I am a Ph.D. Candidate at National University of Singapore (NUS), under the supervision of Prof. Feng Mengling. My research focuses on designing and applying machine learning algorithms that help to solve real-world healthcare problems. Before Ph.D., I graduated from NUS with a master’s degree in electrical & computer engineering and did my research intern at IBM Research.

Research Interests

Machine Learning for Healthcare

• Self-Supervised Learning for Medical Time Series
• Explainable Models for Medical Time Series
• Multimodal Models for Medical Time Series
• Electronic Medical Records Data Mining

General Machine Learning

• Contrastive Learning
• Multimodal Models

News

• [08. 2024] Our survey paper on language modeling for tabular data now available at arXiv.
• [06. 2024] Our paper on multi-stage contrastive learning is accepted in ECCV 2024.
• [06. 2024] I have been selected as a recipient for the Graduate Student Research Award AY2023/2024!
• [03. 2024] Our paper on multi-stage contrastive learning now available at arXiv.
• [01. 2024] Our paper on contrastive learning for time series applications is accepted in ICLR 2024.
• [12. 2023] I will serve as the student organizer of the Health Day Event at The WEB Conference WWW.
• [11. 2023] Our paper on building a large-scale real-wold surgery database now available at KJA.
• [10. 2023] Our survey on LLM for healthcare applications now available at arXiv.
• [05. 2023] Our paper on contrastive learning for time series applications now available at arXiv.
• [01. 2023] Our paper on predicting surgical duration now available at arXiv.
• [05. 2022] Our paper about federated learning on electronic health records is accepted in TIST.
• [12. 2021] Our paper about self-supervised learning for ECG is accepted in AAAI 2022.
• [06. 2021] Our paper about multivariate ECG time series classification is accepted in PMEA.
• [04. 2021] Our paper about domain adaptation for time series is accepted in IJCNN 2021.
• [12. 2020] Our team won the Championship in SG Healthcare AI Datathon 2020.
• [09. 2020] Our team won the 2nd Runner-up in PhysioNet/Computing in Cardiology Challenge 2020.
• [01. 2020] Join NUS Healthcare-AI Lab.
• [07. 2019] Conferred master’s degree by NUS.
• [05. 2019] Start internship at IBM Research.

Publications (* co-first author)

• Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution
  Yucheng Ruan*, Xiang Lan*, Jingying Ma, Yizhi Dong, Kai He, Mengling Feng
  preprint
  [Paper][Project Page]

• Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning
  Jihai Zhang*, Xiang Lan*, Xiaoye Qu, Yu Cheng, Mengling Feng, Bryan Hooi
  The 18th European Conference on Computer Vision ECCV 2024
  [Paper][Code]

• Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
  Xiang Lan, Hanshu Yan, Shenda Hong, Mengling Feng
  International Conference on Learning Representations ICLR 2024 (Ranked 10 in Google Scholar Top publications)
  [Paper][Code]

• The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry
  Hairil Rizal Abdullah, Daniel Yan Zheng Lim, Yuhe Ke, Nur Nasyitah Mohamed Salim, Xiang Lan, Yizhi Dong, Mengling Feng
  Korean Journal of Anesthesiology KJA
  [Paper]

• A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics
  Kai He, Rui Mao, Qika Lin, Yucheng Ruan, Xiang Lan, Mengling Feng, Erik Cambria
  preprint
  [Paper]

• Medical Intervention Duration Estimation Using Language-enhanced Transformer Encoder with Medical Prompts
  Yucheng Ruan*, Xiang Lan*, Daniel J Tan, Hairil Rizal Abdullah, Mengling Feng
  preprint
  [Paper]

• Intra-Inter Subject Self-Supervised Learning for Multivariate Cardiac Signals
  Xiang Lan, Dianwen Ng, Shenda Hong, Mengling Feng
  Association for the Advancement of Artificial Intelligence AAAI 2022 (15% acceptance rate)
  [Paper]

• Federated Learning for Electronic Health Records
  Trung Kien Dang*, Xiang Lan*, Jianshu Weng, Mengling Feng
  ACM Transactions on Intelligent Systems and Technology TIST
  [Paper]

• Adversarial Domain Adaptation with Correlation-Based Association Networks for Longitudinal Disk Fault Prediction (Oral Presentation)
  Xiang Lan*, Dianwen Ng*, Yi Liu, Jiongzhou Liu, Fan Xu, Cheng He and Mengling Feng
  International Joint Conference on Neural Networks IJCNN 2021
  [Paper]

• Identification of 27 abnormalities from multi-lead ECG signals: An ensembled SE ResNet framework with Sign Loss function
  Zhaowei Zhu*, Xiang Lan*, Tingting Zhao, Yangming Guo, Pipin Kojodjojo, Zhuoyang Xu, Zhuo Liu, Siqi Liu, Han Wang, Xingzhi Sun, Mengling Feng
  Physiological Measurement PMEA
  [Paper]

• Federated learning: a collaborative effort to achieve better medical imaging models for individual sites that have small labelled datasets
  Dianwen Ng, Xiang Lan, Melissa Min-Szu Yao, Wing P. Chan and Mengling Feng
  Quantitative Imaging in Medicine and Surgery QIMS
  [Paper]

Academic Services

I serve as a reviewer for ICLR, WWW, AAAI, KDD, TNNLS.