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Draft:Irwin King

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Irwin King
Irwin King
Born1961
Taipei, Taiwan
NationalityAmerican
Alma materB.S., California Institute of Technology (Caltech), MSc and PhD, University of Southern California (USC)
AwardsINNS, APNNS
Scientific career
FieldsComputer science
InstitutionsThe Chinese University of Hong Kong
Websitehttps://www.cse.cuhk.edu.hk/people/faculty/irwin-king/

Irwin King (金國慶) is an American computer scientist and educator known for his contributions to machine learning, artificial intelligence (AI), and data science, making substantial contributions to both theoretical frameworks and practical applications. A professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK), he has held leadership roles such as department chair (2000–2023) and Associate Dean of Engineering (2013–2019)[1]. His work has earned fellowships from the ACM, IEEE, and the International Neural Network Society[2][3][4].

Education

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King completed a Bachelor of Science in Engineering and Applied Science at the California Institute of Technology (Caltech) in 1984. He pursued graduate studies at the University of Southern California (USC), earning a Master of Science (1987) and a Doctor of Philosophy (1993) in computer science. His doctoral research focused on simulating biological neural networks for motion detection, working with Michael A. Arbib, Christoph von der Malsburg, and Irving Biederman, at the University of Southern California (USC).

Career

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King joined CUHK in 1993, rising from assistant professor to chair of the Department of Computer Science and Engineering. From 2010 to 2012, he worked at AT&T Labs Research on big data applications and later taught at the University of California, Berkeley as a visiting professor. He was also a Member of the Technical Staff at the AT&T Labs Research from 2010 to 2012 working on Big Data and data science-related projects[5].

He served as the Associate Dean (Education) of the Engineering Faculty at CUHK from August 2013 to July 2019. He also served as the Chair of the Department of Computer Science from August 2000 to July 2023. He founded CUHK’s Machine Intelligence and Social Computing Lab in 2006 and became the inaugural director of the ELearning Innovation and Technology (ELITE) Centre in 2017, promoting digital education tools.

Notable projects under his leadership include:

  • VeriGuide (2005–present): A plagiarism-detection system to uphold academic integrity.
  • KEEP (2014–present): A platform supporting MOOCs across Greater China.

Awards and Honors

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  1. ACM Fellow (2024)[6]
  2. IEEE Fellow (2019)[7]
  3. INNS Fellow (2021)[8]
  4. AAIA Fellow (2022)[9]
  5. HKIE Fellow[10]
  6. Lee Woo Sing College Fellow
  7. Apple Distinguished Educator
  8. World’s Top 2% Scientists by Stanford University (September 2022)[11]
  9. ACM WSDM Test of Time Award (2022)[12]
  10. ACM SIGIR Test of Time Award (2020)[13]
  11. ACM CIKM Test of Time Award (2019)[14]
  12. 2021 INNS Dennis Gabor Award for work in Neural Engineering for Social Computing[15]
  13. 2020 APNNS Outstanding Achievement Award [16]

Leadership

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  1. Vice-President, ACM SIGWEB (2023–present)[17]
  2. Vice-President of Conference, WebConf Steering Committee (2022–present)
  3. Former President of INNS (2019–2020)
  4. Executive Committee member, Hong Kong High Performance Computing Association (HKHPC) (2024–present)[18]
  5. General Co-Chair, WWW2020[19]
  6. General Co-Chair, RecSys 2013[20]
  7. General Co-Chair, ASONAM 2012[21]

Recent Publications

[edit]
  1. Yifei Zhang, Hao Zhu, Menglin Yang, Jiahong Liu, Rex Ying, Irwin King, Piotr Koniusz: Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning. KDD (1) 2025: 1984-1995[22]
  2. Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip S. Yu: An Unforgeable Publicly Verifiable Watermark for Large Language Models. ICLR 2024[23]
  3. Conghao Xiong, Hao Chen, Hao Zheng, Dong Wei, Yefeng Zheng, Joseph J. Y. Sung, Irwin King: MoME: Mixture of Multimodal Experts for Cancer Survival Prediction. MICCAI (4) 2024: 318-328[24]
  4. Yueen Ma, Dafeng Chi, Jingjing Li, Kai Song, Yuzheng Zhuang, Irwin King: VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder. NAACL-HLT (Findings) 2024: 364-378[25]
  5. Zixing Song, Yifei Zhang, Irwin King: No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning. NeurIPS 2023[26]
  6. Yifei Zhang, Dun Zeng, Jinglong Luo, Zenglin Xu, Irwin King: A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy. WWW (Companion Volume) 2023: 1167-1176[27]
  7. Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King: WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering. SIGIR 2023: 2521-2525[28]
  8. Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu: Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5026-5041 (2022)[29]

Selected Award-Winning Publications

[edit]
  1. [ICONIP2023 Best Student Paper Award Finalist] Xiangli Yang, Xinglin Pan, Irwin King, Zenglin Xu: Generalized Category Discovery with Clustering Assignment Consistency. ICONIP (5) 2023: 535-547[30]
  2. [ICONIP2020 Best Student Paper Award] Yaoman Li, Irwin King: AutoGraph: Automated Graph Neural Network. ICONIP (2) 2020: 189-201[31]
  3. [CVPR2019 Best Paper Award Finalist] Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu: SelFlow: Self-Supervised Learning of Optical Flow. CVPR 2019: 4571-4580[32]
  4. [ICONIP2017, Best Student Paper Award Runner-up] Shenglin Zhao, Irwin King, Michael R. Lyu: Geo-Pairwise Ranking Matrix Factorization Model for Point-of-Interest Recommendation. ICONIP (5) 2017: 368-377[33]
  5. [CIKM2016 Best Paper Award Runner-up] Tong Zhao, Irwin King: Constructing Reliable Gradient Exploration for Online Learning to Rank. CIKM 2016: 1643-1652[34]
  6. [WSDM 2022 Test of Time Award] Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, Irwin King: Recommender systems with social regularization. WSDM 2011: 287-296[35]
  7. [SIGIR 2020 Test of Time Award] Hao Ma, Irwin King, Michael R. Lyu: Learning to recommend with social trust ensemble. SIGIR 2009: 203-210[36]
  8. [CIKM 2019 Test of Time Award] Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King: SoRec: social recommendation using probabilistic matrix factorization. CIKM 2008: 931-940[37]

References

[edit]
  1. ^ "Irwin King – CUHK CSE". Retrieved April 15, 2025.
  2. ^ "Irwin King". awards.acm.org. Retrieved 2025-04-15.
  3. ^ "IEEE Fellows Directory - Member Profile". services27.ieee.org. Retrieved 2025-04-15.
  4. ^ "Fellows and Senior Members". www.inns.org. Retrieved 2025-04-15.
  5. ^ "Irwin King Inventions, Patents and Patent Applications - Justia Patents Search". patents.justia.com. Retrieved 2025-04-16.
  6. ^ "2024 ACM Fellows Celebrated for transformative contributions to computing science and technology". www.acm.org. Retrieved 2025-04-15.
  7. ^ "IEEE Fellows Directory - Member Profile". services27.ieee.org. Retrieved 2025-04-15.
  8. ^ "Fellows and Senior Members". www.inns.org. Retrieved 2025-04-15.
  9. ^ "Asia-Pacific Artificial Intelligence Association". www.aaia-ai.org. Retrieved 2025-04-15.
  10. ^ "Standing Committees | HKIE". www.hkie.org.hk. Retrieved 2025-04-15.
  11. ^ Kumar, Rajendra (2022). "World's top 2% Scientist 2022". doi:10.13140/RG.2.2.30055.11687. {{cite journal}}: Cite journal requires |journal= (help)
  12. ^ "WSDM Test of Time Award". WSDM'22. 2022-01-27. Retrieved 2025-04-15.
  13. ^ "SIGIR 2020". sigir.org. Retrieved 2025-04-15.
  14. ^ "CIKM Test of Time Award". www.cikmconference.org. Retrieved 2025-04-15.
  15. ^ "Prof. Irwin King Awarded the 2021 INNS Dennis Gabor Award – CUHK CSE". www.cse.cuhk.edu.hk. Archived from the original on 2024-06-17. Retrieved 2025-04-15.
  16. ^ "Awards". APNNS. Retrieved 2025-04-15.
  17. ^ "SIGWEB - Executive Committee". www.sigweb.org. Retrieved 2025-04-15.
  18. ^ "Executive Committee – hkhpc.org". Retrieved 2025-04-15.
  19. ^ "The Web Conference 2020". The Web Conference. Retrieved 2025-04-15.
  20. ^ "RecSys – ACM Recommender Systems". RecSys. Retrieved 2025-04-15.
  21. ^ "ASONAM 2012 Home page". asonam.cpsc.ucalgary.ca. Retrieved 2025-04-15.
  22. ^ Zhang, Yifei; Zhu, Hao; Yang, Menglin; Liu, Jiahong; Ying, Rex; King, Irwin; Koniusz, Piotr (2025-07-20). "Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning". Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1. KDD '25. New York, NY, USA: Association for Computing Machinery. pp. 1984–1995. arXiv:2310.18209. doi:10.1145/3690624.3709249. ISBN 979-8-4007-1245-6.
  23. ^ Liu, Aiwei; Pan, Leyi; Hu, Xuming; Li, Shuang; Wen, Lijie; King, Irwin; Yu, Philip S. (2023-10-13). "An Unforgeable Publicly Verifiable Watermark for Large Language Models". arXiv:2307.16230. {{cite journal}}: Cite journal requires |journal= (help)
  24. ^ Xiong, Conghao; Chen, Hao; Zheng, Hao; Wei, Dong; Zheng, Yefeng; Sung, Joseph J. Y.; King, Irwin (2024). "MoME: Mixture of Multimodal Experts for Cancer Survival Prediction". In Linguraru, Marius George; Dou, Qi; Feragen, Aasa; Giannarou, Stamatia; Glocker, Ben; Lekadir, Karim; Schnabel, Julia A. (eds.). Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. Lecture Notes in Computer Science. Vol. 15004. Cham: Springer Nature Switzerland. pp. 318–328. doi:10.1007/978-3-031-72083-3_30. ISBN 978-3-031-72083-3.
  25. ^ Ma, Yueen; Chi, DaFeng; Li, Jingjing; Song, Kai; Zhuang, Yuzheng; King, Irwin (June 2024). Duh, Kevin; Gomez, Helena; Bethard, Steven (eds.). "VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder". Findings of the Association for Computational Linguistics: NAACL 2024. Mexico City, Mexico: Association for Computational Linguistics: 364–378. arXiv:2307.00852. doi:10.18653/v1/2024.findings-naacl.26.
  26. ^ Song, Zixing; Zhang, Yifei; King, Irwin (2023-12-15). "No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning". Advances in Neural Information Processing Systems. 36: 47511–47526.
  27. ^ Zhang, Yifei; Zeng, Dun; Luo, Jinglong; Xu, Zenglin; King, Irwin (2023-04-30). "A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy". Companion Proceedings of the ACM Web Conference 2023. WWW '23 Companion. New York, NY, USA: Association for Computing Machinery. pp. 1167–1176. arXiv:2302.10637. doi:10.1145/3543873.3587681. ISBN 978-1-4503-9419-2.
  28. ^ Chen, Yankai; Zhang, Yifei; Yang, Menglin; Song, Zixing; Ma, Chen; King, Irwin (2023-07-18). "WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering". Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. SIGIR '23. New York, NY, USA: Association for Computing Machinery. pp. 2521–2525. arXiv:2305.04410. doi:10.1145/3539618.3592089. ISBN 978-1-4503-9408-6.
  29. ^ Liu, Pengpeng; Lyu, Michael R.; King, Irwin; Xu, Jia (September 2022). "Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation". IEEE Transactions on Pattern Analysis and Machine Intelligence. 44 (9): 5026–5041. arXiv:2106.04195. doi:10.1109/TPAMI.2021.3085525. ISSN 1939-3539. PMID 34061735.
  30. ^ Yang, Xiangli; Pan, Xinglin; King, Irwin; Xu, Zenglin (2024). "Generalized Category Discovery with Clustering Assignment Consistency". In Luo, Biao; Cheng, Long; Wu, Zheng-Guang; Li, Hongyi; Li, Chaojie (eds.). Neural Information Processing. Lecture Notes in Computer Science. Vol. 14451. Singapore: Springer Nature. pp. 535–547. doi:10.1007/978-981-99-8073-4_41. ISBN 978-981-99-8073-4.
  31. ^ Li, Yaoman; King, Irwin (2020). "AutoGraph: Automated Graph Neural Network". In Yang, Haiqin; Pasupa, Kitsuchart; Leung, Andrew Chi-Sing; Kwok, James T.; Chan, Jonathan H.; King, Irwin (eds.). Neural Information Processing. Lecture Notes in Computer Science. Vol. 12533. Cham: Springer International Publishing. pp. 189–201. doi:10.1007/978-3-030-63833-7_16. ISBN 978-3-030-63833-7.
  32. ^ Liu, Pengpeng; Lyu, Michael R.; King, Irwin; Xu, Jia (2021-06-08), Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation, arXiv:2106.04195, retrieved 2025-04-15
  33. ^ Zhao, Shenglin; King, Irwin; Lyu, Michael R. (2017). "Geo-Pairwise Ranking Matrix Factorization Model for Point-of-Interest Recommendation". In Liu, Derong; Xie, Shengli; Li, Yuanqing; Zhao, Dongbin; El-Alfy, El-Sayed M. (eds.). Neural Information Processing. Lecture Notes in Computer Science. Vol. 10638. Cham: Springer International Publishing. pp. 368–377. doi:10.1007/978-3-319-70139-4_37. ISBN 978-3-319-70139-4.
  34. ^ Zhao, Tong; King, Irwin (2016-10-24). "Constructing Reliable Gradient Exploration for Online Learning to Rank". Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. CIKM '16. New York, NY, USA: Association for Computing Machinery. pp. 1643–1652. doi:10.1145/2983323.2983774. ISBN 978-1-4503-4073-1.
  35. ^ Ma, Hao; Zhou, Dengyong; Liu, Chao; Lyu, Michael R.; King, Irwin (2011-02-09). "Recommender systems with social regularization". Proceedings of the fourth ACM international conference on Web search and data mining. WSDM '11. New York, NY, USA: Association for Computing Machinery. pp. 287–296. doi:10.1145/1935826.1935877. ISBN 978-1-4503-0493-1.
  36. ^ Ma, Hao; Lyu, Michael R.; King, Irwin (2009-10-23). "Learning to recommend with trust and distrust relationships". Proceedings of the third ACM conference on Recommender systems. RecSys '09. New York, NY, USA: Association for Computing Machinery. pp. 189–196. doi:10.1145/1639714.1639746. ISBN 978-1-60558-435-5.
  37. ^ Ma, Hao; Yang, Haixuan; Lyu, Michael R.; King, Irwin (2008-10-26). "SoRec: Social recommendation using probabilistic matrix factorization". Proceedings of the 17th ACM conference on Information and knowledge management. CIKM '08. New York, NY, USA: Association for Computing Machinery. pp. 931–940. doi:10.1145/1458082.1458205. ISBN 978-1-59593-991-3.

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