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
Broadly interested in the theoretical study of large stochastic systems, especially on rare events and heavy tails
Understanding the probabilistic underpinnings of generative models and their theoretical guarantees.
Building decentralized systems, aligning consensus and incentives with the transformative potential of DeFi, InfoFi, and AI agents.
wancheng@bu.edu
Office 338 CDS
Department of Mathematics and Statistics
Boston University
665 Commonwealth Ave
Boston, MA 02215
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.
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.
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.
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.
🎾 🏀 🎿 🃏 🚴 📸 ⛰️