Practical Deep Learning for Microscopy

“Practical Deep Learning for Microscopy” is the second session in ASCB’s “Connect and Discover: Data Science in Cell Imaging Virtual Meeting Series.” During this session, we will highlight personal stories of cell biologists deciding to use data science to forward their cell biology. Join us to hear from experts as they share their stories where computation was essential to learning new cell biology.

Speakers:  

• Beth Cimini, Broad Institute of MIT and Harvard
• Florian Jug, Fondatione Human Technopole
• Anna Klemm, Uppsala University

Organizers:

• Assaf Zaritsky, Ben-Gurion University of the Negev
• Meghan Driscoll, University of Minnesota

Speaker Bios:

Dr. Beth Cimini is the Associate Director for Bioimage Analysis and a CZI Imaging Scientist in the Imaging Platform at the Broad Institute in Cambridge, MA. She obtained a PhD in Biochemistry and Molecular Biology with Dr. Elizabeth Blackburn at UCSF, studying splicing variants of the telomere master scaffolding protein TIN2. This work honed her interests in image analysis, leading her to postdoctoral and staff scientist roles with Dr. Anne Carpenter’s lab at the Broad, leading a team collaborating with ~30 outside scientists per year on custom image analysis projects. The Cimini lab focuses on bioimage analysis tool creation (Piximi) and maintenance (CellProfiler), as well as on applying open source tools to novel biological problems.  She created and directs the Platform’s Postdoctoral Training Program in Bioimage Analysis, and also leads the Broad efforts on community engagement and technology development for the Center for Open Bioimage Analysis (COBA).

Dr. Florian Jug holds a PhD in Computational Neuroscience from the Institute of Theoretical Computer Science at ETH Zurich. His research aims at pushing the boundary of what AI and machine learning can do to better analyze and quantify biological data. At HT, Dr. Jug covers the full breadth of bio-image computing, from research on novel methods for computer vision and machine learning, all the way to offering bio-image analysis as a service.

Florian is a strong proponent of open access science, open AI and ML methods, and open-source software. His team is part of AI4Life and was for many years a core contributor to  Fiji (~100,000 active users). He is also involved in the collaboratively developments of open methods such as CARE, Noise2Void, PN2V, DivNoising, and others. He organizes scientific conferences (e.g the I2K conference), workshops (e.g. the BIC workshops at top-tier computer vision conferences) and various practical courses on machine learning for bio-image analysis (e.g. DL@MBL in Woods Hole) or microscopy (e.g. Quantitative Imaging at Cold Spring Harbor).

Anna Klemm heads the BioImage Informatics Unit, SciLifeLab – a Swedish national unit providing expert support on bioimage analysis to researchers in Sweden. She received her PhD degree in cellular Biophysics at the University Erlangen-Nürnberg, Germany in 2010. She then pursued her postdoctoral work at the Max-Planck-Institute for Cell Biology and Genetic in Dresden, Germany, where she studied mitotic chromosome movements using microscopy and image analysis. From 2015-2018, Anna worked as a microscopist and bioimage analyst at the Core Facility BioImaging at the Biomedical Center in Munich, Germany. Since March 2018, she has been working at the BioImage Informatics Facility of SciLifeLab, Sweden.

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