Yuguang Yang

About Yuguang Yang

Highlights: Book: LLM Foundation and Application in IR (2023-) (https://yangyutu.github.io/llm_book.github.io/docs/index.html) Fundamentals of LLM, including NLP basics, LLM architecture, training, inference, and applications in information retrieval. Book: Essentials of Mathematical Methods (2021) in Github (https://github.com/yangyutu/EssentialMath) Vo1-Foundations and Principles: Essential foundations and principles in applied math and statistical modeling, including linear algebra, matrix analysis, optimization, statistics, and dynamical systems. Vo2-Statistical Learning and Deep Learning: Foundations, algorithms, and recent developments in statistical learning, deep learning, and reinforcement learning. Their applications in natural language processing, speech and speaker recognition, etc. are demonstrated. Professional skills summary: • Solid applied math and extensive mathematical modeling experience, with an in-depth understanding of analytical methods and data-driven methods (ML/DL/DRL); capable of abstracting models from complex application scenarios and strategically leveraging different modeling methodology. • Applied scientist and machine learning engineer. Work with cross-functional teams of scientists, engineers to design and implement ML systems and solutions to improve and enrich customer experience. • Propose and execute risky research ideas that offer long-term customer impact. Drive research to production by constructing productionization roadmap and influencing peers and leadership. • Adept in coaching interns/juniors in research and engineering. • Skills: Natural language processing, search engine technologies, LLM, machine learning, deep learning, reinforcement learning (Python, PyTorch, Spark, C++, Shell, etc.)

Experience

1. Member of Technical Staff

   OpenAI

   Feb 2025 — Present

2. Principal Applied Scientist

   Microsoft

   Aug 2024 — Feb 2025

3. Senior Applied Scientist

   Microsoft

   Mar 2022 — Sep 2024

4. Applied Scientist II @ Alexa AI

   Amazon

   Oct 2020 — Mar 2022

5. Applied AI Visiting Researcher (Part-time)

   Tsinghua University

   Jun 2018 — Sep 2020

6. Quantitative Analyst (machine learning & software developer)

   Wells Fargo

   Jul 2017 — Sep 2020

7. Research Intern

   PARC, a Xerox Company

   Oct 2016 — Dec 2016

8. Software Engineer Intern

   Vectorworks

   Jun 2015 — Aug 2015

Education

• The Johns Hopkins University

  Doctor of Philosophy (Ph.D.) · Computational Chemical Physics & Machine Learning

  2011 — 2017

• The Johns Hopkins University

  Master’s Degree · Computer Science

  2014 — 2016

• Zhejiang University

  Bachelor's degree · General engineering education in Chu Konchen Honors College

  2007 — 2011

• Guilin Middle School

  High School

  2004 — 2007

Skills

• Applied Mathematics
• Mathematical Modeling
• Java/C/C++
• Matlab
• Algorithms
• Numerical Methods
• Parallel Computing
• Machine Learning
• Fluid Dynamics
• Database(Php/Mysql)
• Statistical Mechanics
• Image Analysis
• Physical Chemistry
• Numerical Analysis
• Microsoft Office
• Mathematica
• Latex
• Python
• Programming
• Fortran
• C
• Simulations
• Python (Programming Language)