Curriculum Vitae

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Biography

I am interested in the intersection between biology, cognition, and machine learning. My research topics have ranged from purely computational, such as generative modeling and machine perception, to purely biological, such as field ethology with chimpanzees and multiunit extracellular neurophysiology with songbirds, however my primary interest sits somewhere in between, studying computational neuroscience and biologically/cognitively motivated machine learning algorithms.

Research Interests

Sequence models, Generative models, Machine perception, Auditory neuroscience, Language origins, Language development, Deep Learning/NLP, Animal cognition/communication

Education

2015–now
University of California, San Diego, CA
Ph.D. in Behavioral Neuroscience with a Specialization in Anthropogeny
Auditory Neuroscience Laboratory
Advisor: Timothy Q. Gentner
2010–2014
The Pennsylvania State University, State College, PA
B.A. in Psychology with a Minor in Biology

Research Positions

2015–now
PhD Student, Auditory Neurscience Laboratory
University of California, San Diego, La Jolla, CA
Advisor: Timothy Q Gentner
2016–2017
Student Contractor, Machine learning and Artificial Perception Laboratory
Space and Naval Warfare Systems Center, San Diego, CA
Advisor: Benjamin Migliori
2015
R&D Engineer, Cognitive Perception and Computational Intelligence Laboratory
Applied Research Laboratory, State College, PA
Advisor: John Sustersic and Brad Wyble
2014
Field Research Technician, Waibira Research Project
Budongo Conservation Field Center, Budongo Forest, Uganda
Advisor: Catherine Hobaiter
2012–2014
Research Assistant, Comparative Communication Laboratory
The Pennsylvania State University, State College, PA
Advisor: Daniel Weiss

Honors and Awards

2019
Annette Merle-Smith Fellowship
Center for Research and Training in Anthropogeny
2018
Norman Henry Anderson Scholar Prize
UC San Diego, Psychology Dept.
2018
Student Travel Award
Computational Cognitive Neuroscience (CCN)
2016
Graduate Research Fellowship
National Science Foundation (NSF)
2012
President's Fund for Undergraduate Scholars
The Pennsylvania State University

Publications

Tim Sainburg, Brad Theilman, Marvin Thielk, and Tim Gentner, “Parallels in the sequential organization of birdsong and human speech”, Nature Communications, 2019.

Preprints

Tim Sainburg, Marvin Thielk, Brad Theilman, Benjamin Migliori, and Timothy Q. Gentner, “Generative adversarial in-terpolative autoencoding: adversarial training on latent space interpolations encourage convexlatent distributions”, arXiv. 1807.06650, 2018.

Under Review

Willem Zuidema, Robert M. French. Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg, Timothy Q. Gentner, “Five ways in which computational models can help advancing Artificial Grammar Learning research”, Topics in Cognitive Sciences (TiCS), 2019 (to appear).

In Preparation

Tim Sainburg, Marvin Thielk, and Tim Gentner, “Exploring and exploiting acoustic spaces of animal vocalizations”, In Preparation
Tim Sainburg, Marvin Thielk, and Tim Gentner, “Birdbrain: A Python tool for 3D brain visualization for songbirds and other animals.”, In Preparation
Marvin Thielk, Tim Sainburg, Tatyana Sharpee, and Tim Gentner, “Synthetic vocalizations reveal a shared perceptual space predicted by relationships in neural population activity shared across birds and recording sites.”, In Preparation

Conference Papers

Tim Sainburg, Marvin Thielk, and Timothy Q. Gentner, “Learned context dependent categorical perception in a songbird”, Computational Cognitive Neuroscience (CCN), 2018.
Marvin Thielk, Tim Sainburg, Tatyana Sharpee, and Timothy Q. Gentner, “Combining Biological and Artificial Approaches to Understand Perceptual Spaces for Categorizing Natural Acoustic Signals”, Computational Cognitive Neuroscience (2018), 2018.

Datasets

Zeke Arneodo, Tim Sainburg, James Jeanne, & Timothy Q Gentner, “An acoustically isolated European starling song library”, Zenodo, 2019.

Conference Presentations (Poster)

Tim Sainburg, Marvin Thielk, and Timothy Q. Gentner, “Animal Vocalization Generative Network (AVGN): A method for visualizing, understanding, and sampling from animal communicative repertoires”, Cognitive Science Society 2019 (CogSci), 2019.
Tim Sainburg, Marvin Thielk, Brad Theilman, and Timothy Q. Gentner, “Sequential organization in birdsong and language: implications for neuroscience and AI”, Center for Englineered Natural Intelligence Symposium (CENI 2018), 2018.
Tim Sainburg, Marvin Thielk, and Timothy Q. Gentner, “Learned context dependent categorical perception in songbirds”, Society for Neuroscience (SfN), 2018.
Marvin Thielk, Tim Sainburg, Tatyana Sharpee, and Timothy Q. Gentner, “Combining Biological and Artificial Approaches to Understand Perceptual Spaces for Categorizing Natural Acoustic Signals”, Cognitive Computational Neuroscience (CCN), 2018.
Tim Sainburg, Marvin Thielk, and Timothy Q. Gentner, “Latent manifold analysis reveals parallels in hierarchical patterning of birdsong and human speech”, Computational and Systems Neuroscience (COSYNE), 2017.
Marvin Thielk, Tim Sainburg, Tatyana Sharpee, and Timothy Q. Gentner, “Shared perceptual spaces for high-dimensional natural acoustic signals”, Computational and Systems Neuroscience (COSYNE), 2017.
Tim Sainburg, Marvin Thielk, Brad Theilman, and Timothy Q. Gentner, “Latent manifold analysis reveals parallels in hierarchical patterning of birdsong and human speech”, Computational and Systems Neuroscience (COSYNE), 2017.
Tim Sainburg, Brad Theilman, and Timothy Q. Gentner, “Mechanisms for category learning in songbirds”, Society for Neuroscience, 2016.

Conference Presentations (Oral)

2018
Generative modelling for birdsong: learned acoustic spaces for generating stimuli, labelling syllables, and visualizing sequences
Birdsong (SfN Satellite)
2018
Learned context dependent categorical perception in a songbird
Computational Cognitive Neuroscience (CCN)
2016
Analyzing birdsong with neural networks
SSC Pacific Workshop on Naval Applications of Machine Learning

Invited Talks

2018
Sequential structure of learned vocal communization
Anderson Prize Address, UC San Diego

Software Libraries

tensorflow_generative_models, Tensorflow2/Colab implementations of a number of audio and image generative models.
birdbrain, Python MRI atlas visualization tool for several songbirds and bats.
noisereduce, Spectral noise reduction package for python.
AVGN, Latent space models for visualizing and manipulating animal communization signals.

Teaching

2018
Brain, Behavior, and Evolution, Teaching Assistant, University of California, San Diego
2018
Sensory Neuroscience, Teaching Assistant, University of California, San Diego
2017
General Psychology, Teaching Assistant, University of California, San Diego
2016
Cognitive Psychology, Teaching Assistant, University of California, San Diego
2013–2014
Biology: Basic Concepts and Biodiversity, Peer Leader/Tutor, The Pennsylvania State University

Mentorship

2019
Meixuan Jiang, Undergraduate at UCSD
2019
Yijia Yan, Undergraduate at UCSD
2019
Jimmy Lozono, Undergraduate at UCSD
2016–2018
Darvesh Gorhe, Undergraduate at UCSD
2017
Hector Ponce, Undergraduate at UCSD

Academic Service

2017–2019
External Funding Officer, UCSD Psychology

Reviewer

Animal Behavior

Additional Coursework

2019
Diverse Intelligences Summer School (DISI), St. Andrews, Scotland

Employment and Business Ventures

2007–2012
Brambling Design, Co-Founder/Lead Developer