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Associate Professor

Daniel, Zhengkui WANG

Associate Professor
Director, SIT x Nvidia AI Center (SNAIC)
Director, Data Science & AI Lab @ SIT (DSAIL)
PhD (Computer Science), National University of Singapore, Singapore
Cluster:
Infocomm Technology
Email
Website

Biography

Dr. Daniel, WANG is currently an Associate Professor in the Infocomm Technolgy Cluster,  the director of SIT x NVIDIA  AI center (SANIC), and the director of the Data Science and AI Lab (DSAIL) at Singapore Institute of Technology (SIT).  He received his Ph.D. degree under the supervision of Prof. Tan Kian-Lee at the National Unversity of Singapore in 2013. He was invited as a visiting research scholar to work with Prof. Divyakant Agrawal and Prof. Amr El Abbadi at the University of California at Santa Barabra, USA in 2011-2012. He received his Master's and Bachelor's degrees in computer science and technology from the Harbin Institute of Technology and Heilongjiang University of Science and Technology in 2006 and 2008 respectively.  Prior to joining SIT, he was a research fellow working with Prof. Ooi Beng Chin at the National University of Singapore. 

Dr. Wang's research brings together the fields of Data Science, Artificial Intelligence, and Big Data Analytics.  In particular, his research interests are Machine Learning and Deep Learning, Text Mining, Natural Language Processing, Image Recognition/Annotation/Clustering,  Graph Neural Networks,  Big Data, and Data Warehousing.  His works have been published in more than 60 papers in various international prestigious conferences and journals in these domains, such as AAAI, IJCAI, NuerIPS, SIGMOD,  ICDE, KDD, FSE, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Engineering, Bioinformatics etc.  

Since joining SIT, Dr. Wang has led and participated in various funded applied research projects. He is intrigued to investigate the next generation of AI and Data-driven technologies and Innovations. His research spans a diverse range of interdisciplinary domains including Transportation, Telecommunications, Power Engineering, Healthcare, and Cyber Security. 

SIT Appointments

  • Director, SIT x Nvidia AI Center (SNAIC)
    – Present
  • Associate Professor
    – Present
  • Director, Data Science & AI Lab @ SIT (DSAIL)
    – Present
  • Assistant Professor
    –

Education

  • PhD (Computer Science)
    National University of Singapore , Singapore
  • MSc (Computer Science)
    Harbin Institute of Technology , China
  • BSc (Computer Science)
    Heilongjiang University of Science and Technology , China

Achievements

  • Best Paper Award, 26th International Conference on Pattern Recognition (ICPR), 2022
    –
  • Economy Drive Award, SIT, Singapore
    –
  • Digital Initiative Award, SIT, Singapore
    –
  • Best Paper Presentation Award, Asia Conference on Computers and Communications, 2021
  • 1st Prize on Data-Driven Innovation Challenge (the team supervised by me), IMDA, Singapore
    –
  • Amazon Research Grant Award, Amazon, USA
    –
  • The Best Speaker Award, 3rd NGS Symposium, Singapore
  • NGS Graduate Research Scholarship, NUS, Singapore
    –
  • The Outstanding Peronsal Award, HIT, China
  • 1st Class Undergraduate Scholarship, HIST, China
    –
  • Innovation of Science and Technology: Personal Award, Sci. & Tech. Campaign, China
    –

Professional Memberships

  • IEEE (The Institute of Electrical and Electronics Engineers)
    – Present
  • ACM (Association for Computing Machinery)
    – Present

Corporate Experience

  • Local Chair: 2021 The 2nd Asia Conference on Computers and Communications
    Present
  • Guest Editor: Special Issue on Big Data Analytics for Business Intelligence/Open Journal of Social Sciences/ (ISSN: 2327-5960)
    Present
  • Reviewer: Transactions on Database Systems (TODS)
    Present
  • Reviewer: Journal of Computers (JCP)
    Present
  • Reviewer: IEEE Transactions on Computers (TC)
    Present
  • Reviewer: Distributed and Parallel Databases (DPD)
    Present
  • Reviewer: IEEE Transactions on Knowledge and Data Engineering (TKDE)
    Present
  • Program Chair: THE 2024 2ND INTERNATIONAL CONFERENCE ON DATA, INFORMATION AND COMPUTING SCIENCE, CDICS2024
    –
  • Program Committee: Algorithms and Systems for MapReduce and Beyond Workshop (BeyondMR15, BeyondMR16, BeyondMR17, BeyondMR18)
    –
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Research Interests

  • Artificial Intelligence

    Dr. Wang has a strong interest in deep learning, machine learning, graph neural networks, contrastive learning, data augmentation, and foundational and generative AI models. He has tried to use these technologies in different AI problems in Natural Language Processing (NLP) and text analytics (such as sentiment analytics, topic/entity extraction,  large language models, text classification, and clustering), and Computer Vision (automated image annotation and captioning, object detection,  image Segmentation, depth estimation, Image classification, and clustering).  

     

  • Big Data / Data Science

    With a special interest in data, Dr. Wang is intrigued to examine the entire process of data science and analytics, from data collection, data cleaning/preparation, data modeling, and data visualization until deployment. His research focuses on providing data-driven innovations and solutions for transferring Big Data into Big Values. He has led and participated in various funded data-centered projects utilizing big data, data analytics, data science, business intelligence, and data warehousing techniques together with different industry and government sectors. 

  • Social Media Analytics

    With a special interest in innovative solutions by analyzing different social media data (e.g. such as news, online reviews, and comments) for different applications.

Current Projects

  • Postgraduate Study Opportunities
    – Present

    We have multiple opening positions for Master and Doctorate students. If you are seeking a postgraduate study for a master or doctorate degree, please contact me. The successful candidates will be provided with full scholarships. 

  • We Are Hiring
    – Present

    I am currently looking for Research Fellows and Research Engineers to work in my team on various data science and AI projects. 

    • Key Responsibilities: The RFs/REs will work on research projects in AI, data science, and big data. Meanwhile, they will get the opportunity to co-supervise our doctorate and master students' research. The candidates will also get a chance to work with big companies like Nvidia, and SMRT. The position is for 2 years subject to extension after completion.
    • Job Requirements: 1. hold a Ph.D. or master's degree in the relevant areas, or hold a bachelor's degree but with rich experience in the domain. 2. Strong skill in coding especially on Python. 3. Good communication and interpersonal skills.
    • How to apply: Interested applicants may send your CV to me.

     

     

     

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Journal Papers

  • W. Shan, J. Chew, Z. Wang, A. Sharma, A.B. Ng, S. See, Examining the Cultural Influence on Online Stances Towards COVID-19 Preventive Measures and Their Impact on Incidence and Mortality: A Global Stance Detection Analysis of Tweets, Accepted in SSM - Public Health journal, May 2024 (IF = 4.7) 

  • Y. Wang, Y. Zhao, Z. Wang, C. Zhang, X. Wang, Robust Multi-graph Multi-label Learning with Dual-granularity Labeling, Accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, (IF = 24.314, Top AI Journal) 

  • L Pan, J. Diao, Z. Wang, S. Peng, C. Zhao: HF-YOLO: Advanced Pedestrian Detection Model with Feature Fusion and Imbalance Resolution. Neural Process. Lett. 56(2): 90 (2024)

  • W. Shan, Z. Wang, Q. Zhao, Y. Chu,  Different Cultures, Different Gateways: Culture Shapes Stratified Job Descriptions on LinkedIn, Human Resource Development International journal, DOI: 10.1080/13678868.2023.2260702, Oct 2023 (IF=7.3) 

  • L. Li, Y. Zhao, S. Luo, G. Wang, Z. Wang, "Efficient Community Search in Edge-Attributed Graphs", IEEE Transactions on Knowledge and Data Engineering (TKDE),vol. 35, no. 10, pp. 10790-10806, 1 Oct. 2023, doi:10.1109/TKDE.2023.3267550. (IF = 8.9)

  • W. Shan, Z. Wang, M.Y. Sun, The Impact of Public Responses Towards Healthcare Workers During the COVID-19 Pandemic on Their Work Engagement and Well-being, Frontiers in Psychology, 2022 (IF= 4.232)

  • L. Li, Y. Zhao, Y. Li, F. Wahab, Z. Wang, The Most Active Community Search in Large Temporal Graphs, Knowledge-Based Systems Journal, 2022  (IF: 8.038)

  • Jing Lu, Yuhai Zhao, Kian-Lee Tan, Zhengkui Wang* . Distributed Density Peaks Clustering Revisited. IEEE Transactions on Knowledge and Data Engineering (TKDE - Top Journal), 2, 560-584 (2020)

  • Yan Chu, Xiao Yue, Lei Yu, Mikhailov Sergei, Zhengkui Wang*: Automatic Image Captioning Based on ResNet50 and LSTM with Soft Attention. Wirel. Commun. Mob. Comput. 2020: 8909458:1-8909458:7 (2020)

  • Yejiang Wang, Yuhai Zhao, Zhengkui Wang, Chengqi Zhang: Towards Coarse and Fine-grained Multi-Graph Multi-Label Learning. CoRR abs/2012.10650 (2020)

  • Yan Chu, Xiao Yue, Quan Wang, Zhengkui Wang: SecureAS: A Vulnerability Assessment System for Deep Neural Network Based on Adversarial Examples. IEEE Access 8: 109156-109167 (2020)

  • Zhengkui Wang, Guangdong Bai, Soumyadeb Chowdhury, Quanqing Xu, Zhi Lin Seow: TwiInsight: Discovering Topics and Sentiments from Social Media datasets.  CoRR abs/1705.08094

  • Huiju Wang, Zhengkui Wang, Kian-Lee Tan, Chee-Yong Chan, Qi Fan, Xiao Yue: VCExplorer: A Interactive Graph Exploration Framework Based on Hub Vertices with Graph Consolidation. CoRR abs/1709.06745

  • Zhengkui Wang, Yan Chu, Kian-Lee Tan, Divyakant Agrawal, Amr EI Abbadi, and Xiaolong Xu. Scalable Data Cube Analysis over Big Data, CoRR

  • Zhengkui Wang, Divyakant Agrawal and Kian-Lee Tan. COSAC: A Framework for Combinatorial Statistical Analysis on Cloud, IEEE Transactions on Knowledge and Data Engineering (TKDE), 25(9), PP. 2010-2023

  • Zhengkui Wang, Yue Wang, Kian-Lee Tan, Limsoon Wong and Divyakant Agrawal. eCEO: An    Efficient Cloud Epistasis Computing Model in Genome-wide Association Study, Bioinformatics,   Oxford University Press, 27(8), PP. 1045-1051

Conferences

  • S. Jiang, T. Ma, X. Miao, Z. Wang, T. Zang, Vicinal Data Augmentation for Classification Model via Feature Weaken, Engineering and Management (KSEM 2024), PP. 334-346, Singapore: Springer Nature Singapore, 2024

  • Y. Chu, K. Liu, S. Jiang, X. Sun, B. Wang and Z. Wang, Meta-Pruning: learning to prune on few-shot learning, 17th international Conference on Knowledge Science, Engineering and Management (KSEM 2024), Singapore: Springer Nature Singapore, 2024

  • Y. Zhao, Y. Wang, Z. Wang, W. Shan,  M. Huang, M. Wang, M. Huang, X. Wang, Towards Robust Multi-Label Learning against Dirty Label Noise, Accepted as full paper  in the 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), Jeju, 3 Aug - 9 Aug 2024, ( Top-tier AI Conference. News! )

  • L. Pang, X. Li, Z. Wang, N. Yang, W. Shan, Enhancing Multi-Label Text Classification by Incorporating Label Dependency to Handle Imbalanced Data, Accepted as full paper in the International Joint Conference on Neural Networks (IJCNN 2024), Yokohama, Japan, June 30-July 5 2024. 

  • W. Shan, J. Chew, Z. Wang, A. Sharma, A.B. Ng, S. See, From Words to Walls: Deciphering Cultural Impact on Gender Bias in Job Descriptions,  Accepted as the full-paper in the 37th annual conference of IACM (IACM 2024), Singapore, June 23- 26, 2024

  • W. Shan, J. Chew, Z. Wang, A. Sharma, A.B. Ng, S. See, From Words to Walls: Deciphering Cultural Impact on Gender Bias in Job Descriptions,  Accepted as the full-paper in the Eastern Academy of Management International on AI (EAMI 2024), Taipei, Taiwan, June 17- 21, 2024

  • Y. Li, X. Chen, Y. Zhao, W. Shan, Z. Wang, G. Yang, G. Wang, Self-Training GNN-based Community Search in Large Attributed Heterogeneous Information Networks, Accepted as a full paper in 40th IEEE International Conference on Data Engineering (ICDE2024), Utrecht, Netherlands, 13th - 17th May 2024. (Top-tier Conference - News!)

  • L. Li, Y. Zhao, S. Luo, G. Wang, Z. Wang, "Efficient Community Search in Edge-Attributed Graphs", Accepted as a poster, 40th IEEE International Conference on Data Engineering (ICDE 2024), Utrecht, Netherlands, 13 -17 May 2024  (Top-tier Conference - News!)

  • L. Pan, Y. Yang, Z. Wang, W. Shan, J. Yin, Open-Vocabulary And Multitask Image Segmentation, SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, Poster, PP 104801049, April 2024

  • Y. Wang, Y. Zhao, Z. Wang, W. Shan, X. Wang, "Limited-Supervised Multi-Label Learning with Dependency Noise", Accepted as a full paper in AAAI2024, Thirty-Eighth AAAI conference on Artificial Intelligence, Feb 20-27, 2024, Vancouver, Canada, (Top-tier AI conference - News!)

  • Y. Wang, Y. Zhao, Z. Wang, L. Li, GALOPA: Graph Transport Learning with Optimal Plan Alighment, Accepted in The 37th Annual Conference on Neural Information Processing System, NeurIPS 2023, New Orleans Ernest N. Morial Convention Center, 10-16 Dec, 2023. (The Top-tier AI conference! - News!)

  • L. Pan, Y. Yang, Z.i Wang, R. Zhang, W. Shan, and J. Li. 2023. Image Segmentation with Vision-Language Models. In 2023 7th International Conference on Computer Science and Artificial Intelligence (CSAI) (CSAI 2023), December 08--10, 2023, Beijing, China. ACM, New York, NY, USA 6 Pages. https://doi.org/10.1145/3638584.3638624

  • Y. Chu, X. Sun, T. Xie, Z. Wang, and W. Shan, "Imbalanced Few-shot Learning based on Meta-transfer Learning", Accepted in the 32nd International Conference on Artificial Neural Networks (ICANN 2023), Crete, Greece, 26-29 Sep, 2023 

  • H. Wang, Y. Chu, H. Ning, Z. Wang, and W. Shan, "User Feedback-based Counterfactual Data Augmentation for Sequential Recommendation", Accepted in KSEM 2023 ( The 16th International Conference on Knowledge Science, Engineering and Management), Aug 16-18, Guangzhou, China, 2023. 

  • W. Shan, J. Chew, Z. Wang, A. Sharma, A.B. Ng, S. See, "Culture Matters, But Not Always: How Cultural Impacts Vary Across Various Preventive Measures Against COVID-19",  Accepted in The 36th conference of IACM,   9-12 July 2023, Thessaloniki, Greece. 

  • W. Shan, Z. Wang, Y. Su, A. Loh. , "Conflicting Voices of Campaigns for Healthcare Workers During COVID-19: Positive or Negative Depends on Culture", Accepted in the 36th conference of IACM, 9-12 July 2023, Thessaloniki, Greece. 

  • S. Jiang, Y. Chu, Z. Wang, T. Ma, H. Wang, W. Lu, T. Zang. B. Wang, "Explainable Text Classification via Attentive and Targeted Mixing Data Augmentation", Accepted in The 32nd International Joint Conference on Artificial Intelligence (IJCAI-23), (TOP AI conference, News!!!) 

  • L. Li, S. Luo, Y. Zhao, C. Shan, Z. Wang, L. Qing, COCLEP: Contrastive Learning-based Semi-Supervised Community Search,  in 39th IEEE International Conference on Data Engineering (ICDE 2023),  USA,  April 3-7, 2023. Accepted as full paper. (Rank 1 Conference, News!!!) 

  • J. Lu, Y. Zhao, Z. Wang, G. Wang, Skyline Micro-Cluster Query: A Novel and Practical Spatial Query, in 39th IEEE International Conference on Data Engineering (ICDE 2023),  USA,  April 3-7, 2023. Accepted as full paper. (Rank 1 Conference, News!!!) 

  • W.S. Ng, J. Sasikumar, Y.H. Wong, O.R. Khan, Z.H. Ng, A.S. Sahar, H. Guo, Z. Zhang, Z. Wang,  The Impact of the COVID-19 Pandemic on Retrenchment, Vaccinations, and Global Happiness, 15th International Conference Developments in eSystems Engineering ( DeSE 23), 2023 

  • W.Z. Tan, J.H. Lim, K. Tan, R.K. Tech, A.K. Singh. A.S. Sahar. Z. Wang, BrandTrend: Understanding the Trending Games and Gaming Influencers for Better Gaming Peripheral Promotion, 15th International Conference Developments in eSystems Engineering ( DeSE 23), 9-11 Jan, 2023

  • Y. Wang, Y. Zhao, Z. Wang, M. Wang, Robust Self-supervised Multi-instance Learning with Structure Awareness, accepted at the Thirty-Seventh AAAI conference on Artificial Intelligence (AAAI-23). (Top-tier AI conference, News!!!) 

  • Y. Shi, Z. Wang*, D. Lo, X. Xia, T. Zhang, Y. Zhao, B. Xu, How to Better Utilize Code Graphs in Semantic Code Search?, ESEC/FSE 2022  The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) , Nov 2022, Singapore (Top-tier conference)

  • Q. Zhao, L. Li, Y. Chu, Z. Wang, W. Shan, Density Division Face clustering Based on Graph Convolutional Networks, 26TH International Conference on Pattern Recognition (ICPR),  Aug 21-25, Montréal Québec, 2022 (The Best Paper Award!!!)

  • J. Xue, S. Qu, J. Li, Y. Chu and Z. Wang, TSC-GCN: A Face Clustering Method based on GCN, KSEM, Singapore 2022

  • I. Tuhin, P. Loh and Z. Wang, “Smart Cybercrime Classification for Digital Forensics with Small Datasets”, The 6th International Symposium on Cyber Security, Cryptology and Machine Learning (CSCML 2022). 270-280, 2022

  • Y. Chu, J. Guo, W. Shan, Z. Wang, “An Efficient One-stage Object Detection Model based on FCOS”, 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design, Hangzhou China, 617-622, 2022

  • Z. Wang, S. Chowdhury, M. Y. H. Low and W. Shan, "NewsInsider: Innovating News Understanding to Improve the Quality of Reading Experience", 2021 Asia Conference on Computers and Communications, Singapore, Sep 24-27, 2021, (BEST PAPER PRESENTATION AWARD)

  • Yan Chu, Zhengkui Wang*, Lina Wang, Qingchao Zhao and Wen Shan, "Fine-Grained Image Classification Based on Target Acquisition and Feature Fusion" Accepted in the 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021) as a regular paper, Tokyo, Japan, August 14-16, 2021 

  • Qingchao Zhao, Jing Yang, Zhengkui Wang*, Yan Chu, Wen Shan and Isfaque Al Kaderi Tuhin, "Clustering Massive-categories and Complex Documents via Graph Convolutional Network", Accepted in the 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021) as a regular paper, Tokyo, Japan, August 14-16, 2021 

  • Yejiang Wang, Yuhai Zhao, Zhengkui Wang*, Chengqi Zhang, Multi-graph Multi-label Learning with Dual-granularity Labeling, KDD 21, pp 2327-2337, 2021

  • Jing Lu, Yuhai Zhao, Kian-Lee Tan, Zhengkui Wang*, 2021, Distributed Density Peaks Clustering Revisited, 37th IEEE International Conference on Data Engineering (ICDE - Rank 1 Conference)

  • Yan Chu, Shuhao Qi, Yue Yang, Chenqi Shan, Lina Wang, Zhengkui Wang: An Attention-Based Recommendation Algorithm. ISPA/BDCloud/SocialCom/SustainCom 2019: 1505-1510

  • Zhengkui Wang, Yan Chu, Kian-Lee Tan, Divyakant Agrawal and Amr El Abbadi, HaCube: Extending MapReduce for Efficient OLAP Cube Materialization and View Maintenance, The 21st International Conference on Database Systems for Advanced Applications (DASFAA), Dallas, TX, USA, PP 113-129

  • Yan Chu, Hongbin Wang, Liying Zheng, Zhengkui Wang*, Kian-Lee Tan: TRSO: A Tourism Recommender System Based on Ontology. KSEM 2016, PP 567-579

  • Qi Fan, Zhengkui Wang, Chee-Yong Chan, Kian-Lee Tan, “Towards neighborhood window analytics over large-scale graphs”, The 21st International Conference on Database Systems for Advanced Applications (DASFAA), Dallas, TX, USA, PP 201-217

  • Qian Lin, Pengfei Chang, Chen Gang, Beng Chin Ooi, Kian-Lee Tan, Zhengkui Wang, Towards a Non-2PC Transaction Management in Distributed Database Systems, ACM International Conference on Management of Data, SIGMOD 2016, San Francisco, USA, PP 1659-1674

  • Lei Yang, Yan Chu, Guangyu Li, Xingmei Wang, Linlin Xia, Zhengkui Wang, Kian-Lee Tan, “A flexible and reliable recommendation algorithm in intelligent transportation system”, 10th International Conference on Digital Information Management, ICDIM 2015, Jeju Island, South Korea, PP 229-233

  • Lei Yang, Yan Chu, Jianpei Zhang, Linlin Xia, Zhengkui Wang*, “Transfer Learning Over Big Data”, 10th International Conference on Digital Information Management, (ICDIM) 2015, Jeju Island, South Korea, PP 63-68

  • Yan Chu, Zhengkui Wang*, Man Chen, Linlin Xia, Fengmei Wei and Mengnan Cai, “Transfer Learning in Large-Scale Short Text Analysis”. The 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015, Chongqing, China, PP 499-511

  • Qian Lin, Beng Chin Ooi, Zhengkui Wang and Cui Yu, “Scalable Distributed Stream Join Processing”, ACM International Conference on Management of Data, SIGMOD 2015, Melbourne, Australia, PP 811-825

  • Zhengkui Wang, Qi Fan, Huiju Wang, Kian-Lee Tan, Divyakant Agrawal, Amr El Abbadi, Pagrol: Parallel graph OLAP over large-scale attributed graphs, IEEE 30th International Conference on Data Engineering(ICDE), Chicago, Illinois, USA, PP 496-507

  • Qian Xiao, Zhengkui Wang and Kian-Lee Tan. LORA: Link Obfuscation by Randomization in Graphs, Proceedings of the 8th VLDB Workshop on Secure Data Management (SDM), Seattle, WA, USA, PP. 33-51

  • Zhengkui Wang, Yue Wang, Kian-Lee Tan, Limsoon Wong and Divyakant Agrawal. CEO: A Cloud  Epistasis Computing Model in GWAS, IEEE Conference on Bioinformatics and Biomedicine (BIBM) , Hong Kong, PP. 85-90

Books

  • Kuan-Huei Lee, Zhengkui Wang and Nur SyaZeema Binte Sazari, " Uncovering Food Experience from Social Media", Accepted as a book chapter in the Handbook on Tourism and Social Media, ISBN: 9781800371408.

  • Chapter on "Graph OLAP" - Encyclopedia of Database Systems (EDBS) Published by Springer

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Past

  • ICT1002 Programming Fundamentals on Python Programming
  • ICT2103 Information Management on Big Data Management with NoSQL Databases and Data Warehousing
  • ICT1009 Objective Oriented Programming on Java Programming
  • ICT2107 Distributed System Programming on Cloud Computing, Hadoop and its Related Systems
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