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Here are my previous academic and professional projects, which has these focused areas:

VR/AR | Game Dev | Quantitative Analysis | Software | ML(CV) | Robotics

Roblox: Branching narrative project

Producer, Tech Lead

A CMU project cooporated with Roblox (Fall 2022)


This is a Roblox Education sponsored project, aiming to discover the potential of Roblox in education area. In the project, we learnt from Twine - a widely used narrative building tool, and deliver a similar application that supports real-time editing and story building within Roblox, the leading content creation platform. 

As the lead programmer and producer, I am responsible for the key function development: dialogue system, and implemented the frontend and backend including server-side programming with Lua. We also communicate with the Roblox, participating in weekly meetings and reporting on progress during the delivery timeline of 13 weeks.

Cloud-based layout editor

Machine Learning Intern at Unity Technologies

ML Artistry Team, San Francisco, Summer 2022

Along with the tremendous growth of virtual worlds in games and movies, scene arranging has always been a time-consuming issue that takes a group of technical artists months to complete a high-quality scene.

Our goal is to implement layout(set-dressing) tools that greatly boost this process by providing real-time solution, including an optimized placement tool, a physic-based transform tool, and a intelligent assets palette. It can also be compatible with future XR devices interaction.

It is an early staged project. During the 13 weeks internship, we started by collecting critical needs and started by making system designs, then followed by prototyping UI features and implemented them. Also we experimented with different physics methods for one of the UI features as well.

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AIPI: AI and self-driving car

Lead Programmer

Collaborated with CMU Machine Learning & Computer Sciences Departments, Spring 2022


This is a project whose client is Boys and Girls Club of America and is currently pushed in use.

trAIn and gAIn is an interactive WebGL game to assist 14-16-year-old AIPI (Artificial Intelligence Pathways Institute) students understand the concepts of neural networks through interactive visualization of the self-driving car. 


16-726 Learning-Based Image Synthesis (ML, CV, GAN)

This course taught by Jun-Yan Zhu start from Computer Vision basics and then go further into content generation with machine learning methods. The primary focus for this course is Generative Adversial Network(GAN), but it take advantage of deep learning methods and digital image processing as well. In this course I received A-.

See the course page and my project writeups: proj1 | proj2 | proj3 | proj4

Meta Human: Motion Capture and Emotion Model

Algorithm Engineer Intern

Lilith Games, Summer 2021


Our algorithm team researched making the automatic workflow from a normal video containing human dancing to an avatar with the same body movement. 

Besides, we have implemented a virtual pet with an emotion model backend by Python Flask.

Cotton picking robot

Research Assistant

ShanghaiTech School Lab & Xinjiang Esquel, 2020-2021

After college graduation, I worked as Research Assistant in the ShanghaiTech robotics lab and worked in a research team with Xinjiang Esquel Group. We aim to develop a mobile cotton-picking platform, with the robot arm and precise cotton sense with the 3D camera and computer vision object detection algorithm. My main focus is the suction device on the end of the robot arm. We altogether iterated several versions of the suction device and I coded on the control part of the suction device. The device is a prototype based on Arduino and Raspberry Pi, and is connected to the ROS robot platform. Besides, I helped with developing and deploying detection methods on the robot.


Venture capital data analysis project

During my senior year in ShanghaiTech, I became a student research assistant in School of Entrepreneurship and management, ShanghaiTech University. My contribution is to analysis venture capital investment data collected by and run machine learning methods on them, aiming to find mechanism of how it is related with an important index: Economy Policy Uncertainty Index. Besides, we found this vary between investors depends on their education level, gender and some other personal attributes. 

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