Publications

GiGL: Large-Scale Graph Neural Networks at Snapchat

Published in The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025

Tong Zhao, Yozen Liu, Matthew Kolodner, Kyle Montemayor, Elham Ghazizadeh, Ankit Batra, Zihao Fan, Xiaobin Gao, Xuan Guo, Jiwen Ren, Serim Park, Peicheng Yu, Jun Yu, Shubham Vij, Neil Shah

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Improving Embedding-Based Retrieval in Friend Recommendation with ANN Query Expansion.

Published in The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024

Pau Kung, Zihao Fan, Tong Zhao, Yozen Liu, Zhixin Lai, Jiahui Shi, Yan Wu, Jun Yu, Neil Shah, Ganesh Venkataraman

Lessons Learnt from Building Friend Recommendation Systems.

Published in The 17th ACM International Conference on Web Search and Data Mining Conference (WSDM), 2024

Jun Yu

Embedding Based Retrieval in Friend Recommendation.

Published in Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023

Jiahui Shi, Vivek Chaurasiya, Yozen Liu, Shubham Vij, Yan Wu, Satya Kanduri, Neil Shab, Peicheng Yu, Nik Srivastava, Lei Shi, Ganesh Venkataraman, and Jun Yu

Graph Neural Networks for Friend Ranking in Large-scale Social Platforms.

Published in Proceedings of the Web Conference (WWW), 2021

Aravind Sankar, Yozen Liu, Jun Yu, and Neil Shah

Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves?

Published in PLoS One, 2015

Bayesian and empirical Bayesian forests.

Published in The 32nd International Conference on Machine Learning (ICML), 2015

Matt Taddy, Chun-Sheng Chen, Jun Yu, and Mitch Wyle

Latent Dirichlet Allocation based Diversified Retrieval for E-commerce Search.

Published in The 7th ACM International Conference on Web Search and Data Mining Conference (WSDM), 2014

Jun Yu, Sunil Mohan, Duangmanee (Pew) Putthividhya, and Weng-Keen Wong

Clustering Species Accumulation Curves to Identify Skill Levels of Citizen Scientists Participating in the eBird Project.

Published in the Twenty-Sixth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2014

Jun Yu, Weng-Keen Wong, and Steve Kelling

The eBird enterprise: an integrated approach to the development and application of citizen science.

Published in Biological Conservation, 2014

HC-Search for Multi-Label Prediction: An Empirical Study.

Published in The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014

Janardhan Rao Doppa, Jun Yu, Chao Ma, Alan Fern and Prasad Tadepalli

A Latent Variable Model for Discovering Bird Species Commonly Misidentified by Citizen Scientists.

Published in The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014

Jun Yu, Rebecca Hutchinson, and Weng-Keen Wong

Machine Learning for Improving the Quality of Citizen Science Data.

Published in Ph.D Dissertation at Oregon State University, 2013

Jun Yu

Clustering Species Accumulation Curves to Identify Groups of Citizen Scientists with Similar Skill Levels.

Published in The Twenty-seventh Conference on Neural Information Processing Systems (NIPS) Workshop, 2013

Jun Yu, Weng-Keen Wong, and Steve Kelling

Modeling Misidentification of Bird Species by Citizen Scientists.

Published in The Twenty-seventh Conference on Neural Information Processing Systems (NIPS), 2013

Jun Yu, Rebecca A. Hutchinson, and Weng-Keen Wong

eBird: A Human/Computer Learning Network for Biodiversity Conservation and Research.

Published in AI magazine, 2013

Steve Kelling, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Jeff Gerbracht, Daniel Fink, and Carla Gomes

eBird: A Human/Computer Learning Network for Biodiversity Conservation and Research.

Published in The Twenty-fourth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2012

Steve Kelling, Jeff Gerbracht, Daniel Fink, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, and Carla Gomes.

Automated Data Verification in a Large-scale Citizen Science Project: a Case Study.

Published in The IEEE International Conference on eScience (eScience), 2012

Jun Yu, Steve Kelling, Jeff Gerbracht, and Weng-Keen Wong

Multi-label Classification for Species Distribution Modeling.

Published in The International Conference on Machine Learning (ICML) Workshop, 2011

Jun Yu, Weng-Keen Wong, Tom Dietterich, Julia Jones, Matthew Betts, Sarah Frey, Susan Shirley, Jeffery Miller, and Matt White

Emergent Filters: Automated Data Verification in a Large-Scale Citizen Science Project.

Published in The IEEE International Conference on eScience Workshop, 2011

Steve Kelling, Jun Yu, Jeff Gerbracht, and Weng-Keen Wong

Crowdsourcing Citizen Science Data Quality with a Human-Computer Learning Network.

Published in The Conference on Neural Information Processing Systems (NIPS) Workshop, 2010

Andrea Wiggins, Jeff Gerbracht, Carl Lagoze, Jun Yu, Weng-Keen Wong, and Steve Kelling

Modeling Experts and Novices in Citizen Science Data for Species Distribution Modeling.

Published in The 10th IEEE International Conference on Data Mining (ICDM), 2010

Jun Yu, Weng-Keen Wong, and Rebecca A. Hutchinson

Learning Algorithms for Link Prediction based on Chance Constraints.

Published in The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2010

Janardhan Rao Doppa , Jun Yu, Prasad Tadepalli, and Lise Getoor

Chance-Constrained Programs for Link Prediction.

Published in The Conference on Neural Information Processing Systems (NIPS) Workshop, 2009

Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, and Lise Getoor