Welcome, my name is Zexi Huang. I am a Machine Learning Scientist at TikTok Recommendation. I obtained my PhD in Computer Science at the Department of Computer Science, University of California, Santa Barbara (UCSB) in April 2023. Prior to that, I received my Bachelor's in Computer Science and Technology with the highest honor at Yingcai Honors College, University of Electronic Science and Technology of China (UESTC), in 2018. My research focuses on machine learning and data mining on information-rich data. At TikTok, I work on developing state-of-the-art machine learning solutions for the billion-scale recommendation system of TikTok Live. My PhD dissertation at Dynamic Networks: Analysis and Modeling Lab, UCSB, is on representation learning for information-rich graphs, with Prof. Ambuj Singh as my advisor. Previously, I had multiple applied science internships at Books Tech, Amazon, where I leveraged graph-based machine learning techniques to solve large-scale industry problems including fraud detection, inventory management, and content discovery. I also interned at Computational Intelligence Lab, Nanyang Technological University, working with Prof. Sinno Jialin Pan on transfer learning framework for community detection in multiplex networks, as an undergraduate. Feb. 2024 May. 2023 Apr. 2023 Sep. 2018 - Apr. 2023 Sep. 2014 - Jun. 2018 Feb. 2016 - Jun. 2016 May. 2023 - Present Jun. 2022 - Sep. 2022 Jun. 2021 - Sep. 2021 Jun. 2020 - Sep. 2020 Sep. 2017 - Feb. 2018 [AAAI-2024] Aritra Bhowmick, Mert Kosan, Zexi Huang, Sourav Medya, Ambuj Singh, Sourav Medya. DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization. AAAI Conference on Artificial Intelligence, 2024. [Code] [WSDM-2023] Zexi Huang*, Mert Kosan*, Sourav Medya, Sayan Ranu, Ambuj Singh. Global Counterfactual Explainer for Graph Neural Networks. ACM International Conference on Web Search and Data Mining, 2023. (*: equal contribution) [Code] [Slides] [Talk] [WSDM-2022] Zexi Huang, Arlei Silva, Ambuj Singh. POLE: Polarized Embedding for Signed Networks. ACM International Conference on Web Search and Data Mining, 2022. [Code] [Poster] [Slides] [Talk] [KDD-2021] Zexi Huang, Arlei Silva, Ambuj Singh. A Broader Picture of Random-walk Based Graph Embedding. ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021. [Code] [Poster] [Slides] [Talk] [Talk (in Chinese)] [Preprint] Zexi Huang, Mert Kosan, Arlei Silva, Ambuj Singh. Link Prediction without Graph Neural Networks. arXiv preprint arXiv:2305.13656, 2023. [Code] [Preprint] Wei Ye, Zexi Huang, Yunqi Hong, Ambuj Singh. Graph Neural Diffusion Networks for Semi-supervised Learning. arXiv preprint arXiv:2201.09698, 2022. [Code] Apr. 2021 - Apr. 2023 May. 2021 - Feb. 2023 Oct. 2021 - Aug. 2022 Oct. 2020 - Aug. 2021 Apr. 2020 - Oct. 2021 Sep. 2018 - Feb. 2021 Jan. 2020 - Aug. 2020 Jul. 2016 - Aug. 2017 2020 - 2021 Fall 2019 Spring 2019 Winter 2019 Fall 2018 Feb. 2023 Feb. 2022 Sep. 2020 Sep. 2018 Sep. 2018 Jun. 2018 Jun. 2018 Dec. 2017 Dec. 2017 Dec. 2017 Oct. 2017 May. 2017 Dec. 2016 Dec. 2015 Dec. 2015 Dec. 2015
Zexi Huang (黄泽熙)
Machine Learning Scientist at TikTok Recommendation
News
We presented our work on GNN-based attributed graph clustering at AAAI'24!
I joined TikTok as a Machine Learning Scientist and will be working on TikTok Live Recommendation!
I defended my PhD dissertation on Learning Representations for Information-rich Graphs!
Education
College of Engineering, University of California, Santa Barbara
Doctor of Philosophy and Master of Science in Computer Science
Yingcai Honors College, University of Electronic Science and Technology of China
Bachelor of Engineering in Computer Science and Technology (Honors)
College of Electrical and Computer Engineering, National Chiao Tung University
Exchange Student
Work Experience
Machine Learning Scientist, Live Recommendation, TikTok
Billion-scale Machine Learning for TikTok Live Recommendation
Applied Scientist Intern, Books Tech, Amazon
Stochastic Inventory Management for Print-On-Demand and Graph-based Text Classification for Content Intelligence
Applied Scientist Intern, Books Tech, Amazon
Graph-based Fraud Detection in Kindle Direct Publishing
Applied Scientist Intern, Books Tech, Amazon
Graph-based Fraud Detection in Kindle Direct Publishing
Research Intern, Computational Intelligence Lab, Nanyang Technological University
Transfer Learning for Community Detection in Multiplex Networks
Publications
Research Experience
Multiscale Community Detection Based on Pointwise Mutual Information
Advisor: Prof. Ambuj Singh, Collaborator: Manu Kondapaneni, Arlei Silva
Link Prediction without Graph Neural Networks
Advisor: Prof. Ambuj Singh, Collaborators: Mert Kosan, Arlei Silva
Global Counterfactual Explanation for Graph Neural Networks
Advisor: Prof. Ambuj Singh, Collaborators: Mert Kosan, Sourav Medya, Sayan Ranu
Signed Embedding for Polarized Graphs
Advisor: Prof. Ambuj Singh, Collaborator: Arlei Silva
Multiscale Graph Convolution via Neural Diffusions
Advisor: Prof. Ambuj Singh, Collaborator: Wei Ye, Yunqi Hong
Graph Representation Learning Based on Random-walks
Advisor: Prof. Ambuj Singh, Collaborator: Arlei Silva
Prospect Theory for Group Decision Making Dynamics
Advisor: Prof. Ambuj Singh, Collaborator: Mert Kosan
Overlapping Community Detection Based on Game Theory-incorporated Label Propagation Dynamics
Advisor: Prof. Junming Shao
Teaching Experience
Lead Teaching Assistant
Department of Computer Science, UCSB
Teaching Assistant, CS 130A: Data Structures and Algorithms
Department of Computer Science, UCSB
Co-designer and Instructor, Machine Learning Workshops
LMU/UCSB Junior Nanotech Network PhD Student Exchange and Symposium
Teaching Assistant, CS 8: Introduction to Computer Science
Department of Computer Science, UCSB
Teaching Assistant, CS 174A/174N: Fundamentals of Database Systems
Department of Computer Science, UCSB
Honors & Awards
Top 10 best papers of WSDM'23 and best paper in the MLoG workshop
Top 10 out of 123 accepted papers and 690 valid submissions
WSDM NSF Travel Award
$300
UCSB Computer Science Lead Teaching Assistant Fellowship
$3,225
Computer Science Outstanding Scholar Fellowship at UCSB
6%, top four out of 63 admitted PhD students, $10,000
Computer Science Academic Excellence Fellowship at UCSB
$2,000
Outstanding Bachelor Thesis Award of UESTC
10%
Tang Lixin Scholarship for Studying Abroad
$1,453
The Most Outstanding Students Award of UESTC
0.2%, top 10 out of 5,000 seniors, $2,180
Honorary Graduate of Sichuan Province
1%, top one in Yingcai Honors College
Honorary Graduate of UESTC
10%, top twelve in Yingcai Honors College
National Scholarship of China
0.2%, top two in Yingcai Honors College, $1,162
National English Competition for College Students of China 2017
0.1%, Special Prize in National Final (Level C, for Non-English professionals)
People's Scholarship of UESTC
4%, Special Class, top four in Yingcai Honors College, $436
Tang Lixin Scholarship of Yingcai Honors College
1%, First Prize, top one in Yingcai Honors College, $4,359
Tang Lixin Scholarship of UESTC
0.2%, $1,453 per year until graduation
The 7th Chinese Mathematics Competitions
0.05%, 1st out of 1819 selected candidates in Sichuan Province
Academic Services
Registration Chair
Program Committee
Reviewer
Representative
General Judge