World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
7949
World Ranking
9202
National Ranking
117

Overview

See-Kiong Ng is affiliated with the National University of Singapore, where their research primarily focuses on computer science. Their expertise spans several subfields including artificial intelligence, computer vision and pattern recognition, information systems, control and systems engineering, and computer networks and communications.

The scientist has contributed extensively to topics such as topic modeling, natural language processing techniques, multimodal machine learning applications, speech and dialogue systems, recommender systems and techniques, video analysis and summarization, and human pose and action recognition.

See-Kiong Ng's recent published papers include:

  • GPTScore: Evaluate as You Desire (2023), arXiv (Cornell University)
  • Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation (2022), Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • An Enhanced GAN Model for Automatic Satellite-to-Map Image Conversion (2020), IEEE Access
  • Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery (2022), Proceedings of the 30th ACM International Conference on Multimedia
  • MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks (2022), 2022 IEEE 38th International Conference on Data Engineering (ICDE)

Frequent co-authors collaborating with See-Kiong Ng include:

  • Tat-Seng Chua
  • Bryan Kian Hsiang Low
  • Xiaobao Wu
  • Bryan Hooi
  • Anh Tuan Luu

The scientist's publications appear regularly in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Actuators
  • SSRN Electronic Journal
  • Mathematics

In addition to articles, See-Kiong Ng has contributed to book publications with Springer Science+Business Media, including works titled Advances in Knowledge Discovery and Data Mining, published in 2020.

Best Publications

  • MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks

    Dan Li;Dacheng Chen;Lei Shi;Baihong Jin

  • A core-attachment based method to detect protein complexes in PPI networks

    Min Wu;Xiaoli Li;Chee Keong Kwoh;See-Kiong Ng

  • Computational approaches for detecting protein complexes from protein interaction networks: a survey

    Xiaoli Li;Min Wu;Chee-Keong Kwoh;See-Kiong Ng

  • Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series

    Dan Li;Dacheng Chen;Jonathan Goh;See-kiong Ng

  • Integrative approach for computationally inferring protein domain interactions.

    See-Kiong Ng;Zhuo Zhang;Soon-Heng Tan

  • Positive-unlabeled learning for disease gene identification

    Peng Yang;Xiao-Li Li;Jian-Ping Mei;Chee-Keong Kwoh

  • MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks

    Dan Li;Dacheng Chen;Baihong Jin;Lei Shi

  • Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

    See-Kiong Ng;Marie Wong

  • InterDom: a database of putative interacting protein domains for validating predicted protein interactions and complexes

    See-Kiong Ng;Zhuo Zhang;Soon-Heng Tan;Kui Lin

  • STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation

    Nicholas Lim;Bryan Hooi;See-Kiong Ng;Xueou Wang

  • GPTScore: Evaluate as You Desire

    Unknown

  • Interaction graph mining for protein complexes using local clique merging.

    Xiao-Li Li;Chuan-Sheng Foo;Chuan-Sheng Foo;Soon-Heng Tan;Soon-Heng Tan;See-Kiong Ng

  • Discovery of significant rules for classifying cancer diagnosis data

    Jinyan Li;Huiqing Liu;See-Kiong Ng;Limsoon Wong

  • NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs

    Jin Chen;Wynne Hsu;Mong Li Lee;See-Kiong Ng

  • Toward fully automated genotyping: genotyping microsatellite markers by deconvolution.

    M W Perlin;G Lancia;S K Ng

  • Positive Unlabeled Learning for Data Stream Classification.

    Xiao Li Li;Philip S. Yu;Bing Liu;See Kiong Ng

  • Integrated Oversampling for Imbalanced Time Series Classification

    Hong Cao;Xiao-Li Li;David Yew-Kwong Woon;See-Kiong Ng

  • Discovering protein complexes in dense reliable neighborhoods of protein interaction networks.

    Xiao-Li Li;Chuan-Sheng Foo;See-Kiong Ng

  • Intelligent Fault Diagnosis Under Varying Working Conditions Based on Domain Adaptive Convolutional Neural Networks

    Bo Zhang;Wei Li;Xiao-Li Li;See-Kiong Ng

  • A protein interaction extraction system

    See Kiong Ng;Lim Soon Wong

  • Increasing confidence of protein interactomes using network topological metrics

    Jin Chen;Wynne Hsu;Mong Li Lee;See-Kiong Ng

  • Ensemble Positive Unlabeled Learning for Disease Gene Identification

    Peng Yang;Xiaoli Li;Hon-Nian Chua;Chee-Keong Kwoh

Frequent Co-Authors

Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Limsoon Wong
Limsoon Wong National University of Singapore
Wing-Kin Sung
Wing-Kin Sung Chinese University of Hong Kong
Chee Keong Kwoh
Chee Keong Kwoh Nanyang Technological University
Wynne Hsu
Wynne Hsu National University of Singapore
Mong Li Lee
Mong Li Lee National University of Singapore
Roger Zimmermann
Roger Zimmermann National University of Singapore
Bing Liu
Bing Liu University of Illinois at Chicago
Chai Quek
Chai Quek Nanyang Technological University
Jinyan Li
Jinyan Li University of Technology Sydney

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing Computer Science in the USA opens doors to a wide range of online degrees and flexible career pathways. For those interested in data analysis and artificial intelligence, the data science learning path provides a practical and affordable way to build expertise in this in-demand field.

If you prefer a more technical or engineering-focused direction, an online bachelor’s in electrical engineering can also complement a computer science background, giving you the skills to work in areas like robotics, hardware, and embedded systems.

Many students are seeking fast entry points into the tech job market. Consider exploring easy certifications that pay well in fields such as cybersecurity, networking, or cloud computing. These credentials can boost your resume and quickly expand your career options.

For those aiming to accelerate their education, there are also programs among the quickest online masters degree options, allowing you to boost qualifications and earning potential in as little as a year.

Best Scientists Citing See-Kiong Ng

Trending Scientists