Email: jieyuz [at] usc [dot] edu
Office: USC PHE #332
Last Update: 08/22/2023
Jieyu Zhao 赵洁玉
Gabilan Assitant Professor
Thomas Lord Department of Computer Science, USC
Jieyu Zhao is an Assistant Professor of Computer Science Department at University of Southern California. Prior to that, she was an NSF Computing Innovation Fellow at University of Maryland, College Park, working with Prof. Hal Daumé III. Jieyu received her Ph.D. from Computer Science Department, UCLA, where she was advised by Prof. Kai-Wei Chang. Her research interest lies in fairness of ML/NLP models. Her paper got the EMNLP Best Long Paper Award (2017). She was one of the recipients of 2020 Microsoft PhD Fellowship and has been selected to participate in 2021 Rising Stars in EECS workshop. Her research has been covered by news media such as Wires, The Daily Mail and so on. She was invited by UN-WOMEN Beijing on a panel discussion about gender equality and social responsibility. Her CV is available here.
📬 I'm actively looking for strong and motivated students. We welcome applicants from diverse backgrounds. If you are interested in my research, please read 📍this first.
🐾 Research
I am broadly interested in research about how to get machines to understand and respond to human languages (natural language processing & machine learning). A few questions that drive my recent research are:
- how can we get models to efficiently learn knowledge?
- how can we reduce potential harms learned by the model?
- how can we advance better models and humans collaborations?
📰 Recent News
- [10/2022] One paper was accepted at EMNLP 2022 Findings. Check it out!
- [10/2022] We got a paper accepted at AACL. Check it out!
- [10/2022] We will do a "Trustworthy and Responsible AI" tutorial at AAAI 2023. Stay tuned!
- [04/2022] I will join USC CS as an Assistant Professor in 2023 Fall! 🥳 Let me know if you are interested in working with me! 🎉
- [01/2022] I'm here at UMD now. Feel free to drop by or send me an email for discussions!
🗞️️ More News
- [11/2021] I passed my defense! 🎓 🤩
- [08/2021] I'm excited to accepted into 2021 Rising Stars in EECS. See you in October!
Publications (selected)
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers
Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang. EMNLP Findings, 2022.
On Measures of Biases and Harms in NLP
Sunipa Dev, Emily Sheng, Jieyu Zhao, Aubrie Amstutz, Jiao Sun, Yu Hou, Mattie Sanseverino, Jiin Kim, Akihiro Nishi, Nanyun Peng, and Kai-Wei Chang. AACL, 2022.
- Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?
Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, and Kai-Wei Chang. ACL Findings, 2021.
-
Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation
Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, and Cho-Jui Hsieh. NAACL 2021.
- LOGAN: Local Group Bias Detection by Clustering
Jieyu Zhao and Kai-Wei Chang. EMNLP 2020.
- Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
Jieyu Zhao, Subhabrata Mukherjee, Saghar Hosseini, Kai-Wei Chang, Ahmed Hassan Awadallah.
Conference of the Association for Computational Linguistics. ACL 2020.
- Mitigating Gender Bias Amplification in Distribution by Posterior Regularization
Shengyu Jia*, Tao Meng*, Jieyu Zhao, Kai-Wei Chang.
Conference of the Association for Computational Linguistics. ACL 2020.
- "The Boating Store Had Its Best Sail Ever": Pronunciation-attentive Contextualized Pun Recognition
Yichao Zhou, Jyun-Yu Jiang, Jieyu Zhao, Kai-Wei Chang, Wei Wang
Conference of the Association for Computational Linguistics. ACL 2020.
- Examining Gender Bias in Languages with Grammatical
Gender
Pei Zhou, Weijia Shi, Jieyu Zhao, Kuan-Hao Huang, Muhao Chen, Ryan Cotterell, Kai-Wei Chang.
Conference on Empirical Methods in Natural Language Processing. EMNLP 2019.
- Balanced Datasets Are Not Enough: Estimating and Mitigating
Gender Bias in Deep Image Representations
Tianlu Wang, Jieyu Zhao, Mark Yatskar, Kai-Wei Chang, Vicente Ordonez.
International Conference on Computer Vision. ICCV 2019.
- Gender Bias in Contextualized Word Embeddings [video] [slides]
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, Kai-Wei Chang.
North American Chapter of the Association for Computational Linguistics. NAACL 2019.
- Learning Gender-Neutral Word Embeddings [code]
Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, Kai-Wei Chang
Conference on Empirical Methods in Natural Language Processing. EMNLP 2018.
- Gender Bias in Coreference Resolution: Evaluation and
Debiasing Methods [code] [podcast]
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.
North American Chapter of the Association for Computational Linguistics. NAACL 2018.
- Men Also Like Shopping: Reducing Gender Bias Amplification
using Corpus-level Constraints [code], [slides]
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, Kai-Wei Chang.
Conference on Empirical Methods in Natural Language Processing. EMNLP 2017. (Best Long Paper Award)
Press: Wired: Machines Taught By Photos Learn a Sexist View of Women
Talks
- Tutorial: Trustworthy and Responsible AI. AAAI 2023.
- Detect and mitigate bias in NLP. AKBC KG-BIAS work shop, 2020.
Education / Experience
- Postdoc, University of Maryland, College Park. 2022.01 - 2023.06
- Ph.D., University of California, Los Angeles. 2017.9 - 2021.12
- Google Research Intern, NYC. 2021.06 - 2021.09
- AI2 Research Intern, Seattle. 2020.09 - 2020.12
- Microsoft Research Intern, Redmond. 2020.06 - 2020.09
- Microsoft Research Intern, Redmond. 2019.06 - 2019.09
Awards (selected)
- CI Fellowship, 2021
- EECS Rising Star, 2021
- Microsoft PhD Fellowship, 2020
- SoCalNLP Symposium Best Poster Award, 2018
- UCLA Graduate Division Fellowships, 2017
- EMNLP 2017 Best Long Paper Award, 2017
- Outstanding Graduate of Beijing City, 2016