Ziyi Kou

I am a Ph.D. candidate of Computer Science and Engineering (CSE) at University of Notre Dame. My advisor is Dr. Xiangliang Zhang. My research focuses on multimodal generative AI, trustworthy computer vision and graph neural networks. 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

Dec. 2023 - Mar. 2024

Research Scientist Intern
Meta TBD
June. 2023 - Aug. 2023

Applied Scientist Intern
Amazon Graph Neural Network Based Customer Insotck Value Estimation. Received return incline offer.
Oct. 2022 - Feb. 2023

Machine Learning Engineer Intern
Instacart Graph Based Next-Basket Recommendation. Published at CIKM2023.
May. 2022 - Aug. 2022

Machine Learning Engineer Intern
Godaddy Inc. Multi-relational Graph Based Recommendation. Received return intern offer.

Notre Dame CSE Outstanding Research Award, 2023
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

Modeling Sequential Collaborative User Behaviors for Seller-aware Next Basket Recommendation, 1st Author, CIKM'23
A Controllable Prompt Adversarial Attacking Framework for Black-Box Text Guided Image Generation Models, 1st Author, IJCAI'23
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