Publication Highlights


LEAD overview
LEAD: An EEG Foundation Model for Alzheimer’s Disease Detection
(TMLR)

Keywords: EEG, foundation model, Alzheimer’s disease, contrastive pre-training, subject-level detection

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Contrast Everything:
A Hierarchical Contrastive Framework for Medical Time-Series
(NeurIPS 2023)

Keywords: contrastive learning, medical time series, self-supervised

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Population-scale identification of differential adverse events before and during a pandemic
(Nature Computational Science)

Keywords: pandemic, drug side effects, health inequity, demographics, FDA, FAERS

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MindID: Person Identification from Brain Waves through Attention-based Recurrent Neural Network (Ubicomp 2018)

Keywords: EEG, brain-computer interface, non-invasive, person identification, attention mechanism

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News

2026
  • Our paper “What Causes Performance Degradation in Cross-Subject EEG Classification?” received the Best Paper Award at the Brain-Machine Interface Workshop, IEEE SMC 2026.
  • Thrilled to receive the James H. Woodward Faculty Research Award (2025–2026)!
  • LEAD, an EEG foundation model for Alzheimer’s disease detection, published in Transactions on Machine Learning Research (TMLR).
  • FORMED, repurposing backbone foundation models for domain-specific medical time series analysis, accepted at ICLR 2026.
  • Two papers accepted at ACM UbiComp 2026.
  • Paper accepted at IEEE PerCom 2026.
2025
  • Paper accepted at ICML 2025.
  • Paper accepted at IEEE MultiMedia.
  • Paper accepted at IEEE Transactions on Mobile Computing.
2024
  • Medformer, a new Transformer architecture for multivariate medical time series, accepted at NeurIPS 2024.
  • Paper on spatiotemporal heterogeneous learning for time series accepted at ACM Multimedia 2024.
2023
  • Paper on self-supervised contrastive learning for medical time series accepted at NeurIPS 2023.
  • Delivered a keynote at the Brain-Machine Interface Workshop, IEEE SMC 2023; served as session chair and jury for the IEEE Brain Best Paper Award.
  • Appointed director of CharMLab at UNC Charlotte (6 faculty, 18 PhD students, 15 MS/UG/K-12 students).
  • Served as Area Chair for AISTATS 2023.
  • Served as Publicity and Social Media Co-Chair for PerCom 2023.
2022
  • Paper on self-supervised time series transfer learning accepted at NeurIPS 2022.
  • Paper on irregular time series accepted at ICLR 2022.
  • Paper on population-scale drug safety accepted at Nature Computational Science.
Earlier news (2017–2021)
2021
  • Paper accepted at ACM UbiComp 2021.
  • Survey on deep learning for brain-computer interfaces accepted at Journal of Neural Engineering.
  • Invited as guest editor for the special issue “AI-Powered Smart Healthcare in Smart Cities” at Frontiers in Sustainable Cities.
2020
  • GNNGuard accepted at NeurIPS 2020.
  • Paper on EEG- and gait-based user authentication accepted at ACM Transactions on Intelligent Systems and Technology.
  • Paper on neurological diagnosis accepted at IEEE Journal of Biomedical and Health Informatics.
  • Joined ZitnikLab at Harvard Medical School as a Postdoctoral Fellow.
  • Featured in UNSW Alumni Profile.
2019
  • Paper accepted at KDD 2019 Research Track.
  • Paper accepted at ICDM 2019 as a full paper (acceptance rate: 9%).
  • Two papers accepted at ICONIP 2019.
  • Awarded the Engineering PhD Summit fellowship, EPFL 2019 (11 recipients worldwide).
  • Received KDD 2019 Student Travel Grant.
2018
  • Received the Google PhD Fellowship 2018 (one of four recipients in Australia).
  • Paper on EEG-based person identification accepted at UbiComp 2018.
  • Paper on multi-modality sensor data classification accepted at IJCAI 2018.
  • Paper on EEG-based brain typing accepted at PerCom 2018.
2017
  • Paper on Brain-Computer Interface accepted at Mobiquitous 2017.
  • Paper on smart living accepted at ICONIP 2017.