Important event advisory (10/12/2020)
In light of the continuing Covid-19 pandemic, we have decided to make this event virtual for everyone around the world. Please refer to this page for the most up-to-date information about the event.
This event is focused on artificial intelligence-guided techniques for microscopy. Join us on Monday, March 9th for a symposium on AI applications in microscopy. In the afternoon, you can get hands-on experience with open-source and commercial AI tools like the Allen Cell Segmenter and Aivia.
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Supported by
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Hosted by
Guest speakers
The symposium focuses on recent developments in machine learning and deep learning tools for microscopy. Researchers from all backgrounds who are interested in AI microscopy are encouraged to attend. The speakers for this symposium are as follows:
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Phuc "Sam" Nguyen
Graduate Student, Kueh lab
University of Washington
Susanne Rafelski
Director of Assay Development
Allen Institute of Cell Science
Luciano Lucas
Executive Vice President
Aivia
Theo Knijnenburg
Director of Modeling
Allen Institute of Cell Science
Wan-Qing Yu
Postdoctoral Fellow, Wong lab
University of Washington
Julien Dubrulle
Staff Scientist
Fred Hutch
Schedule and agenda
Date to be announced
Fred Hutch Cancer Research Center, Location TBD
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9:20 - 9:30 am
9:30 - 10:15 am
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10:15 - 10:30 am
10:30 - 11:15 am
11:15 - 12:00 noon
12:00 - 1:00 pm
1:00 - 1:45 pm
1:45 - 2:00 pm
2:00 - 2:45 pm
2:45 - 3:30 pm
3:30 - 3:45 pm
3:45 - 5:00 pm
Introductions
Sam Nguyen, "Deep learning based morphological profiling for cell state transition analysis in unmanipulated cells."
Q&A and coffee break
Susanne Rafelski, "An iterative deep learning approach for image-based quantification of stem cell structures."
Luciano Lucas, "Deep learning for image restoration: how to minimize the intrinsic limitation of light microscopy."
Lunch break
Theo Knijnenburg, "Machine learning based integrated cell models and label free imaging."
Q&A and coffee break
Wan-Qing Yu, "AI-aided neural circuit reconstruction in mouse retina."
Julien Dubrulle, "Image analysis services at Fred Hutch."
Q&A and coffee
Demonstrations of image analysis tools available from Aivia, Allen Institute, and Fred Hutch Shared Resources Imaging Facility
Registration
For more information and to register for the event, please complete the form below. ​
Monday, March 9, 2020
Fred Hutch Cancer Research Center, Weintraub Building, Pelton Auditorium Room B1-065
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9:20 - 9:30 am
Introductions
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9:30 - 10:15 am
Sam Nguyen, "Deep learning based morphological profiling of cell state transition analysis in unmanipulated cells."
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10:15 -10:30 am
Q&A and coffee break
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10:30 - 11:15 am
Susanne Rafelski, "An iterative deep learning approach for image-based quantification of stem cell structures."
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11:15 - 12:00 noon
Luciano Lucas, "Deep learning for image restoration: how to minimize the intrinsic limitation of light microscopy."
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12:00 - 1:00 pm
Lunch break
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1:00 - 1:45 pm
Theo Knijnenburg, "Machine learning based integrated cell modes and label free imaging."
1:45 - 2:00 pm
Q&A and coffee break
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2:00 - 2:45 pm
Wan-Qing Yu, "AI-aided neural circuit reconstruction in mouse retina."
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2:45 - 3:30 pm
Julien Dubrulle, "Image analysis services at Fred Hutch."
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3:30 - 3:45 pm
Q&A and coffee break
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3:45 - 5:00 pm
Demonstrations of image analysis tools available from Aivia, Allen Institute, and Fred Hutch Shared Resources Imaging Facility