Hi, my name is Run Zhang.
你好，我是张润 — welcome to my page.
About
I'm a software engineer working on AI. Most of what I do sits where machine learning meets real systems — training and evaluating models in Python and PyTorch, then making them run reliably and fast once they leave the notebook.
I've built perception for autonomous vehicles, researched graph neural networks for text, and worked on video prediction. Lately I've been going deeper on large language models and the engineering around them: retrieval, agents, evaluation, and CUDA for squeezing more out of the hardware. I'm drawn to problems that are both useful and genuinely hard.
Education
- MS Information SystemsNew York UniversitySeptember 2023 – May 2025
- MSc Artificial IntelligenceUniversity of SouthamptonSeptember 2019 – October 2020
- BEng Software EngineeringGuangzhou UniversitySeptember 2015 – July 2019
Projects
Autonomous Surface Vehicle Controller
My Master's dissertation focused on implementing Evolutionary Algorithms to develop a vehicle controller, which selected actions based on the current state of the environment or the vehicle itself. Additionally, the project explored deep reinforcement learning and compared the two approaches.
- Evolutionary Algorithms
- Deep RL
- C++
Graph Attention Networks with automatic graph generation on text data
While working with text data, I realized that structured data is commonly represented using relational graphs, where two nodes are connected if they are related. This observation naturally led to the idea of exploring whether deep learning models can be trained to generate these relational graphs.
- Graph Neural Networks
- LSTM
- NLP
Predicting the future semantic masks of moving objects
For the deep learning course at NYU, I worked with two classmates to implement the open-source SimVP model on a video semantic prediction task, then explored VQ-VAE pre-training as a follow-up.
- Video Prediction
- Segmentation
- PyTorch