Welcome to Kun's Personal Website
I'm Kun Qian (钱坤), a Senior Machine Learning Manager and Researcher at Adobe, with a passion for both scientific research and real-world impact. My work has evolved from theoretical data integration research during my PhD at UC Santa Cruz to applied machine learning and AI.
I earned my PhD under the guidance of Balder ten Cate, Phokion Kolaitis, and Wang-Chiew Tan. My primary focus was on approximation algorithms for data integration problems. Afterward, I joined IBM Research, where I developed machine learning systems for low-resource settings, combining deep learning, human-in-the-loop approaches, and weak supervision. My work at IBM resulted in over 20 publications at top AI and CS conferences. I later worked at Amazon's Search Science and AI group, improving search experiences for millions of customers, and at Apple, where I led the creation of a knowledge graph for Apple's user queries. Now, I’m at Adobe, building an intelligent AI Assistant for marketers.
Outside of work, I enjoy reading, movies, traveling, and cooking Szechuan cuisine, which I believe rivals many west coast restaurants. Originally from Chongqing, China, I now live with my wife and son in the Seattle area after spending 9 years in the Bay Area.
Research & Publications
Research Interests: information extraction, large language models, human-in-the-loop machine learning, active learning, weak supervision, deep learning, explainable AI, data integration and data exchange, multilingual search.
I have broad research interests ranging from theoretical problems in data exchange to, more recently, machine learning with small data. Explainable AI (XAI) Research is another area that I am recently interested in (please check out our project website).
My work has been published in various notable AI/NLP/DB/HCI conferences and journals including: AAAI, ACL, EMNLP, COLING, VLDB, PODS, ICDE, TODS, CIKM, IUI, ACM DIS, ISWC, etc. with a best demo award at ISWC 2020, and a DSRI AI Incidents and Best Practices Paper Award at IAAI 2025. I also actively review papers for research conferences and journals to serve our research community. My publications (since 2015) are listed below:
(New) EVOSCHEMA: Toward Text-to-SQL Robustness Against Schema Evolution (full)
Tianshu Zhang, Kun Qian, Siddhartha Sahai, Yuan Tian, Shaddy Garg, Huan Sun, Yunyao Li
(New) Adobe Summit Concierge Evaluation with human in the loop (full)
Yiru Chen, Sally Fang, Sai Sree Harsha, Dan Luo, Vaishnavi Muppala, Fei Wu, Shun Jiang, Kun Qian, Yunyao Li
Evaluation and Incident Prevention in an Enterprise AI Assistant (full)
Akash V Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup Rao, Austin Zane, Avi Feller, Kun Qian, Yunyao Li
DaSH - Data Science with Human-in-the-loop (workshop co-chair) (workshop)
Eduard Dragut, Lucian Popa, Yunyao Li, Kun Qian, Sherry Wu
FISQL: Enhancing Text-to-SQL Systems with Rich Interactive Feedback (full)
Rakesh Menon, Kun Qian, Liqun Chen, Ishika Joshi, Daniel Pandyan, Shashank Srivastava, Yunyao Li
Time Sensitive Knowledge Editing through Efficient Finetuning (short)
Xiou Ge, Ali Mousavi, Edouard Grave, Armand Joulin, Kun Qian, Ben Han, Mostafa Arefiyan, Yunyao Li
Evaluation and Continual Improvement for an Enterprise AI Assistant (short)
Akash V. Maharaj, Kun Qian, Uttaran Bhattacharya, Sally Fang, Horia Galatanu, Manas Garg, Rachel Hanessian, Nishant Kapoor, Ken Russell, Shivakumar Vaithyanathan, Yunyao Li
APE: Active Learning-based Tooling for Finding Informative Few-shot Examples for LLM-based Entity Matching (short)
Kun Qian, Yisi Sang, Farima Bayat, Anton Belyy, Xianqi Chu, Yash Govind, Samira Khorshidi, Rahul Khot, Katherine Luna, Azadeh Nikfarjam, Xiaoguang Qi, Fei Wu, Xianhan Zhang, Yunyao Li
FLEEK: Factual Error Detection and Correction with Evidence Retrieved from External Knowledge (demo)
Farima Fatahi Bayat, Kun Qian, Ben Han, Yisi Sang, Anton Belyi, Samira Khorhshidi, Fei Wu, Ihab Ilyas, Yunyao Li
(Intern project that I mentored)
Improving Human Annotation Effectiveness for Fact Collection by Identifying the Most Relevant Answers. (regular)
Pranav Kamath, Yiwen Sun, Thomas Semere, Adam Green, Scott Manle, Xiaoguang Qi, Kun Qian, Yunyao Li
Explainability for Natural Language Processing. (tutorial)
Shipi Dhanorkar, Marina Danilevsky, Yunyao Li, Lucian Popa, Kun Qian, Anbang Xu
Who needs to know what, when?: Broadening the Explainable AI (XAI) Design Space by Looking at Explanations Across the AI Lifecycle (regular)
Shipi Dhanorkar, Christine T Wolf, Kun Qian, Anbang Xu, Lucian Popa, Yunyao Li
(DIS 2021)
Work done at IBM Research
(Intern project that I mentored)
XNLP: A Living Survey for XAI Research in Natural Language Processing (demo)
Kun Qian, Marina Danilevsky, Yannis Katsis, Ban Kawas, Erick Oduor, Lucian Popa, Yunyao Li
Learning Structured Representations of Entity Names using Active Learning and Weak Supervision (short)
Kun Qian, Poornima Chozhiyath Raman, Lucian Popa, Yunyao Li
(Acceptance rate: 16.7% - short paper)
A Survey of the State of Explainable AI for Natural Language Processing (regular)
Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katasis, Ban Kawas, Prithviraj Sen
Ontology Mediated Information Extraction with MASTRO SYSTEM-T (demo)
Domenico Lembo, Yunyao Li, Lucian Popa, Kun Qian, Federico Scafoglieri
(Intern project that I mentored)
Explainability for Natural Language Processing. (tutorial)
Shipi Dhanorkar, Yunyao Li, Lucian Popa, Kun Qian, Christine T Wolf, Anbang Xu
An Intuitive User Interface for Human-in-the-loop Entity Name Parsing and Entity Variant Generation. (regular)
Kun Qian, Lucian Popa, Yunyao Li
Answering Complex Questions by Combining Information from Curatedand Extracted Knowledge Bases. (regular)
Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H.V. Jagadish
XAIT: An Interactive Website for Explainable AI for Text. (demo)
Eno Oduor, Kun Qian, Yunyao Li, Lucian Popa
PARTNER: Human-in-the-loop Entity Understanding with Deep Learning. (demo)
Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa
Learning-based Human-in-the-loop Methods for Entity Resolution. (tutorial)
Sairam Gurajada, Lucian Popa, Kun Qian, Prithviraj Sen
Learning Explainable Entity Resolution Algorithms for Small Business Data using SystemER. (workshop)
Kun Qian, Douglas R Burdick, Sairam Gurajada, Lucian Popa
Low-resource Deep Entity Resolution with Transfer and Active Learning. (regular)
Jungo Kasai, Kun Qian, Sairam Gurajada, Yunyao Li, Lucian Popa
(Intern project that I mentored)
SystemER: A Human-in-the-loop System for Explainable Entity Resolution. (demo)
Kun Qian, Lucian Popa, Prithviraj Sen
Knowledge Refinement via Rule Selection. (regular)
Phokion G. Kolaitis, Lucian Popa, Kun Qian
(Acceptance rate: 16.2%)
Exploiting Structure in Representation of Named Entities using Active Learning (regular)
Nikita Bhutani, Kun Qian, Yunyao Li, H.V. Jagadish, Mauricio A. Hernandez., Mitesh Vasa
(Intern project that I mentored)
LUSTRE: An Interactive System for Entity Structured Representation and Variant Generation. (demo)
Kun Qian, Nikita Bhutani, Yunyao Li, H.V. Jagadish, Mauricio A. Hernandez.
(Intern project that I mentored)
Active Learning of GAV Schema Mappings. (regular)
Balder ten Cate, Phokion G. Kolaitis, Kun Qian, Wang-Chiew Tan
Active Learning for Large-Scale Entity Resolution. (regular)
Kun Qian, Lucian Popa, Prithviraj Sen
Approximation Algorithms for Schema-Mapping Discovery from Data Examples. (regular)
Balder ten Cate, Phokion G. Kolaitis, Kun Qian, Wang-Chiew Tan
Approximation Algorithms for Schema-Mapping Discovery from Data Examples. (regular)
Balder ten Cate, Phokion G. Kolaitis, Kun Qian, Wang-Chiew Tan
(To appear) EVOSCHEMA: Toward Text-to-SQL Robustness Against Schema Evolution
Tianshu Zhang, Kun Qian, Siddhartha Sahai, Yuan Tian, Shaddy Garg, Huan Sun, Yunyao Li
(To appear) Adobe Summit Concierge Evaluation with human in the loop
Yiru Chen, Sally Fang, Sai Sree Harsha, Dan Luo, Vaishnavi Muppala, Fei Wu, Shun Jiang, Kun Qian, Yunyao Li
Evaluation and Incident Prevention in an Enterprise AI Assistant
Akash V Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup Rao, Austin Zane, Avi Feller, Kun Qian, Yunyao Li
DaSH - Data Science with Human-in-the-loop (workshop co-chair)
Eduard Dragut, Lucian Popa, Yunyao Li, Kun Qian, Sherry Wu
FISQL: Enhancing Text-to-SQL Systems with Rich Interactive Feedback
Rakesh Menon, Kun Qian, Liqun Chen, Ishika Joshi, Daniel Pandyan, Shashank Srivastava, Yunyao Li
Time Sensitive Knowledge Editing through Efficient Finetuning
Xiou Ge, Ali Mousavi, Edouard Grave, Armand Joulin, Kun Qian, Ben Han, Mostafa Arefiyan, Yunyao Li
Evaluation and Continual Improvement for an Enterprise AI Assistant
Akash V. Maharaj, Kun Qian, Uttaran Bhattacharya, Sally Fang, Horia Galatanu, Manas Garg, Rachel Hanessian, Nishant Kapoor, Ken Russell, Shivakumar Vaithyanathan, Yunyao Li
APE: Active Learning-based Tooling for Finding Informative Few-shot Examples for LLM-based Entity Matching
Kun Qian, Yisi Sang, Farima Bayat, Anton Belyy, Xianqi Chu, Yash Govind, Samira Khorshidi, Rahul Khot, Katherine Luna, Azadeh Nikfarjam, Xiaoguang Qi, Fei Wu, Xianhan Zhang, Yunyao Li
Improving Human Annotation Effectiveness for Fact Collection by Identifying the Most Relevant Answers.
Pranav Kamath, Yiwen Sun, Thomas Semere, Adam Green, Scott Manle, Xiaoguang Qi, Kun Qian, Yunyao Li
Who needs to know what, when?: Broadening the Explainable AI (XAI) Design Space by Looking at Explanations Across the AI Lifecycle
Shipi Dhanorkar, Christine T Wolf, Kun Qian, Anbang Xu, Lucian Popa, Yunyao Li
Learning Structured Representations of Entity Names using Active Learning and Weak Supervision
Kun Qian, Poornima Chozhiyath Raman, Lucian Popa, Yunyao Li
A Survey of the State of Explainable AI for Natural Language Processing
Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katasis, Ban Kawas, Prithviraj Sen
An Intuitive User Interface for Human-in-the-loop Entity Name Parsing and Entity Variant Generation.
Kun Qian, Lucian Popa, Yunyao Li
Answering Complex Questions by Combining Information from Curatedand Extracted Knowledge Bases.
Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H.V. Jagadish
Learning Explainable Entity Resolution Algorithms for Small Business Data using SystemER.
Kun Qian, Douglas R Burdick, Sairam Gurajada, Lucian Popa
Low-resource Deep Entity Resolution with Transfer and Active Learning.
Jungo Kasai, Kun Qian, Sairam Gurajada, Yunyao Li, Lucian Popa
Knowledge Refinement via Rule Selection.
Phokion G. Kolaitis, Lucian Popa, Kun Qian
Exploiting Structure in Representation of Named Entities using Active Learning
Nikita Bhutani, Kun Qian, Yunyao Li, H.V. Jagadish, Mauricio A. Hernandez., Mitesh Vasa
Active Learning of GAV Schema Mappings.
Balder ten Cate, Phokion G. Kolaitis, Kun Qian, Wang-Chiew Tan
Active Learning for Large-Scale Entity Resolution.
Kun Qian, Lucian Popa, Prithviraj Sen
Approximation Algorithms for Schema-Mapping Discovery from Data Examples.
Balder ten Cate, Phokion G. Kolaitis, Kun Qian, Wang-Chiew Tan
FLEEK: Factual Error Detection and Correction with Evidence Retrieved from External Knowledge
Farima Fatahi Bayat, Kun Qian, Ben Han, Yisi Sang, Anton Belyi, Samira Khorhshidi, Fei Wu, Ihab Ilyas, Yunyao Li
XNLP: A Living Survey for XAI Research in Natural Language Processing
Kun Qian, Marina Danilevsky, Yannis Katsis, Ban Kawas, Erick Oduor, Lucian Popa, Yunyao Li
Ontology Mediated Information Extraction with MASTRO SYSTEM-T
Domenico Lembo, Yunyao Li, Lucian Popa, Kun Qian, Federico Scafoglieri
XAIT: An Interactive Website for Explainable AI for Text.
Eno Oduor, Kun Qian, Yunyao Li, Lucian Popa
PARTNER: Human-in-the-loop Entity Understanding with Deep Learning.
Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa
SystemER: A Human-in-the-loop System for Explainable Entity Resolution.
Kun Qian, Lucian Popa, Prithviraj Sen
Explainability for Natural Language Processing.
Shipi Dhanorkar, Marina Danilevsky, Yunyao Li, Lucian Popa, Kun Qian, Anbang Xu
(SIGKDD 2021)
Explainability for Natural Language Processing.
Shipi Dhanorkar, Yunyao Li, Lucian Popa, Kun Qian, Christine T Wolf, Anbang Xu
Learning-based Human-in-the-loop Methods for Entity Resolution.
Sairam Gurajada, Lucian Popa, Kun Qian, Prithviraj Sen
Award(s)
| Best Post/Demo Award @ The 19th International Semantic Web Conference (ISWC 2020) |
Experience
| 2024.02 - Now | Sr. Machine Learning Manager (since 2024.09) | Adobe | |
| Sr. Machine Learning Engineer | |||
| 2022.03 - 2024.01 | Senior Machine Learning Researcher and Engineer | Apple | |
| 2021.03 - 2022.06 | Applied Scientst | Amazon | |
| 2017.02 - 2021.03 | Research Scientist | IBM Research | |
| 2010.10 - 2011.08 | Project Officer | Nanyang Technological University |
Education
| Ph.D. | - | University of California, Santa Cruz |
| M.S. | - | Beihang University |
| B.S. | - | Chongqing University |
Professional Services
| Conference PC: | PVLDB (2022, 2023, 2024), EMNLP (2022, 2021), DaSH@KDD 2021, DaSH@NAACL 2021, IUI 2021 (demo), NAACL 2021 | |
| ACL 2020, ACL 2025 (Area Chair), IJCAI 2020, AAAI (2021, 2020), ICDE 2020 (industry track) | ||
| IEEE BigData 2019, WebDB@SIGMOD 2018 | ||
| Journal referee: | ACM TODS (2018, 2019), IEEE TKDE (2019) |
Skills
| Programming: | Python, Java | |
| Deep Learning | Pytorch, Pytorch-transformer | |
| Web Development | Angular, Angular Material, Django, Javascript, Typescript, HTML, W3.CSS | |
| Distributed Computing & Cloud Computing | Spark (PySpark), AWS | |
| Others | LaTeX |
Visitors since May 2019
