Ziyi Kou

I am a Ph.D. student of Computer Science and Engineering (CSE) at University of Notre Dame. My advisor is Dr. Xiangliang Zhang. My research focuses on trustworthy deep learning, graph neural network and recommender system. I got my master's degree of Computer Science from University of Rochester and my bachelor's degree of Software Engineering from Chongqing University.

Education

Aug. 2020 - Present

University of Notre Dame
Ph.D. Student, Computer Science and Engineering Courses: Text Mining, Algorithm and Complexity, Operating System, Computer Graphic
Aug. 2018 - May 2020

University of Rochester
M.S. Computer Science Courses: Artificial Intelligence, Adv. Topic of Computer Vision, Intro. of Statistics, Machine Learning
Sept. 2014 - Jun. 2018

Chongqing University, China
B.S. Software Engineering Courses: Java Programming, Data Mining with Python, Web Development, Database Design, Android Programming

Oct. 2022 - Feb. 2023

Machine Learning Intern
Instacart Graph Based Personalized List Generation
May. 2022 - Aug. 2022

Machine Learning Intern
Godaddy Inc. Multi-relational Graph Based Recommendation
Oct. 2019 - Apr. 2020

Research Assistant
University of Rochester Weakly Supervisied Image Object Localization
Jun. 2019 - Sept. 2019

Deep Learning Intern
Suzhou Institute of Artificial Intelligence, Shanghai Jiao Tong University SmartTV embedded Asian Celebrity Face Recognition

3rd Winner of Ebay University Machine Learning Competition - Simi-Supervised Name Entity Recognition, 2023
Winner of Sequential Dynamic Molecular Prediction AI Competition, Argonne US National Lab, 2022
Bronze Medal for H&M Fashion Recommendations, Kaggle 2022
PhD Student Travel Grants, IEEE INFOCOM and IEEE BigData
Graduate Tuition Scholarship, University of Rochester 2018

A Crowd-AI Duo Relational Graph Learning Framework Towards Social Impact Aware Photo Classification, 2nd Author, AAAI'23
A Web Crowdsourcing Based Face Partition Approach Towards Privacy-Aware Face Recognition, 1st Author, WWW'22
A Duo-Generative Approach to Explainable Multimodal COVID-19 Misinformation Detection, co-1st Author, WWW'22
Human-AI Interaction Towards Natural Language Explanation based COVID-19 Misinformation Detection, 1st Author, IJCAI'22
A Crowdsourcing Multi-Modal Knowledge Graph Approach to Explainable Fauxtography Detection, 1st Author, CSCW'22
A Hierarchical Crowdsource Knowledge Graph Approach to Explainable COVID-19 Misinformation Detection, 1st Author, GROUP'22
Improve CAM with Auto-adapted Segmentation and Co-supervised Augmentation, 1st Author, WACV'21
ExgFair: A Crowdsourcing Data Exchange Approach To Fair Human Face Datasets Augmentation, 1st Author, BigData'21
Faircrowd: Fair human face dataset sampling via batch-level crowdsourcing bias inference, 1st Author, IWQOS'21
What comprises a good talking-head video generation, co-1st Author, CVPRW'20
Exfaux: A weakly supervised approach to explainable fauxtography detection, 1st Author, BigData'20