Short Bio

Welcome to my personal webpage! My name is Yang Xiao (Chinese: 肖阳). I am currently a Researcher at TikTok. Prior to that, I earned my Master’s degree in Computer Science from Northeastern University, where I was supervised by Ryan Rad. I also hold a Bachelor’s degree from Beihang University.

My research interests mainly focus on 2D computer vision, including but not limited to image classification/detection/segmentation, semi-supervised learning, contrastive learning, human image generation, diffusion model, etc.

📖 Educations

• 2023.01 - 2024.08, Master, Khoury College, Northeastern University
• 2015.09 - 2019.07, Undergraduate, ShenYuan Honors College, Beihang University

💻 Experience

• 2024.04 - now, TikTok, Vancouver, Canada
• 2020.07 - 2021.05, DiDi, Beijing, China
• 2019.12 - 2020.07, 4paradigm, Beijing, China
• 2019.06 - 2019.09, Haier Uhome, Beijing, China
• 2018.09 - 2018.12, ZhenRobotics, Beijing, China

🎓 Publications

1. Yang Xiao, Yunke Li, Shaoyujie Chen, Hayden Barker, and Ryan Rad. "Do you actually need an LLM? Rethinking language models for customer reviews analysis". Artificial Intelligence Review, 2025. [Paper] [Code]

• Investigated and compared the performance and computational costs of SLMs and LLMs in sentiment polarity classification and correlation analysis.

📝 Teaching

• Spring 2024: Teaching Assistant
  • Northeastern University, Vancouver, Canada
  • Course: Foundation of AI
  • Supervisor: Professor Richard Hoshino
• Fall 2023: Teaching Assistant
  • Northeastern University, Vancouver, Canada
  • Course: Programing Desgin Paradigm
  • Supervisor: Professor Jack Thomas

🔧 Projects

Pet Avatar Customized and Animated Generation via Diffusion Model

Apr. 2024
Master's capstone
code page

Built a pipeline aiming at generating pet images and videos in a personalized and customized way. To better preserve the original pet features, we followed DreamBooth + LoRA paradigm; furthermore, we inserted the LoRA weight into AnimateDiff framework to animate the original pet.

Real-time Interactive Online-Classroom

Nov. 2023
Course project
code

Built a online classroom where students and teachers can chat and draw some sketches in real-time. The tech stack is based on Typescript, Node.js, React and Redis. To ensure real-time and low-lantency, communication between front-end and back-end was implemented via websocket.

Lane Segementation Challenge on ApolloScape Benchmark

Dec. 2020
6/94 place on lane segementation track

Combined multiple augmentation strategies, class-balanced loss functions and a sementic segmention Network(HRNet+OCR) to parse real-world image.

Chinese Artificial Intelligence Competition

Aug. 2019
3rd place on same source image retrieval category

Used ImageNet-pretrained backbone to extract image feature and trained a MLP to obtained the image embedding with triple loss.

3D Reconstruction with an Two-stage Stereo Matching Approach

Jan. 2019
Bachelor's thesis

A Pytorch implementation of CRL-Net and disparity map denoising.