这学期就只有一门课了： Introduction to Computer Vision Introduction to Computer Vision 也是TTIC的课程，课程质量也相当不错，教授Greg Shakhnarovich在课后回答问题非常认真，

这学期还有三门课： Deep Learning Systems AI Agents for Science Topics in Artificial Intelligence: Specification and Its Discontents: The Measurement Problem in AI Deep Learning Systems 说是将Deep Learning， 但大部分时间都在讲LLM，讲的内容也比较无聊

第三学期三门课是： Variational Methods in Image Processing Machine Learning Speech Technologies Variational Methods in Image Processing 看了标题里有图像处理就选了，但似乎上课内容和想象的区别有点大了。几乎完全是一门数学课，大部分作

第二学期三门课是： Mathematical Computation IIA: Convex Optimization Monte Carlo Simulation Learning, Decisions, and Limits Mathematical Computation IIA: Convex Optimization 计算数学轨必选，从凸集等概念一步步讲到对偶，不过算法部分讲的有点少，基本只讲了个障碍方法

第一个学期有三门课： Mathematical Computation I: Matrix Computation Course Modern Applied Optimization Inverse Problems and Data Assimilation: A Machine Learning Approach Matrix Computation 这个课是计算数学轨必选，感觉和国内上的数值代数比较像，稍微更难一点，还多了点编程

I’m Zhuyiheng Chu, a Master’s student in Computational and Applied Mathematics at the University of Chicago. I hold a Bachelor’s degree in Information and Computing Science from Zhejiang University. I have a passion for solving complex problems, as demonstrated by my participation in numerous programming and mathematical competitions. Competitions & Awards Finalist, 2023 Mathematical Contest In Modeling (Top 1%) Second Prize, 2022 Contemporary Undergraduate Mathematical Contest in Modeling (Top 2%) Gold Medal, 2021 Collegiate Computer System & Programming Contest, East China Site Gold Medal, 2021 China Collegiate Programming Contest, Guangzhou Site Silver Medal, 2021 ICPC Asia Shanghai Regional Contest Gold Medal, 2020 ICPC Asia Nanjing Regional Contest Gold Medal, 2020 China Collegiate Programming Contest, Mianyang Site I’ve also gained industry experience during my internship at Momenta, where I applied deep learning algorithms to predict optimal vehicle paths using multimodal data.