Sherry Tongshuang Wu Download PDF

HCII, School of Computer Science Carnegie Mellon University Newell-Simon Hall 3525 Pittsburgh, PA 15213
+1 206-910-2784 sherryw@cs.cmu.edu http://cs.cmu.edu/~sherryw @tongshuangwu

Academic Experience

2022–
Carnegie Mellon University, Assistant Professor

Human-Computer Interaction Institute (CMU HCII)

Language Technology Institute (CMU LTI)

2016–22
University of Washington, Research Assistant
with Jeffrey Heer, Dan Weld

Pitfalls in status quo human-AI interactions.

Principles and tools for enhanced NLP model analysis.

Controllable generators for model analysis and improvement.

Education

2016–22
Ph.D. in Computer Science and Engineering
University of Washington, Seattle, WA
Thesis: Interactive AI Model Debugging and Correction
Advisor: Jeffrey Heer, Dan Weld
Committee: Marco Tulio Ribeiro, Noah Smith, Mari Ostendorf
2016–18
M.S. in Computer Science and Engineering
University of Washington, Seattle, WA
2012–16
B.Eng. in Computer Science and Engineering
Hong Kong University of Science and Technology, Hong Kong, Hong Kong
Advisor: Huamin Qu
2014
Exchange student in Computer Science and Engineering
University of Michigan, Ann Arbor, MI

Industry Experience

2021
Google Brain/PAIR, Research Intern & Part-time Student Researcher
with Carrie Cai, Michael Terry

Transparent & controllable human-AI collaborations via multi-step problem-solving.

2019
Microsoft Research, Research Intern
with Marco Tulio Ribeiro

Behavioral testing for NLP models covering broad model capabilities.

2018–19
Apple Inc., Full-time Intern & Part-time Intern
with Chris DuBois, Kayur Patel, Kanit Wongsuphasawat, Donghao Ren, Charlie Maalouf

Structural analysis for unstructured text datasets.

2017
Microsoft Research, Research Intern
with Bongshin Lee, Ece Kamar, Saleema Amersh

Uncertainty-aware data labeling and visual refinement.

2015
Microsoft Research Asia, Research Intern
with Weiwei Cui

De-cluttering statistical graphs.

Publications

* denotes equal contribution

Manuscripts and Pre-prints

2021
P.1
Kaustubh D Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahendiran, Simon Mille, Ashish Srivastava, Samson Tan, Tongshuang Wu, Jascha Sohl-Dickstein, Jinho D Choi, Eduard Hovy, Ondrej Dusek, Sebastian Ruder, et al.. NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. In arXiv:2112.02721.
arXiv 2021

Peer-reviewed Conference and Journal Publications

2023
P.2
Tongshuang Wu, Hua Shen, Jeffrey Heer, Daniel S. Weld, Marco Tulio Ribeiro. ScatterShot: Interactive In-context Example Curation for Text Transformation. In ACM Conference on Intelligent User Interfaces.
IUI 2023
2022
P.3
Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zheng, Toby Jia-Jun Li, Nora Bradford, Branda Sun, Tran Bao Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer. Fantastic Questions and Where to Find Them: FairytaleQA -- An Authentic Dataset for Narrative Comprehension. In the 60th Annual Meeting of the Association for Computational Linguistics.
ACL 2022
P.4
Tongshuang Wu*, Alexis Ross*, Hao Peng, Matthew E. Peters, Matt Gardner. Tailor: Generating and Perturbing Text with Semantic Controls. In the 60th Annual Meeting of the Association for Computational Linguistics.
ACL 2022
P.5
Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Toby Jia-Jun Li, Mo Yu, Ying Xu. It is AI's Turn to Ask Humans a Question: Question and Answer Pair Generation for Children Storybooks with FairytaleQA Dataset. In the 60th Annual Meeting of the Association for Computational Linguistics.
ACL 2022
P.6
Hua Shen, Tongshuang Wu, Wenbo Guo, Ting-Hao 'Kenneth' Huang. Are Shortest Rationales the Best Explanations for Human Understanding?. In the 60th Annual Meeting of the Association for Computational Linguistics.
ACL 2022
P.7
Jiao Sun, Tongshuang Wu, Yue Jiang, Ronil Awalegaonkar, Xi Victoria Lin, Diyi Yang. Pretty Princess vs. Successful Leader: Gender Roles in Greeting Card Messages. In the 2022 Conference on Human Factors in Computing Systems.
CHI 2022 Honorable Mention
P.8
Tongshuang Wu, Michael Terry, Carrie J. Cai. AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts. In the 2022 Conference on Human Factors in Computing Systems.
CHI 2022
P.9
Zheng Zhang, Ying Xu, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li. StoryBuddy: A Human-AI Collaborative Agent for Parent-Child Interactive Storytelling with Flexible Parent Involvement. In the 2022 Conference on Human Factors in Computing Systems.
CHI 2022
P.10
Yun Wang, Zhitao Hou, Leixian Shen, Tongshuang Wu, Jiaqi Wang, He Huang, Haidong Zhang, Dongmei Zhang. Towards Natural Language-Based Visualization Authoring. In IEEE Transactions on Visualization and Computer Graphics (Proc. InfoVis 2022).
TVCG 2022
2021
P.11
Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, Daniel S. Weld. Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models. In the 59th Annual Meeting of the Association for Computational Linguistics.
ACL 2021
P.12
Tongshuang Wu*, Gagan Bansal*, Joyce Zhou+, Raymond Fok+, Besmira Nushi, Ece Kamar, Marco Tulio Ribeiro, Daniel S. Weld. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. In the 2021 Conference on Human Factors in Computing Systems.
CHI 2021
P.13
Xingbo Wang, Yao Ming, Tongshuang Wu, Haipeng Zeng, Yong Wang, Huamin Qu. DeHumor: Visual Analytics forDecomposing Humor. In IEEE Transactions on Visualization and Computer Graphics.
TVCG 2021
2020
P.14
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, Sameer Singh. Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. In the 58th Annual Meeting of the Association for Computational Linguistics.
ACL 2020 Best Paper
P.15
Tongshuang Wu, Kanit (Ham) Wongsuphasawat, Donghao Ren, Kayur Patel, Chris DuBois. Tempura: Query Analysis with Structural Templates. In the 2020 Conference on Human Factors in Computing Systems.
CHI 2020
P.16
Alison Smith-Renner, Ron Fan, Melissa Birchfield, Tongshuang Wu, Jordan Boyd-Graber, Daniel S. Weld, Leah Findlater. No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML. In the 2020 Conference on Human Factors in Computing Systems.
CHI 2020
P.17
Tongshuang Wu*, Zhihang Dong*, Sicheng Song, Mingrui Zhang. Interactive Attention Model Explorer for Natural Language Processing Tasks with Unbalanced Data Sizes. In IEEE Pacific Visualization Symposium 2020.
PacificVis 2020
2019
P.18
Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, Daniel S. Weld. Errudite: Scalable, Reproducible, and Testable Error Analysis. In the 57th Annual Meeting of the Association for Computational Linguistics.
ACL 2019
P.19
Yang Shi, Maoran Xu, Rongwen Zhao, Hao Fu, Tongshuang Wu, Nan Cao. Interactive Context-Aware Anomaly Detection Guided by User Feedback. In IEEE Transactions on Human-Machine Systems.
THMS 2019
P.20
Tongshuang Wu, Daniel S. Weld, Jeffrey Heer. Local Decision Pitfalls in Interactive Machine Learning: An Investigation into Feature Selection in Sentiment Analysis. In ACM Transactions on Computer-Human Interaction 26.4.
TOCHI 2019
2016
P.21
Yun Wang, Tongshuang Wu, Zhutian Chen, Huamin Qu, Qiong Luo. STAC: Enhancing Stacked Graphs for Time Series Analysis. In IEEE Pacific Visualization Symposium 2016.
PacificVis 2016
P.22
Tongshuang Wu, Yuan Yao, Yuqing Duan, Xinzhi Fan, Huamin Qu. NetworkSeer: Visual Analysis for Social Network in MOOCs. In IEEE Pacific Visualization Symposium 2016.
PacificVis 2016 Best Paper
P.23
Tongshuang Wu, Yingcai Wu, Conglei Shi, Huamin Qu, Weiwei Cui. PieceStack: Toward Better Understanding of Stacked Graphs. In IEEE Transactions on Visualization and Computer Graphics (Proc. PacificVis 2016).
TVCG 2016 Honorable Mention
P.24
Qiaomu Shen, Tongshuang Wu, Haiyan Yang, Yanhong Wu, Huamin Qu, Weiwei Cui. NameClarifier: A Visual Analytics System for Author Name Disambiguation. In IEEE Transactions on Visualization and Computer Graphics (Proc. VAST 2016).
TVCG 2016

Posters, Extended Abstracts, Workshop Papers and Technical Reports

2022
W.1
Zheng Zheng, Ying Xu, Yanhao Wang, Tongshuang Wu, Bingsheng Yao, Daniel Ritchie, Mo Yu, Dakuo Wang, Toby Jia-Jun Li. Building a storytelling conversational agent through parent-AI collaboration. In AAAI Artificial Intelligence for Education Workshop.
AAAI 2022
W.2
Chenyang Yang, Rachel Brower-Sinning, Grace A. Lewis, Christian Kästner, Tongshuang Wu. Capabilities for Better ML Engineering. In The AAAI's Workshop on Artificial Intelligence Safety.
AAAI SafeAI 2023 2022
W.3
Tongshuang Wu*, Ellen Jiang*, Aaron Donsbach, Jeff Gray, Alejandra Molina, Michael Terry, Carrie J. Cai. PromptChainer: Chaining Large Language Model Promptsthrough Visual Programming. In the 2022 Conference on Human Factors in Computing Systems (Late Breaking Work).
CHI LBW 2022
2021
W.4
Tongshuang Wu. Principles and Interactive Tools for Evaluating and Improvingthe Behavior of Natural Language Processing models. In CHI 2022 Doctoral Consortium.
CHI DC 2021
2018
W.5
Halden Lin, Tongshuang Wu, Kanit (Ham) Wongsuphasawat, Yejin Choi, Jeffrey Heer. Visualizing Attention in Sequence-to-Sequence Summarization Models. In IEEE Conference on Visual Analytics Science and Technology.
VAST 2018

Patent

2022
PT.1
Ajit Narayanan, Subhashini Venugopalan, Tongshuang Wu, Shanqing Cai, Michael Terry, Meredith Morris, Carrie Cai. Providing Suggestions of Expanded Text from Abbreviated Text Input.
US Patent (Defensive Publication) 2022
PT.2
Carrie Cai, Tongshuang Wu, Michael Terry. Transparent and Controllable Human-AI Interaction via Chaining of Machine-Learned Language Models.
US Patent US63/251,264 (submitted), 2021 2022

SELECTED HONORS AND AWARDS

2022
CHI 2022 Honorable Mention Award
2020
Rising Stars in EECS Workshop (UC Berkeley)
A highly selective workshop based on academic excellence and commitment to advancing equity and inclusion.
2020
ACL 2020 Best Paper Award
2016–17
Faithful Steward Endowed Fellowship in Computer Science & Engineering
2012–16
Scholarship Scheme for Continuing Undergraduate Students
2016
IEEE PacificVis 2016 Honorable Mention Award
2016
IEEE PacificVis 2016 Best Notes Paper

Teaching Experience

Instructor

2023
05-499/899 Human-Centered NLP (CMU)
2023 Spring. Designed this special topic course on HCI+NLP research.

Conference Tutorial

2023
EMNLP 2023: Designing, Evaluating, and Learning from Humans Interacting with NLP Models
Key considerations and effective approaches for studying human-NLP model interactions

Guest Lecture

2022
Visualization and Machine Learning (Carnegie Mellon University)
In 05-898 Data Visualization
Interacting with Large Language Models (Carnegie Mellon University)
In 05-318/618 Human-AI Interaction
Designing Human-Centered, AI-Infused Software (Carnegie Mellon University)
In 05-391/891: Designing Human-Centered Software
Visualizing Text Summarization Models (Carnegie Mellon University)
In 05-120: Introduction to Human-Computer Interaction
2021
HCI+AI Interaction (University of Notre Dame)
In CSE 60427: Human-Centered Computing Research
2019
Model Interpretability (University of Washington)
In CSE 512: Data Visualization

Teaching Assistant

2019
CSE 512 Data Visualization (University of Washingon)
Graduate level course, 112 students (Instructor: Jeffrey Heer)
2018
CSE 442 Data Visualization (University of Washingon)
Undergraduate level course, 109 students (Instructor: Jeffrey Heer)

Mentoring Experience

Advisees

PhD
Christina Ma (CMU HCII, co-advisor: Ken Koedinger)
Human-AI Interaction for Education
Vijay Viswanathan (CMU LTI, co-advisor: Graham Neubig)
Human-in-the-loop NLP Model Fixing
Master
Yiyang (Diana) Wang (CMU HCII)
End-User Prompt Disambiguation
Yuanchen (Sophie) Bai (CMU Heinz)
NLP dataset characterization
Raoyi (Cathy) Huang (CMU Heinz)
NLP dataset characterization

Thesis Committee

PhD
Kundan Krishna (CMU)
Improving the reliability of summarization models
Hua Shen (Penn State)
Towards Useful AI Interpretability via Interactive AI Explanations
Master
Shreya Bali (CMU)
Tools to facilitate working on Machine Learning in the Industry

Prior to CMU

PhD
Yi Guo (Tongji University)
Co-supervised with Nan Cao. Natural-language-based visualization generation.
Sebastin Santy (UW)
The design and creation of an HCI+NLP research playbook.
Jiao Sun (USC)
Co-supervised with Diyi Yang. Gender bias in NLP datasets.
Master
Joyce Zhou (UW; Now at Cornell)
Co-supervised with Dan Weld & Gagan Bansal. Human-AI teaming.
Halden Lin (UW; Now at Apple Inc.)
Attention visualization for NLP models.
Akshat Shrivastava (UW; Now at Meta)
Active learning for sequence labeling.

Invited Talks

2022
Advanced NLP: Prompting
Peking University, Wangxuan Institute of Computer Technology (2022.3)
Model-in-the-loop Data Collection: What Roles does the Model Play?
DADC: Dynamic Adversarial Data Collection, NAACL 2022 (2022.7)
Interactive AI Model Debugging and Correction
Carnegie Mellon University, Ameet Group Meeting (2022.9)
Carnegie Mellon University, LTI Colloquium (2022.9)
University of Washington, DUB Seminar (2022.7)
University of Washington, Paul G. Allen School of CSE (2022.6)
MIT Computer Science & Artificial Intelligence Laboratory (2022.3)
Stanford University, Computer Science Department (2022.3)
Princeton University, Computer Science Department (2022.3)
Cornell University, Computer Science Department (2022.3)
Carnegie Mellon University, Human-Computer Interaction Institute (2022.3)
Peking University, Wangxuan Institute of Computer Technology (2022.3)
UT Austin, Computer Science Department (2022.2)
University of Chicago, Data Science Institute (2022.2)
Hong kong University of Science and Technology, Computer Science Department (2022.2)
PennState, Young Achievers Symposium (2022.1)
2021
Principles and Tools for Evaluating and Improving NLP Models
Google Research (2021.7)
ACM CHI Doctoral Consortium (2021.5)
NLP with Friends (2021.4)
Interactive Data Exploration System (IDEAS) lab, Shandong University (2021.4)
Transparent and Controllable Collaboration with Large Language Models
Google Film Sprint: Fluid Language Integrating Muse (2021.1)
Google PAIR: People+AI Research Initiative (2021.7)
Human+AI: the Relationships, the Goals, the Challenges
University of Notre Dame, Human-Centered Computing Research (2021.1)
Hong Kong University of Science and Technology, VisLab (2021.1)
Machines in the Loop: Explainability, Transparency, and Rich Interaction
ACL InterNLP 2021, invited panelist (2021.8)
Generating and Perturbing Text with Semantic Controls
Allen Institute for Artificial Intelligence, All-AI2 Meeting (2021.8)
2020
Behavioral Testing of NLP Models
AI Technology Review (2020.8)
AI Time PhD (2020.7)
UCLA, Center for Vision, Cognition, Learning and Autonomy (VCLA) (2020.7)
2019
Scalable, Reproducible, and Testable Error Analysis
UW CSE 512, as guest lecturer (2019.5)
Allen Institute for Artificial Intelligence, All-AI2 Meeting (2019.5)
Apple Inc., Knowledge Graph Team Seminar (2019.3)
Robust AI Event: Research & Reality (2019.5)

Professional Service

Organizing Committees

2023
Tutorial: Designing, Evaluating, and Learning from Humans Interacting with NLP Models (EMNLP 2023)
2022
SSLL: Sharing Stories and Lessons Learned Workshop (EMNLP 2022)
2022
TRAIT: Workshop on Trust and Reliance in AI-Human Teams (CHI 2022-23)
2022
NL-Augmenter (part of GEM: Workshop for Generation, Evaluation, Metrics, ACL 2021)

Program Committees

AI
AAAI 2022, AAAI HCOMP 2022, ACM FAccT 2022, NeurIPS XAI 2021
NLP
ACL 2023
HCI
CHI 2023, ACM IUI 2022-23, IUI TExSS 2022, CHI HCXAI 2021

Paper Reviewing

HCI
ACM CHI 2019-22, TOCHI 2021, UIST 2018/20/22, IUI 2020, CSCW 2020, TiiS 2022
Special recognition for outstanding reviews ACM CHI, IUI
NLP
ACL 2020, EACL 2021, NAACL 2021
AI
NeurIPS 2022, AAAI 2022, AKBC 2021, ACM Computing Surveys 2021
Viz.
IEEE VIS 2017-21, TVCG 2021, EuroVis 2021, PacificVis 2018/20, ChinaVis 2017-19

Community Service

2023
Committee member, ACM/SCS Thesis Nomination & Award Committee
Read various candidate PhD dissertations and selected awardees for both CMU and ACM level thesis award.
Leader, Postdoc Mentoring Group
Led a bi-weekly mentorship group for Postdocs within PhD HCII.
Committee member, CMU HCII PhD Admission Committee
2021
Co-organizer, UW Allen School Pre-Application Mentoring Service (PAMS)
A program supporting 107 potential CS PhD applicants, with 80% from underrepresented communities.
Coordinator, UW Allen School Diverse Genders in Research Events
Course design mentor, UW AVELA (A Vision for Electronic Literacy & Access)
Mentored undergraduate students to develop curriculum for high-school web development courses.
Co-organizer, UW Allen School Women's Research Day
An outreach event to women and nonbinary people in research.
2020
Student contributor, UW Allen School Strategic Plan for Diversity, Equity & Inclusion
Student volunteer, IEEE VIS 2020
Subcomittee Student Assistant, ACM SIGCHI 2021
2019
Reviewer, UW Allen School Graduate Admission Committee
2018
Co-leader, UW Interactive Systems Seminar
2013
Community tutor, HKUST Connect

Media Coverage

2023
Debugging Imperfect AI
CMU User Experience Association (UXA) Newsletter, 2023.2
2020
AI researchers create testing tool to find bugs in NLP from Amazon, Google, and Microsoft
VentureBeat, 2020.7
Allen School researchers earn Best Paper Award at ACL 2020
Allen School News, 2020.8
How Should We Do Error Analysis? A Lesson for NLP developers [Chinese]
AI Technology Review, 2020.8
2019
Experimental results and error reporting, Ethics and NLP, Distillation
Distillation vol. 2,, SemEval 2020