Liangli Zhen

Senior Scientist at A*STAR

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Welcome to my homepage! I am a group leader and senior scientist at the Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore. I lead the AI Safety research group focused on enhancing the safety and robustness of AI systems for real-world deployment and use. Prior to joining IHPC, I received my PhD in Computer Science from Sichuan University, supervised by Professor Dezhong Peng. I was a joint PhD student at the University of Birmingham in the UK, supervised by Professor Xin Yao (IEEE Frank Rosenblatt Award Recipient).

My research is mainly on machine learning and optimisation. Related research topics include multimodal learning, adversarial robustness, domain generalisation, foundation models, evolutionary multi-objective optimisation, and more.

News

  • [Aug 2024] Our project on Cyber Sentinel: A Unified Framework for Safeguarding Foundation Models has been awarded the CyberSG Research and Development Programme Office (CRPO) Grand Challenge Funding.
  • [Aug 2024] We are currently offering open positions for visiting PhD students and internships in Reliable AI research.
  • [Aug 2024] Our paper on Continuous Disentangled Joint Space Learning for Domain Generalization has been accepted for publication by the IEEE Transactions on Neural Networks and Learning Systems.
  • [May 2024] Our team won the 1st Prize in the IJCAI Vision-based Remote Physiological Signal Sensing Challenge.
  • [Apr 2024] Our paper on Neural Architecture Search with Progressive Evaluation and Sub-Population Preservation has been accepted for publication by the IEEE Transactions on Evolutionary Computation.
  • [Mar 2024] Our paper on Generative Image Reconstruction from Gradients has been accepted by the IEEE Transactions on Neural Networks and Learning Systems.
  • [Jan 2024] Our paper on Geometric Correspondence-Based Multimodal Learning for Ophthalmic Image Analysis has been accepted for publication by the IEEE Transactions on Medical Imaging.
  • [Jan 2024] Our paper on MedNAS: Multi-scale Training-free Neural Architecture Search for Medical Image Analysis has been accepted for publication by the IEEE Transactions on Evolutionary Computation.
  • [Nov 2023] Our paper on Deep Supervised Multi-View Learning with Graph Priors has been accepted for publication by the IEEE Transactions on Image Processing.
  • [Nov 2023] Our paper on Evolutionary Architecture Search for Generative Adversarial Networks Based on Weight Sharing has been accepted for publication by the IEEE Transactions on Evolutionary Computation.
  • [Jul 2023] Our project on Development of Stable, Robust and Secure Intelligent Systems for Autonomous Vehicles has been awarded the AI Singapore Robust AI Grand Challenge Funding.
  • [Jul 2023] Our paper on Generative Gradient Inversion via Over-parameterized Convolutional Networks in Federated Learning has been accepted for publication by ICCV-2023.