Liangli Zhen

Group Manager & Senior Scientist at A*STAR

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Welcome to my homepage! I am a group manager and senior scientist at the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. I lead the Reliable AI research group to improve AI safety and robustness. Prior to joining IHPC, I received my PhD in Computer Science from Sichuan University in 2018, supervised by Professor Dezhong Peng. I was a joint PhD student at the University of Birmingham from Aug 2016 to Aug 2018, supervised by Professor Xin Yao.

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

news

  • [Nov 2023] We are currently offering open positions for visiting PhD students and internships in Reliable AI research.
  • [Nov 2023] Our paper on Deep Supervised Multi-View Learning with Graph Priors has been accepted by the IEEE Trans. on Image Processing.
  • [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 is accepted by ICCV-2023.
  • [Jan 2023] Our paper on Contrastive Domain Adaptation With Consistency Match for Automated Pneumonia Diagnosis has been published in Medical Image Analysis.
  • [Jul 2022] Our paper on Adversarial Multimodal Fusion with Attention Mechanism for Skin Lesion Classification Using Clinical and Dermoscopic Images is accepted by Medical Image Analysis.
  • [Mar 2022] Our project on RAPIER – Radiology Pathology Information Exchange Resource has been awarded the AI Singapore Technology Challenge Funding.
  • [Feb 2022] Our paper on Deep Multimodal Transfer Learning for Cross-Modal Retrieval is published in the IEEE Trans. on Neural Networks and Learning Systems.
  • [Jan 2022] Our paper on Efficient Sharpness-Aware Minimization for Improved Training of Neural Networks is accepted by ICLR-2022.
  • [Aug 2021] Our paper on Evolutionary Multi-Objective Model Compression for Deep Neural Networks is published in the IEEE Computational Intelligence Magazine.
  • [Apr 2021] Our paper on Video Corpus Moment Retrieval with Contrastive Learning is accepted by SIGIR-2021.
  • [Apr 2021] Our paper on Learning Cross-modal Retrieval with Noisy Labels is accepted by CVPR-2021.
  • [Apr 2021] Our paper on Natural Language Video Localization: A Revisit in Span-based Question Answering Framework is accepted by the IEEE Trans. on Pattern Analysis and Machine Intelligence.
  • [Feb 2021] Our project on MARIO: Multimodal AI-Driven Decision Making for Ophthalmology has been awarded the Singapore RIE2020 Advanced Manufacturing and Engineering (AME) Programmatic Grant.