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Post-Training/Sythetic Data/Evaluation for LLMs/VLMs/Agents
I am leading the Ecosystem and User Experience algorithm team at TikTok Business Integrity, where we build strong capabilities to detect risks and user experience issues on TikTok’s monetization ecosystem. We strive for making TikTok safe to gain user trust, enabling sustainable business growth. Prior to TikTok, I was a Research Scientist at Gaussian Robotics, where worked on various topics on intelligent robotics, such as visual SLAM related deep learning algoirthms, multi-task learning and efficient deep learning model inference on edge-devices. I also spent time at ViSenze and Tuputech, leading various computer vision projects. I obtained my bachelor’s degree in Computing Science from the University of Glasgow in 2016, after spending 3 wonderful years in Scotland, I also obtained a bachelor’s degree in Eletronics Engineering from Sun Yat-Sen University in the same year. I have broad interests in AI. Currently, I am working on building strong LLMs and MLLMs to empower TikTok’s moderation system via both pre-training and post-training. I am also interested in 3D computer vision problems and building systems/algorithms for autonomous robotics that efficiently interact with our physical world.
University of Glasgow
Bachelor of Science (BSc) Honour, Computer Software Engineering
January 1, 2013 – January 1, 2016
TikTok
Staff Applied Scientist (Technical Lead)
November 1, 2023 – Present
Singapore · On-site
Gaussian Robotics
Staff Research Scientist
November 1, 2021 – November 1, 2023
Singapore
TikTok
Senior Research Scientist - AI Lab
November 1, 2020 – November 1, 2021
Singapore
ViSenze - AI for Visual Commerce
Research Engineer
June 1, 2019 – November 1, 2020
Singapore
TUPU Technology Co., Ltd
Senior Research Software Engineer (Algorithm Team Lead)
July 1, 2017 – June 1, 2019
Guangzhou-Foshan Metropolitan Area
TUPU Technology Co., Ltd
Research Software Engineer
April 1, 2016 – July 1, 2017
Guangzhou-Foshan Metropolitan Area
IBM
Software Engineer Intern
June 1, 2015 – September 1, 2015
Greenock, Scotland, United Kingdom
Cultural Fit Analysis
The candidate has worked at diverse companies ranging from large tech (TikTok, IBM) to specialized AI firms (Gaussian Robotics, ViSenze, TUPU Technology). This breadth of experience suggests adaptability and an ability to thrive in different organizational cultures. Their involvement in research and competitive achievements indicates a proactive and results-oriented mindset, which aligns well with innovative tech environments.
Soft Skills & Operational Fit
The candidate's experience as a technical lead and research scientist suggests strong problem-solving, innovation, and collaboration skills. Their work on MLOps and HIL frameworks indicates an understanding of operationalizing ML models and ensuring quality.