Gabrielle J. Gutierrez, PhD
Education and Training
Barnard College, Columbia University, graduated in 2006
Bachelor of Arts, Physics major, Applied Mathematics minor
Brandeis University, Neuroscience PhD program
September 2006 – August 2012
PhD in Neuroscience
Advisor: Eve Marder; Thesis: Dynamics of multi‐functional, pattern‐generating, neuronal networks
Ecole Normale Superieure, Group for Neural Theory
April 2013 – September 2015
Postdoctoral researcher; Advisor: Sophie Deneve
Janelia Research Campus, Shaul Druckmann
October 2015 – March 2016
Visiting researcher
University of Washington, Applied Math department
April 2016 – present
Postdoctoral research associate; Advisors: Eric Shea-Brown and Fred Rieke
Additional Training
Grow with Google Udacity scholarship, Android Basics Nanodegree
April 24, 2018 – October 24, 2018
Methods in Computational Neuroscience, Woods Hole, MA
July 30, 2014 – August 27, 2014
Computational and Cognitive Neuroscience course, Shanghai, China
July 5, 2014 – July 23, 2014
Research and Teaching Experience
University of Washington, Seattle, WA
April 2016 – present
Postdoctoral researcher and UWIN fellow in the Applied Math dept. Advisors: Eric Shea-Brown and Fred Rieke. Topic: Contribution of local neuron properties to global network computation.
Janelia Research Campus, Ashburn, VA
October 2015 – March 2016
Visiting postdoctoral researcher. Advisor: Shaul Druckmann. Topic: Interplay between recurrent connectivity and intrinsic neuron properties in a predictive coding model.
École Normale Supérieure, Paris, France
April 2013 – September 2015
Postdoctoral researcher in Group for Neural Theory, Advisor: Sophie Denève. Topic: Adaptation and population coding in a predictive coding model.
Brandeis University, Waltham, MA
August 2012 – April 2013
Postdoctoral researcher in Eve Marder’s lab. Continued work on computational modeling of neural circuits and neuromodulation.
Brandeis University, Waltham, MA
September 2006 – August 2012
Research trainee and IGERT fellow, Advisor: Eve Marder. Performed electrophysiology experiments and did computational modeling work. Studies focused on neural circuits and neuromodulation.
Brandeis University, Waltham, MA
Fall 2007 & Spring 2008
Teaching Assistant for BioLab and Neuropharmacology courses: Graded homework and exams and held regular study sessions and office hours.
Barnard College, New York, NY
Spring 2006
Teaching Assistant for Physics Department: Taught Electricity and Magnetism Laboratory. Responsibilities included lab set-up, lecturing, and grading.
New York University, New York, NY
Summer 2005
SURP Research Experience for Undergraduates, IGERT research fellow: Studied visual preference in Nava Rubin’s psychophysics lab.
City College of New York, New York, NY
Summer 2004
Summer Research with Professor Jay Edelman: Studied vision in human subjects. Designed and coded programs using MATLAB and EYEtracker. Analyzed data and presented findings to fellow student researchers and professors.
Honors and Awards
Research Exchange Fellow, California Alliance, 2019
BRAINS NIH Fellow, 2019
NIH Career Transition/Pathway to Independence K Award, 2018
Perfect Pitch Competition, 1st place UWIN division, 2016
CMU Modeling Neural Activity conference, travel award, 2016
WRF Innovation Postdoctoral Fellowship in Neuroengineering, UWIN, 2016
Allison Doupe Fellowship to attend McKnight Endowment Fund Conference, 2016
Barnard Alumnae Association Fellowship for Graduate Studies, 2010
Bernstein Conference on Computational Neuroscience Travel Fellowship, 2009 and 2011
BOLLI Teaching Fellowship, Brandeis University, 2008
IGERT Training Fellowship, 2006
SURP Research Experience for Undergraduates, 2005
Barnard College Leadership Award, 2005
GE Fellowship for minority students in science, 2005
Irene Diamond Scholarship, 2004
Charles Dana Undergraduate Scholarship, 2004
Dulcida Romerco Chicon Scholarship, 2003
Work Experience
American Museum of Natural History, New York, NY
November 2003 – August 2006
Astrophysics Education Coordinator (part-time): Developed and taught astrophysics programs aimed at children and teachers. Managed the Saltz High School Internship Program, including training, supervision, and design of activities. Oversaw the maintenance of the Saltz Carts: moveable exhibitions with interactive, educational activities.
American Museum of Natural History, New York, NY
November 2002 – November 2003
Space Show Presenter and Educator (part-time): Operated the space show in the Hayden Planetarium. Programmed space shows and performed live sky presentations using the Zeiss star projector. Presented and performed in the “Kid’s show”: an interactive, live, educational show in the Hayden Planetarium. Assisted in teaching and developing astronomy programs for children.
Henry Street Settlement, New York, NY
September 2002 –January 2003
After school teacher (part-time): Developed and provided fun and enriching after-school activities for a group of 25 third and fourth graders. Assisted this group with homework for 1 hour every day.
Public Outreach and Service
Guest speaker for YSP-REACH program, University of Washington. Summer 2019.
Computational neuroscience journal club leader, University of Washington. Academic year 2018-2019.
Guest speaker at Girls Who Code, Seattle, WA. Multiple sessions every summer since 2016.
Panelist at Emerald City Comic Con’s “Science doesn’t work that way, goodnight!” event. March 2019.
Abstract reviewer of submissions for Cosyne conference 2018-2020.
Skype a Scientist participant. Summer 2018.
Guest speaker, Darwin Day at the Burke Museum, Seattle, WA. 18 February 2018.
Chair, Computational Neuroscience Social, Society for Neuroscience conference, 2017.
Co-chair, Computational Neuroscience Social, Society for Neuroscience conference, 2016.
Volunteer, UW Bioscience experience program for underrepresented minority students. 21 July, 2016.
Guest science speaker at Heritage High School, Leesburg, VA. 11 February, 2016.
Women in Science club co-organizer at Brandeis University, 2012.
Barnard Alumnae Admissions Representative (BAAR) since 2010.
Invited Talks
Northwestern University, Neurobiology Department seminar, January 19th, 2021.
Harris-Stowe State University, Department of Life Sciences seminar, November 30th, 2020.
Yale University, Emonet group seminar, November 23rd 2020.
Oberlin College, Neuroscience Department Seminar, November 20th, 2020.
Stanford University, Computational Neuroscience Journal Club, October 28th, 2020.
Columbia University, Psychology Department Seminar, October 19th, 2020.
Johns Hopkins University, Neuroscience Department Seminar, October 8th, 2020.
UW Applied Math 50th Conference 2019, Seattle, WA. Neural and Neuronal Networks mini-symposium.
Neural Computation and Engineering Connection 2018, Seattle, WA.
Cosyne 2015, Salt Lake City, UT. “Cortical Circuits in Action” Workshop.
Primary Publications
Gutierrez GJ, Rieke FR, Shea-Brown ET (2021). Nonlinear convergence boosts information coding in circuits with parallel outputs. PNAS, 118(8).
Review Articles
Conference Abstracts
Gutierrez GJ, Rieke FM, Shea-Brown ET (2018) Info in a bottleneck: The compression of information in neural circuits. San Diego, CA: Society for Neuroscience 2018.
Gutierrez GJ, Shea-Brown E, Rieke F (2018) Info in a bottleneck: exploring the compression of visual information in the retina. Seattle, WA: Organization for Computational Neuroscience 2018. *talk
Gutierrez GJ and Deneve S (2016) Spike-frequency adaptation optimizes the tradeoff between efficiency and accuracy in a predictive coding model. Waikoloa, HI: Modeling of Neural Activity conference hosted by Carnegie Mellon.
Gutierrez GJ and Deneve S (2015) Spike-frequency adaptation optimizes the tradeoff between efficiency and accuracy in a predictive coding model. Chicago, IL: Society for Neuroscience 2015. *talk
Gutierrez GJ and Deneve S (2015) Spike-frequency adaptation optimizes the tradeoff between efficiency and accuracy in a predictive coding model. Bilbao, Spain: Neural coding, computation, and dynamics conference 2015.
Gutierrez GJ and Deneve S (2015) Adaptation and homeostasis in a spiking predictive coding network. Salt Lake City, UT: Cosyne 2015.
Gutierrez G and Marder E (2013) The rectification of an electrical synapse can change the functional output of a pattern-generating circuit. Paris, France: CNS, Organization for Computational Neuroscience 2013.
Gutierrez G and Marder E (2012) An electrically coupled and synaptically inhibited neuron switches between competing oscillator sub-networks via multiple mechanisms. New Orleans, LA: Society for Neuroscience 2012.
Gutierrez G, Goeritz M, Marder E (2011) Signal propagation in a small neural network: the contribution of inhibitory synapses and electrical gap junctions to signal propagation properties of a central pattern generator. San Diego, CA: Society for Neuroscience 2011.
Gutierrez G and Marder E (2011) Signal propagation in a small neural network. Freiburg, Germany: Bernstein Conference for Computational Neuroscience 2011.
Gutierrez G, Abbott LF, Marder E (2009) Are biological neural networks capable of acting as computing reservoirs? Frankfurt, Germany: Bernstein Conference for Computational Neuroscience 2009.
Gutierrez GJ, Abbott LF, Marder E (2009) Can a biological neural network act as a dynamic reservoir? Chicago, IL: Society for Neuroscience 2009.
Extracurricular
Member of the board of directors of the Young Patrons Circle of Pacific Northwest Ballet, 2017-2019; Data Analytics committee and Executive committee (Secretary).
“Grow with Google” Udacity scholarship, Android Basics Nanodegree program, 2018.
Art Neureau contributor, 2018.
Gabrielle J Gutierrez 