fields.
• Elementary Statistics — probability, distributions, estimation and hypothesis testing.
• Random Matrices — limiting spectra, random graphs, edges and spikes; the companion notes to RandomMatrix.jl.

Data Science

• Classical Machine Learning — the classical core in one thread: least squares from every angle, logistic regression, GLMs and ARIMA; how classifiers draw their boundaries; and how clustering finds structure without labels — with interactive demos throughout.
• Optimization — gradient methods and Newton’s method, linear programming, stochastic optimization and an introduction to reinforcement learning.
• Neural Networks — foundations and learning, convolutional networks, and the modern architectures in brief.
• Natural Language Processing — embeddings, language models and regular expressions.

Kemper Insurance - Pricing and Research Data Scientist
May 2025 - Present, Remote Earth

The AES Corporation - Digital Solutions and Innovation Data Scientist
May 2023 - April 2025, 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.
Commodity Trading
Forecasting
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 Assistant / Instructor
2016 - May 2023, Binghamton NY

• 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 Senator
Sep. 2021 - May 2023, Binghamton NY

• Attend Senate meetings and committee meetings, on 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 Center Math Tutor
Feb. 2014 - Aug. 2016, Queens NY

• Worked with students from disadvantaged backgrounds.
• Guided students in developing study strategies and good study habits. Led group and one-on-one tutoring sessions for struggling students.
• Tutored students in courses including algebra, trigonometry, calculus and linear algebra.
Tutor Queensborough

• RandomMatrix.jl — a Julia package for random matrix theory: limiting spectra (semicircle, Marčenko–Pastur, circular laws), spectral edges and spikes, covariance cleaning and free probability. Registered in the Julia General registry; the companion notes are this site’s Random Matrices page.
• ToolBox — a public Python toolbox of shared, reusable machinery: market data and futures boards, notebook tooling, network utilities. One canonical implementation of each tool, imported everywhere it is used.
• nowei.us — this site. Hand-written HTML, CSS and JavaScript with no framework and no build step: notes on mathematics and machine learning with interactive demos, and a travel atlas.

• Google Cloud Big Data and Machine Learning Fundamentals 🔗
• Sequence Models for Time Series and Natural Language Processing🔗

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• Master Python for Data Science, LinkedIn Learning 🔗
• Master SQL for Data Science, LinkedIn Learning 🔗

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• EXAM P Probability, Society of Actuaries 🔗
• EXAM FM Financial Mathematics, Society of Actuaries 🔗

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• Six Sigma Green Belt, Edu360 🔗

Google Cloud ☁ Python SQL Data Science Probability Financial Mathematics

Six continents, seven countries, fifty-four places, one map. Every place in the albums, pinned — from the Yellow River to the Sacred Valley, and the three cities my wife Yue and I visited together, marked with a ❤️.

🌎 6 continents 🗺️ 7 countries 📍 54 places 📅 Mar 2019 – Oct 2026

Explore the Atlas 🗺️ →