News
2025
| Date | News |
|---|---|
| May-2025 | Our paper entitled Boosting Time-series Domain Adaptation via A Time-Frequency Consensus Framework has been accepted. This work introduces a novel consensus-based strategy that integrates time- and frequency-domain representations to enhance robustness in domain adaptation for time-series tasks. |
| Feb-2025 | Our paper entitled Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation has been accepted in IEEE Transactions on Instrumentation and Measurement. This work introduces an evidential learning framework to handle incomplete degradation data during domain adaptation for RUL prediction. |
| Jan-2025 | Our paper entitled EverAdapt: Continuous adaptation for dynamic machine fault diagnosis environments has been accepted in Mechanical Systems and Signal Processing. EverAdapt offers a novel framework for lifelong learning in fault diagnosis, continuously adapting to changes in operating conditions. |
| Jan-2025 | Our paper entitled From Inconsistency to Unity: Benchmarking Deep Learning-Based Unsupervised Domain Adaptation for RUL has been accepted in IEEE Transactions on Automation Science and Engineering. It provides a unified benchmark and protocol for evaluating UDA methods in RUL prediction. |
| Jan-2025 | Our paper entitled Augmented Contrastive Clustering with Uncertainty-Aware Prototyping for Time Series Test Time Adaptation has been accepted at KDD 2025. This method improves test-time adaptation by leveraging contrastive learning and prototype uncertainty for time series. |
2024
| Date | News |
|---|---|
| Oct-2024 | Our paper entitled Overcoming Negative Transfer by Online Selection: Distant Domain Adaptation for Fault Diagnosis has been accepted in IEEE Transactions on Instrumentation and Measurement. It presents a novel online selection strategy to reduce negative transfer in distant domain scenarios. |
| Jul-2024 | Our paper entitled A Virtual-Label-Based Hierarchical Domain Adaptation Method for Time-Series Classification has been accepted in IEEE Transactions on Neural Networks and Learning Systems (TNNLS). The work introduces a hierarchical adaptation method using virtual labels to enhance classification performance. |
| Jun-2024 | Our survey paper Label-Efficient Time Series Representation Learning: A Review has been accepted in IEEE Transactions on Artificial Intelligence. It comprehensively reviews recent advances in SSL and semi-supervised methods for time series analysis. |
| May-2024 | Our paper entitled TSLANet: rethinking transformers for time series representation learning has been accepted at International Conference on Machine Learning (ICML). This work introduces a novel transformer architecture specifically designed for time series representation learning. |
2023
| Date | News |
|---|---|
| Aug-2023 | Our paper entitled Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification has been accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). |
| Jun-2023 | Our paper entitled Contrastive Domain Adaptation for Time-Series via Temporal Mixup has been accepted in IEEE Transactions on Artificial Intelligence (TAI). |
| May-2023 | Our paper entitled Source-Free Domain Adaptation with Temporal Imputation for Time Series Data has been accepted in The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023). |
| Feb-2023 | Our paper entitled AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data has been accepted in ACM Transactions on Knowledge Discovery from Data (TKDD). |
| Feb-2023 | Our paper entitled Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation has been accepted in IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). |
| Jan-2023 | Our paper entitled Diverse and Consistent Multi-view Networks for Semi-supervised Regression has been accepted in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). |
2022
| Date | News |
|---|---|
| July-2022 | Our paper entitled ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training has been accepted in IEEE Transactions on Emerging Topics in Computational Intelligence. |
| June-2022 | Our paper entitled Self-supervised Autoregressive Domain Adaptation for Time Series Data has been accepted in IEEE Transactions on Neural Networks and Learning Systems (TNNLS). |
| June-2022 | Our paper entitled Domain Generalization via Selective Consistency Regularization for Time Series Classification has been accepted in International Conference on Pattern Recognition (ICPR), 2022. |
| May-2022 | Started a joint position as Scientist at both A*STAR Center of Frontiers AI Research (CFAR) and Institute for Infocomm Research (I2R). |
2021
| Date | News |
|---|---|
| Feb-2021 | Our paper entitled Conditional Contrastive Domain Generalization for Fault Diagnosis has been accepted in IEEE Transactions on Instrumentation and Measurement. |
| Jan-2022 | Our paper entitled DiagNet: Machine Fault Diagnosis Using Federated Transfer Learning in Low Data Regimes has been accepted in FL-AAAI 2022. |
| Sep-2021 | Our paper entitled Attention-Based Sequence to Sequence Model for Machine Remaining Useful Life Prediction has been accepted in Neurocomputing, Elsevier. |
| Jun-2021 | Nominated to Participate in the first trilateral Global Fellows Programme “AI and Healthcare”, a partnership between NTU (Singapore), Imperial College London (UK), and TUM (Germany). |
| May-2021 | Our paper entitled Time-Series Representation Learning via Temporal and Contextual Contrasting has been accepted in International Joint Conference on Artificial Intelligence (IJCAI-21). |
| Apr-2021 | Our paper entitled Contrastive Adversarial Knowledge Distillation for Deep Model Compression in Time-Series Regression Tasks has been accepted in Neurocomputing, Elsevier. |
| Jan-2021 | Our paper entitled Robust Domain-free Domain Generalization with Class-aware alignment has been accepted in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). |
2020
| Date | News |
|---|---|
| Oct-2020 | Our paper entitled Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction has been accepted in IEEE Transactions on Industrial Informatics [IF:9.112]. |
| Sep-2020 | Joined ST Engineering Aerospace as a Machine Learning Intern. |
| Sep-2020 | Joined Egypt Scholars Inc as a volunteer member at labs and communities. |
| Sep-2020 | Our paper entitled Secure Transfer Learning for Machine Fault Diagnosis under Different Operating Condition has been accepted in International Conference on Provable and Practical Security (PROVSEC 2020). |
| Jul-2020 | Our paper entitled Adversarial Multiple-Target Domain Adaptation for Fault Classification has been accepted in International Conference on Provable and Practical Security (PROVSEC 2020). |
| Jun-2020 | Our paper entitled Adversarial Transfer Learning for Machine Remaining Useful Life Prediction has won, Finalist Academic Paper Award at IEEE International Conference on Prognostics and Health Management (ICPHM) 2020. |
| Jan-2020 | Successfully passed my PhD Qualifying Exam. |
2018
| Date | News |
|---|---|
| Aug-2018 | Joined as PhD Student in Computer Science and Engineering at Nanyang Technological University |