David Richmond

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

• Segmentation and tracking of somite development in zebrafish (joint with Carsten Rother, TUD, and the Oates Lab, UCL)
• Segmentation and tracking of cell clones during limb regeneration in Brainbow Axolotl (joint with Tanaka Lab, CRTD)

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

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).