See-Kiong Ng

5.4k total citations
138 papers, 2.6k citations indexed

About

See-Kiong Ng is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, See-Kiong Ng has authored 138 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Artificial Intelligence, 43 papers in Molecular Biology and 24 papers in Information Systems. Recurrent topics in See-Kiong Ng's work include Bioinformatics and Genomic Networks (32 papers), Topic Modeling (27 papers) and Natural Language Processing Techniques (18 papers). See-Kiong Ng is often cited by papers focused on Bioinformatics and Genomic Networks (32 papers), Topic Modeling (27 papers) and Natural Language Processing Techniques (18 papers). See-Kiong Ng collaborates with scholars based in Singapore, China and United States. See-Kiong Ng's co-authors include Xiaoli Li, Min Wu, Chee-Keong Kwoh, Chris Soon Heng Tan, Chee Keong Kwoh, Peng Yang, Mong Li Lee, Wynne Hsu, Marie Wong and Zhuo Zhang and has published in prestigious journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

See-Kiong Ng

116 papers receiving 2.5k citations

Peers

See-Kiong Ng
Lun Hu China
Arlindo L. Oliveira Portugal
Roberto Santana Spain
Heitor Silvério Lopes Brazil
Jungang Lou China
Peter Widmayer Switzerland
Zili Zhang China
Alberto Marchetti-Spaccamela Italy
Nagarajan Natarajan United States
André Elisseeff Germany
Lun Hu China
See-Kiong Ng
Citations per year, relative to See-Kiong Ng See-Kiong Ng (= 1×) peers Lun Hu

Countries citing papers authored by See-Kiong Ng

Since Specialization
Citations

This map shows the geographic impact of See-Kiong Ng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by See-Kiong Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites See-Kiong Ng more than expected).

Fields of papers citing papers by See-Kiong Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by See-Kiong Ng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by See-Kiong Ng. The network helps show where See-Kiong Ng may publish in the future.

Co-authorship network of co-authors of See-Kiong Ng

This figure shows the co-authorship network connecting the top 25 collaborators of See-Kiong Ng. A scholar is included among the top collaborators of See-Kiong Ng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with See-Kiong Ng. See-Kiong Ng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Wenjie, et al.. (2025). A Federated Framework for LLM-based Recommendation. 2852–2865. 3 indexed citations
2.
3.
4.
Shi, Wenhao, Yi Bin, Junhua Liu, et al.. (2024). Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models. 4663–4680. 6 indexed citations
5.
Zhang, Bo, et al.. (2024). Open Set Bearing Fault Diagnosis with Domain Adaptive Adversarial Network under Varying Conditions. Actuators. 13(4). 121–121. 4 indexed citations
6.
Luu, Anh Tuan, et al.. (2024). From Static to Dynamic: Knowledge Metabolism for Large Language Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23784–23786.
7.
Wang, Wenjie, Xinyu Lin, Jizhi Zhang, et al.. (2024). Learnable Item Tokenization for Generative Recommendation. 2400–2409. 16 indexed citations
8.
9.
10.
Gollapalli, Sujatha Das, et al.. (2023). Socratic Question Generation: A Novel Dataset, Models, and Evaluation. 147–165. 4 indexed citations
11.
Gollapalli, Sujatha Das, et al.. (2023). Identifying Early Maladaptive Schemas from Mental Health Question Texts. 11832–11843. 2 indexed citations
12.
Ng, See-Kiong, et al.. (2023). Constructing and Interpreting Causal Knowledge Graphs from News. Proceedings of the AAAI Symposium Series. 1(1). 52–59. 1 indexed citations
13.
Hooi, Bryan, et al.. (2023). Learning Hierarchical Spatial Tasks with Visiting Relations for Next POI Recommendation. 1(4). 1–26. 1 indexed citations
14.
Yi, Bin, Wenhao Shi, Lei Wang, et al.. (2023). Non-Autoregressive Math Word Problem Solver with Unified Tree Structure. 3290–3301. 2 indexed citations
15.
Yin, Yifang, Ying Zhang, Guanfeng Wang, et al.. (2023). Multimodal Deep Learning for Robust Road Attribute Detection. ACM Transactions on Spatial Algorithms and Systems. 9(4). 1–25. 3 indexed citations
16.
Fu, Jinlan, See-Kiong Ng, & Pengfei Liu. (2022). Polyglot Prompt: Multilingual Multitask Prompt Training. 9919–9935. 5 indexed citations
17.
Yang, Peng, Xiaoli Li, Min Wu, Chee-Keong Kwoh, & See-Kiong Ng. (2011). Inferring Gene-Phenotype Associations via Global Protein Complex Network Propagation. PLoS ONE. 6(7). e21502–e21502. 68 indexed citations
18.
Nguyen, Minh Nhut, Xiaoli Li, & See-Kiong Ng. (2011). Positive Unlabeled Leaning for Time Series Classification.. International Joint Conference on Artificial Intelligence. 1421–1426. 11 indexed citations
19.
Li, Xiaoli, et al.. (2010). Distributional Similarity vs. PU Learning for Entity Set Expansion. Meeting of the Association for Computational Linguistics. 359–364. 12 indexed citations
20.
Ng, See-Kiong, Zexuan Zhu, & Yew-Soon Ong. (2004). Whole-genome functional classification of genes by latent semantic analysis on microarray data. 123–129. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Lun Hu Breakdown of academic impact, for papers by Arlindo L. Oliveira Breakdown of academic impact, for papers by Roberto Santana Breakdown of academic impact, for papers by Heitor Silvério Lopes Breakdown of academic impact, for papers by Jungang Lou Breakdown of academic impact, for papers by Peter Widmayer Breakdown of academic impact, for papers by Zili Zhang Breakdown of academic impact, for papers by Alberto Marchetti-Spaccamela Breakdown of academic impact, for papers by Nagarajan Natarajan Breakdown of academic impact, for papers by André Elisseeff
Rankless by CCL
2026