Kaiping Zheng

Kaiping Zheng

Senior Research Fellow

National University of Singapore

Biography

Kaiping Zheng is a Senior Research Fellow in Database System Research Group, National University of Singapore (NUS). She obtained her Ph.D. degree in Computer Science from NUS in 2020 with IMDA Excellence Prize for Best Ph.D. Thesis, supervised by Prof. Beng Chin Ooi.

Her research interests mainly focus on facilitating high quality and interpretable healthcare delivery, driven by healthcare data and artificial intelligence technologies. She is currently collaborating with clinicians on various medical problems in healthcare practice ranging from clinical medicine to lifestyle intervention.

Interests

  • Healthcare Data Representation Learning
  • Interpretable Healthcare Analytics
  • Healthcare Data Management

Education

  • Ph.D. in Computer Science, 2020

    National University of Singapore

  • B.Eng. in Computer Science, 2014

    Harbin Institute of Technology

Selected Publications

(2024). Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics. International Conference on Machine Learning.

(2024). CohortNet: Empowering Cohort Discovery for Interpretable Healthcare Analytics. 50th International Conference on Very Large Databases, VLDB 2024.

(2024). Development of a dental diet-tracking mobile app for improved caries-related dietary behaviours: Key features and pilot evaluation of quality. Digital Health.

(2023). Application of Artificial Intelligence in the Assessment of Thyroid Eye Disease (TED) - A Scoping Review. Frontiers in Endocrinology.

(2022). DyHealth: Making Neural Networks Dynamic for Effective Healthcare Analytics. 48th International Conference on Very Large Databases, VLDB 2022.

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(2022). eDental: Managing Your Dental Care in Diet Diaries (Best Demo Paper Award Runner Up). Proceedings of the 2022 ACM on Conference on Information and Knowledge Management (demo), CIKM 2022, Atlanta, Georgia, USA, October 17-21, 2022.

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(2022). ELDA: Learning Explicit Dual-Interactions for Healthcare Analytics. 38th IEEE International Conference on Data Engineering, ICDE 2022, May 9-12, 2022.

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(2021). Healthcare Analytics with Time-invariant and Time-variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study. Journal of Medical Internet Research (JMIR).

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(2021). Towards Robust Cross-domain Image Understanding with Unsupervised Noise Removal. MM ‘21: ACM Multimedia Conference, Virtual Event, China, October 20 - 24, 2021.

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(2021). PACE: Learning Effective Task Decomposition for Human-in-the-loop Healthcare Delivery. Proceedings of the 2021 International Conference on Management of Data, SIGMOD Conference 2021, June 20 - June 25, 2021.

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(2021). ARM-Net: Adaptive Relation Modeling Network for Structured Data. Proceedings of the 2021 International Conference on Management of Data, SIGMOD Conference 2021, June 20 - June 25, 2021.

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(2021). MLCask: Efficient Management of Component Evolution in Collaborative Data Analytics Pipelines. 37th IEEE International Conference on Data Engineering, ICDE 2021, April 19-22, 2021.

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(2020). TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications. Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, Portland, OR, USA, June 14 - 19, 2020.

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(2017). Big Healthcare Data Analytics: Challenges and Applications. Handbook of Large-Scale Distributed Computing in Smart Healthcare.

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(2017). Capturing Feature-Level Irregularity in Disease Progression Modeling. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM 2017, Singapore, November 06 - 10, 2017.

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(2017). Resolving the Bias in Electronic Medical Records. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17, 2017.

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(2015). SINGA: A Distributed Deep Learning Platform. Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM ‘15, Brisbane, Australia, October 26 - 30, 2015.

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Professional Services

  • PC Member for VLDB 2022, 2025
  • PC Member for ICDE 2023, 2024
  • PC Member for NeurIPS 2024
  • PC Member for SIGKDD 2022, 2023 - 2024 (Research Track, ADS Track)
  • PC Member for AAAI 2021, 2022, 2024
  • PC Member for IJCAI 2023 - 2024
  • PC Member for SDM 2024
  • PC Member for ICDE 2023 PhD Symposium
  • PC Member for DASFAA 2023 - 2024 (Demo Track)
  • PC Member for ECML-PKDD 2023 - 2024 (ADS Track)
  • PC Member for SISAP 2020 - 2024
  • Session Chair for VLDB 2022
  • Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering
  • Invited Reviewer for IEEE Transactions on Big Data
  • Invited Reviewer for IEEE Transactions on Cloud Computing
  • Invited Reviewer for IEEE Transactions on Signal Processing
  • Invited Reviewer for Communications of the ACM
  • Invited Reviewer for ACM Transactions on Knowledge Discovery from Data
  • Invited Reviewer for ACM Transactions on Data Science
  • Invited Reviewer for ACM Journal of Data and Information Quality
  • Invited Reviewer for Neural Networks
  • Invited Reviewer for Information Fusion
  • Invited Reviewer for Computers in Biology and Medicine
  • Invited Reviewer for Artificial Intelligence in Medicine
  • Invited Reviewer for JMIR Medical Informatics
  • Invited Reviewer for BMC Medical Research Methodology
  • Invited Reviewer for Expert Systems With Applications
  • Invited Reviewer for Behavior Research Methods
  • Invited Reviewer for Signa Vitae
  • Invited Reviewer for Biomedical Signal Processing and Control
  • Invited Reviewer for Engineering Structures
  • Vidi Grant Reviewer for the Dutch Research Council

Invited Talks

Electronic Health Records Analytics in Hospital-Acquired AKI Prediction.

Clinician-Scientist Talk, NUHS, 2021.

Towards Boosting Performance of Healthcare Analytics: Resolving Challenges in Electronic Medical Records.

SoC Research Talk, School of Computing in NUS, 2018. Slides

Disease Progression Modelling for Chronic Kidney Disease - A Deep Learning Approach.

Clinical Artificial Intelligence in the Age of Precision Medicine, NUHS, 2017.

Teaching

  • CS4225 - Massive Data Processing Techniques in Data Science, NUS, Teaching Assistant.
  • CS2102 - Database Systems, NUS, Teaching Assistant.

Awards

  • Best Demo Paper Award (Runner Up), CIKM 2022
  • Valedictorian Speech, NUS School of Computing, 2021. Video
  • IMDA Excellence Prize 2020 for Best Ph.D. Thesis, Singapore, 2019 - 2020.
  • NUS Dean’s Graduate Research Excellence Award, Singapore, 2017 - 2018.
  • NUS Research Achievement Award, Singapore, 2016 - 2017.
  • NUS Research Scholarship, Singapore, 2014 - 2018.
  • National Scholarship, China, 2011 - 2012.