News

[Jan-2024] Received the Competitive Career Development Fund (CDF) from A*STAR for the project titled Label-Efficient and Resilient Federated Learning Approach for Time Series Applications

[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).

[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)

[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 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).

[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

[Aug-2018] Joined as PhD Student in Computer Science and Engineering at Nanyang Technological University