Yi-Ping Phoebe Chen
Also known as: Phoebe Chen
La Trobe University
Research areas: Biochemistry, Genetics and Molecular Biology · Molecular Biology · Genomics and Phylogenetic Studies · Bioinformatics and Genomic Networks · Machine Learning in Bioinformatics
0000-0002-4122-3767
About
Prof Yi-Ping Phoebe Chen is Professor and Chair at the Department of Computer Science and Information Technology, La Trobe University, Melbourne Australia since April 2010. She was Head of Department of Department of Computer Science and Computer Engineering, La Trobe University from 2010 to 2012. Phoebe received her BInfTech degree with First Class Honours and PhD in Computer Science from the University of Queensland in Dec 2000. Phoebe has been awarded 30 research grants around 8 million (include 13 prestigious Australia Research Council (ARC) Grants) so far. Prof Chen is the Chief Investigator of ARC Centre of Excellence in Bioinformatics. Before she joined La Trobe, Phoebe was Associate Professor (Reader) in Deakin University from Dec 2003 to April 2010. She worked as an Associate Lecturer/Lecturer/Senior Lecturer in Queensland University of Technology from Jul 1999 to Nov 2003. Phoebe is a member of Excellence in Research for Australia 2018 (ERA2018) Research Evaluation Committees (REC) of the ARC, member of an NHMRC Grant Review Panel (GRP) 2019 & 2013-2014, and Project Grant Assigners Academy. Professor Chen has been doing multi-discipline research for more than 20 years. Her research focus is to find effective solutions for visualizing, integrating, analyzing and mining big data, complex structures and functions for scientific and biomedical applications. She has been working in many emerging areas such as bioinformatics, multimedia, artificial intelligence, scientific visualization, pattern recognition, health informatics, deep learning, data mining, and databases. Her current Research includes Knowledge Discovery for RNA Structure and Function, Deep Learning Approach and its Applications, Visual and Data Analysis in Disease Diagnosis, Medical Image Analysis with Pattern Recognition, Drug Design by Visualization and Machine Learning Approach, Mining Protein and Genome Regulatory Networks using Graphic Models. She has recently been appointed to the ARC College of Experts.
Phoebe has published over 300 research papers, many of them appeared in top journals and conferences such as IEEE Transactions on Neural Networks and Learning Systems, Nature Machine Intelligence, Artificial Intelligence, Bioinformatics, IEEE Transactions on Biomedical Engineering, Pattern Recognition, Molecular Systems Biology, IEEE Transactions on Industrial Informatics, IEEE Transactions on Multimedia, Aging Cell, Nucleic Acids Research, BMC Genomics, Current Drug Metabolism, Journal of Medical Genetics, RNA, IEEE Transactions on Knowledge and Data Engineering, Information Systems, CVPR, AAAI, ACL, SIGMOD, ACM MM etc. . Phoebe is/has been associate editor for IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Multimedia, Editor-in-Chief Current Bioinformatics. Phoebe is vice chair of ACM SIGMM, steering committee chair of Asia-Pacific Bioinformatics Conference (founder) and international conference on Multimedia Modelling. She has been on the program committee’s chairs and member of over 100 international conferences, including top ranking conferences such as AAAI, ACM MM, ICDE, ICPR, ISMB, CIKM etc.
Employment
Education
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Publications (569)
- ADXpertNet: Deep Learning Approach for Capturing Local and Global Spatial Relationship Between FTIR Spectra and Component Data of Milk for Adulterant Detection Save
- Beyond Robustness: Uncovering Blind Spots in Federated Learning Defenses Save
- A Novel Crude Oil Price Combination Link Forecasting Method based on the MF-VMD-CDVGNets-SLRNN Model Save
- Seeing Further and Wider: Joint Spatio-Temporal Enlargement for Micro-Video Popularity Prediction Save
- VICAL: Vicinal Consistency Alignment for Long-Tailed Visual Recognition Save
- Dual Attention Multi-Instance Learning for Identifying Autism Spectrum Disorder Using Resting-State fMRI Save
- Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review Save
- Spikes as perturbations of resonant neural circuits: an RLC framework with testable predictions Save
- EvoCap: Enhancing video captioning via self-evolving video-LLMs with knowledge consolidation Save
- Optimizing Query-by-Example Spoken Term Detection with Audio-to-Token Sequence Clustering and Query-Guided Retrieval Save
- GateMOT: Q-Gated Attention for Dense Object Tracking Save
- Seeing Further and Wider: Joint Spatio-Temporal Enlargement for Micro-Video Popularity Prediction Save
- TSC-Nodule: a tied non-local and spatial-channel reconstructed faster R-CNN for pulmonary nodule detection Save
- MF-PEAR-net: a multi-scale feature guided project-&-excite affine registration network for CT images Save
- Deep Imputation Bi-Stochastic Graph Regularized Matrix Factorization for Clustering Single-Cell RNA-Sequencing Data Save
- Guest Editorial for the 21th Asia Pacific Bioinformatics Conference Save
- Spectrally Distilled Representations Aligned with Instruction-Augmented LLMs for Satellite Imagery Save
- DeDiff-4DGS: Fusing Temporal Correlations and Diffusion Priors for Dynamic 3D Scenes Save
- MULGONET: An interpretable neural network framework to integrate multi-omics data for cancer recurrence prediction and biomarker discovery Save
- Scalable User Admission Control in Large-Scale Cell-Free Massive MIMO Save