woojeong.jin (at) usc.edu
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Woojeong Jin

Ph.D. Candidate, Computer Science Department

I am currently seeking opportunities in industry research and engineering positions.

I am a final-year Ph.D. candidate in Computer Science at the University of Southern California. I am fortunate to be advised by Prof. Xiang Ren and supported by KEF Scholarship. I received B.S. in Electrical and Computer Engineering at Seoul National University. My undergraduate research was advised by Prof. U Kang.

My research interest lies in Multimodal Learning and Natural Language Processing.


Aug. 2018 - Present

Ph.D. in Computer Science

University of Southern California

Los Angeles, California

Feb. 2017

B.S. in Electrical and Computer Engineering

Seoul National University

Seoul, Korea


WinoViz: Probing Visual Properties of Objects Under Different States
Woojeong Jin, Tejas Srinivasan, Jesse Thomason, and Xiang Ren
arXiv preprint [ paper ]
GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions
Woojeong Jin, Subhabrata Mukherjee, Yu Cheng, Yelong Shen, Weizhu Chen, Ahmed Hassan Awadallah, Damien Jose, and Xiang Ren
arXiv preprint [ paper ]
Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning
Dong-Ho Lee, Kian Ahrabian, Woojeong Jin, Fred Morstatter, and Jay Pujara
EMNLP 2023 [ paper ]
Analyzing Norm Violations in Real-Time Live-Streaming Chat
Jihyung Moon*, Dong-Ho Lee*, Hyundong J. Cho, Woojeong Jin, Chan Young Park, Minwoo Kim, Jay Pujara and Sungjoon Park
EMNLP 2023 [ paper ]
Hybrid forecasting of geopolitical events
Daniel M Benjamin, Fred Morstatter, Ali E Abbas, Andres Abeliuk, Pavel Atanasov, Stephen Bennett, Andreas Beger, Saurabh Birari, David V Budescu, Michele Catasta, Emilio Ferrara, Lucas Haravitch, Mark Himmelstein, KSM Tozammel Hossain, Yuzhong Huang, Woojeong Jin, Regina Joseph, Jure Leskovec, Akira Matsui, Mehrnoosh Mirtaheri, Xiang Ren, Gleb Satyukov, Rajiv Sethi, Amandeep Singh, Rok Sosic, Mark Steyvers, Pedro A Szekely, Michael D Ward, and Aram Galstyan
AI Magazine [ paper ]
A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models
Woojeong Jin, Yu Cheng, Yelong Shen, Weizhu Chen, and Xiang Ren
ACL 2022 (long) [ paper | code ]
Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer
Woojeong Jin*, Dong-Ho Lee*, Chenguang Zhu, Jay Pujara, and Xiang Ren
ACL 2022 (long) [ paper | code ]
MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding
Woojeong Jin, Maziar Sanjabi, Shaoliang Nie, Liang Tan, Xiang Ren, and Hamed Firooz
EMNLP 2021 Findings (long) [ paper ]
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data
Woojeong Jin, Rahul Khanna, Suji Kim, Dong-Ho Lee, Fred Morstatter, Aram Galstyan, and Xiang Ren
ACL 2021 (long) [ paper | www | leaderboard ]
Modality-specific Distillation
Woojeong Jin, Maziar Sanjabi, Shaoliang Nie, Liang Tan, Xiang Ren, and Hamed Firooz
MAI@NAACL 2021 [ paper ]
Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs
Woojeong Jin, Meng Qu, Xisen Jin, and Xiang Ren
EMNLP 2020 (long) [ paper | code ]
Accurate Relational Reasoning in Edge-labeled Graphs by Multi-Labeled Random Walk with Restart
Jinhong Jung, Woojeong Jin, Ha-myung Park, and U Kang
World Wide Web Journal [ paper ]
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
Sankalp Garg*, Navodita Sharma*, Woojeong Jin, and Xiang Ren
IJCAI 2020 [ paper | code ]
Collaborative Policy Learning for Open Knowledge Graph Reasoning
Cong Fu, Tong Chen, Meng Qu, Woojeong Jin, and Xiang Ren
EMNLP 2019 (long) [ paper | code ]
Recurrent Event Network for Reasoning over Temporal Knowledge Graphs
Woojeong Jin, Changlin Zhang, and Xiang Ren
ICLR-RLGM 2019 [ paper ]
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Weizhi Ma, Min Zhang, Yue Cao, Woojeong Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, and Xiang Ren
TheWebConf 2019 [ paper | code ] (18% Acceptance Rate)
Supervised and Extended Restart in Random Walks for Ranking and Link Prediction in Networks
Woojeong Jin, Jinhong Jung, and U Kang
PLOS ONE [ paper | www (code and data) ]
Random Walk Based Ranking in Signed Social Networks: Model and Algorithms
Jinhong Jung, Woojeong Jin, U Kang, and Lee Sael
KAIS [ paper | www (code and data) ]
Fast and Accurate Random Walk with Restart on Dynamic Graphs with Guarantees
Minji Yoon, Woojeong Jin, and U Kang
TheWebConf 2018 [ paper ] (14.8% Acceptance Rate)

Work Experience

Jan. 2022 - Apr. 2022

Research Intern, Microsoft Research, Redmond, Washington

June 2021 - Jan. 2022

Research Intern, Microsoft Azure AI, Redmond, Washington

May 2020 - Aug. 2020

Research Intern, Meta AI, Menlo Park, California

Jan. 2016 - Apr. 2018

Research Assistant, Data Mining Lab., SNU

June 2014 - Aug. 2014

Research Intern, Creative Innovation Center, LG electronics