David Richmond

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Research Interests

I'm interested in the process of self-organization that is evident across all scales in biology, from the internal organization of cells, to the coordinated activity across cells and tissues in development and regeneration.  Microscopy is ideally suited to address these questions, with the capability to probe biological systems across all relevant length scales, and across time.  As microscopy techniques continue to improve, the data sets produced are increasingly large and rich.  We now need advanced computer vision techniques to extract this information in order to address some of the toughest questions in biology.  I work at the interface of these two approaches: developing image processing algorithms to analyze biological data sets, and in turn optimizing microscopy to yield the most information rich data sets for automated analysis.

Techniques that I'm particularly interested in include: machine learning (eg. cascaded random forests, neural networks with deep architectures), statistical models of shape and appearance, graphical models, probabilistic inference, and selective plane illumination microscopy.

Current Projects + Collaborators

Education

University of California, Berkeley (2005-2011)
Ph.D. in Biophysics
Advisor: Prof. Dan Fletcher

University of Victoria (1999-2005)
B.Sc. in Physics (Honours), Minor in Mathematics
Research internships at University of Toronto, Canadian Institute of Theoretical Astrophysics, University of Victoria, Calgary Foothills Hospital

Work Experience

Max Planck Institute of Molecular Cell Biology and Genetics (2013-present)
Postdoctoral Fellow
Advisor: Prof. Gene Myers
Developing advanced machine learning algorithms for the analysis of biological images.

Max Planck Institute of Molecular Cell Biology and Genetics (2011-2012)
Postdoctoral Fellow
Advisor: Prof. Andrew Oates
Studied development of the body plan in zebrafish using transgenic reporters, quantitative microscopy, image analysis, and numerical simulations.

Genentech (2010)
Research Intern
Advisor: Dr. Ryan Watts
Established a live imaging and analysis pipeline for measuring defects in development of the blood-brain barrier in mutant zebrafish.

University of California, Berkeley (2005-2011)
Graduate Student Researcher
Advisor: Prof. Dan Fletcher
Discovered membrane-induced bundling of cytoskeletal filaments. Developed a microfluidic device for making lipid vesicles with controlled contents and membrane properties, a key step in liposomal drug delivery strategies.

Technical Skills

Programming: C++, MATLAB, Python, VIGRA, OpenGM, Caffe
Software: FIJI, Imaris, ilastik, Amira, Metamorph, Micro-Manager
Image Analysis: Machine learning (random forests, convolutional neural networks), graphical models, active appearance models, particle tracking
Microscopy: Microscope assembly and automation, fluorescence microscopy (spinning disk confocal, LSM, TIRF, SPIM, single molecule imaging), high speed imaging, spectrophotometry
Biochemistry: DNA plasmid prep, RNA synthesis, in situ hybridization, immunostaining, protein expression and purification, fluorescent labelling, lipid vesicle preparation

Teaching

Technical University of Dresden (2014)
Guest Lecturer - Discrete Algorithms for Computational Biology
Presented lectures on Expectation-Maximization and Hidden Markov Models for motif discovery in nucleotide and amino acid sequences.

University of California, Berkeley (2010)
Graduate Student Instructor - Optics & Microscopy
Presented two lectures, and led discussion and review sections for class of 50 students.

Marine Biological Laboratory, Woods Hole (2009)
Graduate Student Instructor - Physiology Course
Designed two research projects and supervised a multi-disciplinary team in the acquisition, analysis and interpretation of data.

Awards

European Molecular Biology Organization Long Term Fellowship (2012-2013)
Alan Bearden Award for Outstanding Dissertation Research in Biophysics at UC Berkeley (2011)
1st Place, UC Berkeley Synthetic Biology White Paper Competition (2008)
NSERC Postgraduate Research Scholarship - Doctoral (2007-2010)
Julie Payette NSERC Postgraduate Research Scholarship - Masters (2006)
3 NSERC Undergraduate Student Research Awards (2003-2004)
12 undergraduate scholarships, including UVic President’s Scholarship and UVic Faculty Scholarship (1999-2005)

Publications

  • Uncertainty-driven forest predictors for vertebra localization and segmentation

    Richmond DL*, Kainmueller D*, Glocker B, Rother C, Myers EW (* equal contribution)

    International Conference on Medical Image Computing and Computer Assisted Interventions, accepted

  • Reconstitution of proteins on electroformed giant unilamellar vesicles

    Schmid EM, Richmond DL, Fletcher DA

    Methods in Cell Biology, 2015.

  • A Doppler effect in embryonic pattern formation

    Soroldoni D, Joerg DJ, Morelli LG, Richmond DL, Schindelin J, Julicher F, Oates AC

    Science, 2014

  • The segmentation clock: inherited trait or universal design principle?

    Richmond DL, Oates AC

    Current Opinion in Genetics and Development, 2012

  • Death receptors DR6 and TROY regulate brain vascular development

    Tam SJ, Richmond DL, Kaminker J, Modrusan Z, Martin-McNulty B, Cao T, Tessier-Lavigne M, Watts RJ

    Developmental Cell, 2012

  • Forming giant vesicles with controlled membrane composition, asymmetry and contents

    Richmond DL*, Schmid EM, Martens S, Stachowiak JC, Liska N, Fletcher DA (*equal contribution)

    Proceedings of the National Academy of Sciences, 2011

  • Inkjet formation of unilamellar vesicles for cell-like encapsulation

    Stachowiak JC, Richmond DL, Li TH, Brochard-Wyart F, Fletcher DA

    Lab on a Chip, 2009

  • Membrane-induced bundling of actin filaments

    Liu AP*, Richmond DL*, Maibaum L, Pronk S, Geissler PL, Fletcher DA (*equal contribution)

    Nature Physics, 2009

  • Unilamellar vesicle formation and encapsulation by microfluidic jetting

    Stachowiak JC, Richmond DL, Li TH, Liu AP, Parekh SH, Fletcher DA

    Proceedings of the National Academy of Sciences, 2008

  • Stratified tidal flow over a bump

    Dewey R, Richmond D, Garrett C

    Journal of Physical Oceanography, 2005

Patents

Richmond DL, Stachowiak JC, Li TH, Parekh S, Liu AP, Schmid E, Fletcher DA. “Forming an artificial cell with controlled membrane composition, asymmetry, and contents." Pending.

Selected Conference Presentations

Cascaded random forest classifiers for somite localization and identification in zebrafish. BioImage Informatics, Leuven, BE (2014).

Cascaded random forest classifiers for somite localization and identification in zebrafish. Medical Imaging Summer School, Favignana, IT (2014).

Forming vesicles with cellular features: new tools for cellular reconstitution. ESF-EMBO Symposium – Emergent Properties of the Cytoskeleton, Sant Feliu de Guixols, ES (2010).

Engineering vesicles with complex cellular functions. NIH NanoMedicine Development Center National Meeting, Pacific Grove, USA (2010).

Engineering vesicle membranes for cellular reconstitution. Biophysical Society Annual Meeting, San Francisco, USA (2010).

Encapsulation technology for constructing synthetic cell-like devices. NIH NanoMedicine Development Center National Meeting, Bethesda, USA (2009).

Tools for constructing synthetic cell-like devices. UC Berkeley Synthetic Biology Institute - Planning Meeting, Berkeley, USA (2009).