Deep learning for massive super-resolution imaging & deep learning for the masses
28 Aug, 2019 (Wed)
3:00 pm
Room 603, Chow Yei Ching Building

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Dr. Christophe Zimmer
Unité Imagerie et Modélisation
(Imaging and Modeling Unit)
Département Biologie Cellulaire et Infections
Institut Pasteur


Deep learning is at the heart of the current renaissance of artificial intelligence and holds huge promise for biological research and medicine. In this talk, we will illustrate how deep learning can be leveraged to massively increase the throughput of high resolution microscopy, and will advertise Imjoy, an online platform designed to democratize the deployment of deep learning approaches for biomedical research and beyond.


Biography of the speaker:

C. Zimmer is an interdisciplinary scientist active in the fields of biophysics and computational biology. He started his research track with a PhD in astrophysics on theoretical magnetohydrodynamics in Toulouse (France), followed by a postdoc in space physics at UCLA (USA), where he contributed to the discovery of subsurface oceans on Jupiter’s moons. Driven by a desire to join life science research, he then moved to Institut Pasteur (Paris, France), where he developed image analysis methods for biological microscopy, and contributed to collaborative projects on cell motility and nuclear organization.

In 2008, he started the Imaging and Modeling Unit, an interdisciplinary 12-member team affiliated to the Cell Biology and Infections department and the Center of Bioinformatics, Biostatistics and Integrative Biology. His lab develops experimental and computational imaging and modeling approaches to address major open questions in cell biology, focusing on single molecule based super-resolution microscopy and on chromatin architecture and function. In recent years, the lab started to apply artificial intelligence approaches such as deep learning to the analysis of complex biological and biomedical images.


Dr. K.K.M. Tsia
Co-organizer: IEEE Photonics Society (HK Chapter)

Most seminars are open to the general public, free of charge, unless otherwise stated. Registration is not required. Arrangement for car parking facilities on campus please contact us for details.

For enquiries, please contact:
Department of Electrical and Electronic Engineering,
Room 601, Chow Yei Ching Building,
Pokfulam Road, Hong Kong
Tel: (852) 3917 7093