World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
15023
World Ranking
6037
National Ranking
2719

Overview

Lichan Hong is affiliated with Google in the United States and works primarily in the field of Computer Science. Their research encompasses key areas including Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research, and General Health Professions. The predominant focus lies on Artificial Intelligence and Information Systems, constituting a significant portion of their scholarly output.

Their work addresses topics such as Recommender Systems and Techniques, Topic Modeling, Advanced Bandit Algorithms Research, Advanced Graph Neural Networks, Domain Adaptation and Few-Shot Learning, Multimodal Machine Learning Applications, and Data Stream Mining Techniques.

They have published extensively in venues that include:

  • arXiv (Cornell University)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Companion Proceedings of the Web Conference 2020
  • Proceedings of the ACM Web Conference 2022

Recent notable papers include:

  • "Language Matters In Twitter: A Large Scale Study" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "Is Twitter a Good Place for Asking Questions? A Characterization Study" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations" (2020), published in Companion Proceedings of the Web Conference 2020
  • "Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems" (2020), published in Companion Proceedings of the Web Conference 2020
  • "Distributionally-robust Recommendations for Improving Worst-case User Experience" (2022), published in Proceedings of the ACM Web Conference 2022

Frequent collaborators include:

  • Ed H.
  • Xinyang Yi
  • Derek Zhiyuan Cheng
  • Maheswaran Sathiamoorthy
  • Wang-Cheng Kang

Best Publications

  • Wide & Deep Learning for Recommender Systems

    Heng-Tze Cheng;Levent Koc;Jeremiah Harmsen;Tal Shaked

  • Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network

    Bongwon Suh;Lichan Hong;Peter Pirolli;Ed H. Chi

  • Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts

    Jiaqi Ma;Zhe Zhao;Xinyang Yi;Jilin Chen

  • Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles

    Brent Hecht;Lichan Hong;Bongwon Suh;Ed H. Chi

  • Virtual voyage: interactive navigation in the human colon

    Lichan Hong;Shigeru Muraki;Arie Kaufman;Dirk Bartz

  • DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems

    Ruoxi Wang;Rakesh Shivanna;Derek Z. Cheng;Sagar Jain

  • Generation of transfer functions with stochastic search techniques

    Taosong He;Lichan Hong;Arie Kaufman;Hanspeter Pfister

  • 3D virtual colonoscopy

    Lichan Hong;A. Kaufman;Yi-Chih Wei;A. Viswambharan

  • Fairness in Recommendation Ranking through Pairwise Comparisons

    Alex Beutel;Jilin Chen;Tulsee Doshi;Hai Qian

  • Method and system for providing search based on topic

    Stuart K Card;Lichan Hong;Peter L Pirolli;Mark J Stefik

  • DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems

    Ruoxi Wang;Rakesh Shivanna;Derek Cheng;Sagar Jain

  • Recommending what video to watch next: a multitask ranking system

    Zhe Zhao;Lichan Hong;Li Wei;Jilin Chen

  • Language Matters In Twitter: A Large Scale Study

    Lichan Hong;Gregorio Convertino;Ed H. Chi

  • Automatic centerline extraction for virtual colonoscopy

    Ming Wan;Zhengrong Liang;Qi Ke;Lichan Hong

  • Eddi: interactive topic-based browsing of social status streams

    Michael S. Bernstein;Bongwon Suh;Lichan Hong;Jilin Chen

  • Self-supervised Learning for Large-scale Item Recommendations

    Tiansheng Yao;Xinyang Yi;Derek Zhiyuan Cheng;Felix Yu

  • Voxel based object simplification

    Taosong He;Lichan Hong;A. Kaufman;A. Varshney

  • Sampling-bias-corrected neural modeling for large corpus item recommendations

    Xinyang Yi;Ji Yang;Lichan Hong;Derek Zhiyuan Cheng

  • Systems and methods for turning pages in a three-dimensional electronic document

    Lichan Hong;Stuart K. Card;Jindong Chen

  • Improving User Topic Interest Profiles by Behavior Factorization

    Zhe Zhao;Zhiyuan Cheng;Lichan Hong;Ed H. Chi

  • Verfahren zur automatischen konzeptuellen Hervorhebung in electronischen Text

    Ed H. Chi;Lichan Hong;Stuart K. Card

  • Controlled topology simplification

    Taosong He;Lichan Hong;A. Varshney;S.W. Wang

  • Is Twitter a Good Place for Asking Questions? A Characterization Study.

    Sharoda A. Paul;Lichan Hong;Ed H. Chi

Frequent Co-Authors

Ed H. Chi
Ed H. Chi Google (United States)
Arie E. Kaufman
Arie E. Kaufman Stony Brook University
Stuart K. Card
Stuart K. Card Stanford University
Zhengrong Liang
Zhengrong Liang Stony Brook University
Peter Pirolli
Peter Pirolli Florida Institute for Human and Machine Cognition
Mark J. Stefik
Mark J. Stefik Palo Alto Research Center
Jock D. Mackinlay
Jock D. Mackinlay Tableau Software (United States)
Greg Corrado
Greg Corrado Google (United States)
Michael S. Bernstein
Michael S. Bernstein Stanford University
Hanspeter Pfister
Hanspeter Pfister Harvard University

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