Wancheng Lin

1st-year PhD Student · Probability & Stochastic Processes

Hi, thanks for visiting! I go by Walden, and I am currently studying Stochastic Analysis and Probabilistic Foundation for Generative AI

Topic Interests

🎲

Stochastic Analysis

Broadly interested in the theoretical study of large stochastic systems, especially on rare events and heavy tails

🤖

Generative AI

Understanding the probabilistic underpinnings of generative models and their theoretical guarantees.

🔗

Blockchain

Building decentralized systems, aligning consensus and incentives with the transformative potential of DeFi, InfoFi, and AI agents.

Me in Colorado

Contact

wancheng@bu.edu

Office 338 CDS

Department of Mathematics and Statistics

Boston University

665 Commonwealth Ave

Boston, MA 02215

Education

Now, I am a first-year Ph.D. student in the Department of Mathematics and Statistics at Boston University, and I received my Bachelor's degree from the University of North Carolina at Chapel Hill in 2025.

My educational path has been unconventional yet deeply rewarding. I began as an undergrad exploring Actuarial Science/Accounting/Data Science at Nankai University for 2 years during the global pandemic, while also joining short-term programs on basic computer science at Peking University, Fudan University, and Oxford University. Before coming to the U.S., I completed a Globalink Mitacs internship at the Université de Montréal, Canada. Later, I transferred to UNC, where I studied @MATH and @STOR for 3 years, also taking a course at Duke University. Alongside formal study, much of my growth has been shaped by open platforms such as YouTube, Bilibili, 得到 (Dedao), Coursera, and edX. Now, as a Ph.D. student in the Department of Mathematics and Statistics at Boston University, I remain sincerely grateful for the high-quality education I have received throughout this journey—and above all, for the privilege of learning from truly exceptional mentors and teachers along the way.

Probability Theory Prof. Konstantinos Spiliopoulos
Advanced Stochastic Processes Prof. Solesne Bourguin
Algorithms for Machine Learning Prof. Alina Ene
Advanced Calculus I Prof. Hans Christianson
Advanced Calculus II Prof. Michael Taylor
Topology Prof. Jiuzu Hong
Algebraic Structure Prof. Alexander Varchenko
Measure Theory & Integration Prof. Mark Williams
Ordinary Differential Equations (H) Dr. Jian Wang
Partial Differential Equations Prof. Jeremy Marzuola
Functional Analysis Prof. Idris Assani
Probability II Prof. Sayan Banerjee
Mathematical Statistics Prof. Jan Hannig
Theoretical Statistics II Prof. Andrew Nobel
Stochastic Models I Prof. Nilay Argon
Stochastic Models II Prof. Serhan Ziya
Simulation Modeling Prof. Mariana Olvera-Cravioto
Markov Decision Process & RL Prof. Guanting Chen
Auction and Learning Theory Mentor: Prof. Guanting Chen
Optimization for ML & DS Prof. Michael O'Neil
Data Driven Decision Models Prof. Vidyadhar Kulkarni
Advanced Probability for Applications Prof. Shankar Bhamidi
Weak convergence and local weak convergence Prof. Zoe Huang
Dynamic Programming & Stochastic Control (Duke) Prof. Peng Sun
Rare Events and Heavy-Tailed Phenomenon: from Queuing and Insurance Ruin to Random Graph and Complex Network Honor Thesis Advisor: Prof. Mariana Olvera-Cravioto
Bayesian Robust Statistics with Applications in Actuarial Science Globalink Mitacs Research Intern Mentor: Philippe Gagnon
Introductory Microeconomics
Intermediate Microeconomics
Introductory Macroeconomics
Intermediate Macroeconomics
Investment
Theory of Interest
Financial Accounting Prof. Le Zhao
Financial English Prof. Yifang Chu
Finance Prof. Xue Wang
Insurance and Risk Management
Corporate Finance
Data Structures and Algorithms
Econometrics Prof. Tingting Cheng
Adv Algebra and Analytic Geometry Prof. Dongxiao Han
Probability Prof. Lidan Wang
Actuarial Modelling Prof. Lianzeng Zhang
Machine Learning and R Prof. Lianzeng Zhang
Dynamic Decision Making Prof. Xiaowei Chen

Python (Summer School) Bin Chen (Peking University)
Internet Data Analysis & Research Oxford University
SoE Summer School Fudan University
Mathematics of Deep Learning 22 Prof. Joan Bruna and Dr. Carles Domingo
Machine Learning Specialization Andrew Ng et al. - Coursera
Deep Learning Specialization Andrew Ng et al. - Coursera
Generative AI with Large Language Models Chris Fregly et al. - Coursera

Experience & Conferences

My Professional Journey

I'm incredibly grateful to have crossed paths with so many brilliant minds and kindred spirits throughout my journey. Each encounter has been a gift. These experiences have not only deepened my love for probability theory and machine learning, but also shown me how to connect the dots between theory and real-world impact.

ISBA World Meeting 2022 Montreal, Canada
STORFest 2023 Chapel Hill, NC
Extreme Value Analysis 2025 Chapel Hill, NC
ETHDenver 2025 Colorado, USA
SolanaBoston & ETH Boston 2025 Boston, USA

Posts

Random Notes

I randomly collect some of my notes — along with a selection of interesting interactions with AI :) You can explore a live preview below, or open the full collection on GitBook.

📖 View Full Notes on GitBook

Let's Connect!

Get in Touch

I'm always glad to connect—whether it's sharing ideas in mathematics, exploring collaborations, making friends and learning together, or enjoying tennis, basketball, skiing, poker, biking, photography, or road trips. I'd be delighted to meet and grow with people wherever we are.
🎾 🏀 🎿 🃏 🚴 📸 ⛰️