Point Pinole Regional Shoreline (Jan. 2017)
Dan Yamins, PhD
principal investigator
Dan joined Stanford in September 2016. He's a member of the Departments of Psychology and Computer Science, the Wu Tsai Neurosciences Institute, and the Stanford Artificial Intelligence Laboratory. He is a recipient of the McDonnell Foundation Scholar, Sloan Research Fellowship, and NSF CAREER awards, and is a Simons Foundation Investigator. Prior to moving to Stanford, he did his postdoc at MIT in the Department of Brain and Cognitive Sciences. He received his BA in Mathematics and PhD in Applied Mathematics from Harvard University.
principal investigator
Dan joined Stanford in September 2016. He's a member of the Departments of Psychology and Computer Science, the Wu Tsai Neurosciences Institute, and the Stanford Artificial Intelligence Laboratory. He is a recipient of the McDonnell Foundation Scholar, Sloan Research Fellowship, and NSF CAREER awards, and is a Simons Foundation Investigator. Prior to moving to Stanford, he did his postdoc at MIT in the Department of Brain and Cognitive Sciences. He received his BA in Mathematics and PhD in Applied Mathematics from Harvard University.
Jinyao Yan, PhD
postdoctoral researcher
Jinyao joined SNAIL in November 2019. Before coming to SNAIL, she received her BS in Electrical Engineering from East China Normal University, her PhD in Electrical and Computer Engineering from Michigan State University (Go Green Go White!), and worked as a graduate research fellow at the Janelia Research Campus.
postdoctoral researcher
Jinyao joined SNAIL in November 2019. Before coming to SNAIL, she received her BS in Electrical Engineering from East China Normal University, her PhD in Electrical and Computer Engineering from Michigan State University (Go Green Go White!), and worked as a graduate research fellow at the Janelia Research Campus.
Dan Bear, PhD
postdoctoral researcher
Is there more than one way to see a cat? For difficult problems in vision, like recognizing objects and high- properties in a complex scene, evolution and machine-learning methods have arrived at a similar solution. I am exploring whether this is true in general: Are the algorithms implemented in our brain tailored to perform particular tasks? And if we find out which tasks, can we train artificial neural networks to act like we do? These questions will illuminate the links between natural and artificial intelligence.
Before coming to SNAIL, I received an A.B. in Molecular and Cellular Biology and a Ph.D. in Neuroscience, both from Harvard University.
postdoctoral researcher
Is there more than one way to see a cat? For difficult problems in vision, like recognizing objects and high- properties in a complex scene, evolution and machine-learning methods have arrived at a similar solution. I am exploring whether this is true in general: Are the algorithms implemented in our brain tailored to perform particular tasks? And if we find out which tasks, can we train artificial neural networks to act like we do? These questions will illuminate the links between natural and artificial intelligence.
Before coming to SNAIL, I received an A.B. in Molecular and Cellular Biology and a Ph.D. in Neuroscience, both from Harvard University.
Tyler Bonnen
PhD student (psychology; joint with Anthony Wagner)
After transferring from Miami-Dade Community College, tyler studied chemistry and comparative literature at Columbia University. He went on to research fellowships in the Max-Planck Institute in Leipzig, and then in the Department of Brain and Cognitive Sciences at MIT. Currently, his work integrates biologically plausible computational models, neural data, and animal behavior in order to formalize the relationship between perception and memory.
PhD student (psychology; joint with Anthony Wagner)
After transferring from Miami-Dade Community College, tyler studied chemistry and comparative literature at Columbia University. He went on to research fellowships in the Max-Planck Institute in Leipzig, and then in the Department of Brain and Cognitive Sciences at MIT. Currently, his work integrates biologically plausible computational models, neural data, and animal behavior in order to formalize the relationship between perception and memory.
Honglin Chen
PhD student (Computer Science)
Honglin is a PhD student in the Department of Computer Science. Prior to joining Stanford, he received his BS in Mathematics of Computation from University of California, Los Angeles in 2018. During 2018 - 2019, he was a research assistant in the Center for Brains, Minds & Machines (CBMM) at MIT. Honglin joined SNAIL in March 2020.
PhD student (Computer Science)
Honglin is a PhD student in the Department of Computer Science. Prior to joining Stanford, he received his BS in Mathematics of Computation from University of California, Los Angeles in 2018. During 2018 - 2019, he was a research assistant in the Center for Brains, Minds & Machines (CBMM) at MIT. Honglin joined SNAIL in March 2020.
Daniel Kunin
PhD student (Computational & Mathematical Engineering; joint with Surya Ganguli)
I am a PhD Candidate at the Institute for Computational and Mathematical Engineering focused on computational neuroscience and deep learning theory under the direction of Surya Ganguli and Daniel Yamins. My research focuses on the dynamics of artificial neural network models during training and how to leverage this understanding to generate hypotheses of how biological neural networks might learn.
PhD student (Computational & Mathematical Engineering; joint with Surya Ganguli)
I am a PhD Candidate at the Institute for Computational and Mathematical Engineering focused on computational neuroscience and deep learning theory under the direction of Surya Ganguli and Daniel Yamins. My research focuses on the dynamics of artificial neural network models during training and how to leverage this understanding to generate hypotheses of how biological neural networks might learn.
Eshed Margalit
PhD student (Neuroscience; joint with Kalanit Grill-Spector)
Eshed is a PhD student in the Neurosciences Graduate Program. His interests include the spatial organization and function of high-level visual cortex and the development of biologically-inspired neural networks. Prior to his work at Stanford, Eshed studied models of early visual cortex, developmental prosopagnosia, and the representation of objects in the lateral occipital complex.
PhD student (Neuroscience; joint with Kalanit Grill-Spector)
Eshed is a PhD student in the Neurosciences Graduate Program. His interests include the spatial organization and function of high-level visual cortex and the development of biologically-inspired neural networks. Prior to his work at Stanford, Eshed studied models of early visual cortex, developmental prosopagnosia, and the representation of objects in the lateral occipital complex.
Josh Melander
PhD student (Neuroscience; joint with Steve Baccus)
Josh was trained in cellular biology and physiology at Whitman College (Walla Walla, WA) and the Vollum Institue (Portland, OR). Co-mentored by Steve Baccus (Neurobiology) Josh applies his passion for experimental science to problems at the interface of neurobiology and machine learning. Combiningin vivo physiology (optical and electrical recording) and state-of-the-art machine-learning techniques, Josh studies the strategies that biological systems (neurons and circuits) employ to facilitate flexible and robust behavior in natural environments.
PhD student (Neuroscience; joint with Steve Baccus)
Josh was trained in cellular biology and physiology at Whitman College (Walla Walla, WA) and the Vollum Institue (Portland, OR). Co-mentored by Steve Baccus (Neurobiology) Josh applies his passion for experimental science to problems at the interface of neurobiology and machine learning. Combining
Damian Mrowca
PhD student (Computer Science; joint with Fei-Fei Li)
Damian received his BA (2012) and MSc (2015) in Electrical Engineering and Information Theory, both from the Technical University of Munich. During 2014-2015 he was a visiting student in machine learning at UC Berkeley. After a year in start-up land, he joined the lab in September 2016.
PhD student (Computer Science; joint with Fei-Fei Li)
Damian received his BA (2012) and MSc (2015) in Electrical Engineering and Information Theory, both from the Technical University of Munich. During 2014-2015 he was a visiting student in machine learning at UC Berkeley. After a year in start-up land, he joined the lab in September 2016.
Aran Nayebi
PhD student (Neuroscience; joint with Surya Ganguli)
Aran is a PhD student in the Neurosciences Graduate Program. He earned his Master's degree in Computer Science (AI Specialization), as well as both undergraduate majors in Mathematics and Symbolic Systems, from Stanford University. His primary interests lie at the intersection of machine learning and neuroscience, where he uses tools from deep learning and statistics to approach problems in systems neuroscience. He has also previously worked in theoretical computer science and mathematical logic.
PhD student (Neuroscience; joint with Surya Ganguli)
Aran is a PhD student in the Neurosciences Graduate Program. He earned his Master's degree in Computer Science (AI Specialization), as well as both undergraduate majors in Mathematics and Symbolic Systems, from Stanford University. His primary interests lie at the intersection of machine learning and neuroscience, where he uses tools from deep learning and statistics to approach problems in systems neuroscience. He has also previously worked in theoretical computer science and mathematical logic.
Javier Sagastuy-Brena
PhD student (Computational & Mathematical Engineering)
Javier joined SNAIL in September 2018 interested in biologically-inspired computational intelligence. His interests grew to include using computational models to understand how the brain works, along with recurrent models of the visual system, learning rules, and deep learning theory. Javier started his PhD in Computational and Mathematical Engineering in March 2020. He received his MS (2019) from ICME at Stanford and earned both Applied Mathematics and Computer Engineering BS degrees from ITAM in Mexico City (2015). Before starting grad school, he spent two years working at a Mexican FinTech startup, teaching Computer Science, and doing research in machine learning for text mining. His non-academic interests include alpine skiing, hiking, and cooking.
PhD student (Computational & Mathematical Engineering)
Javier joined SNAIL in September 2018 interested in biologically-inspired computational intelligence. His interests grew to include using computational models to understand how the brain works, along with recurrent models of the visual system, learning rules, and deep learning theory. Javier started his PhD in Computational and Mathematical Engineering in March 2020. He received his MS (2019) from ICME at Stanford and earned both Applied Mathematics and Computer Engineering BS degrees from ITAM in Mexico City (2015). Before starting grad school, he spent two years working at a Mexican FinTech startup, teaching Computer Science, and doing research in machine learning for text mining. His non-academic interests include alpine skiing, hiking, and cooking.
Elias Wang
PhD student (Electrical Engineering)
Elias received his BS in Electrical and Computer Engineering from Cornell University in 2016 and is now pursing his PhD in Electrical Engineering. His interests involve the understanding of natural intelligence and the creation of artificial intelligence. In particular, he hopes to build intelligent systems that are more general, flexible, and robust.
PhD student (Electrical Engineering)
Elias received his BS in Electrical and Computer Engineering from Cornell University in 2016 and is now pursing his PhD in Electrical Engineering. His interests involve the understanding of natural intelligence and the creation of artificial intelligence. In particular, he hopes to build intelligent systems that are more general, flexible, and robust.
Violet Xiang
PhD student (Psychology)
Violet received BS in Informatics (2016) and MS in computer science (2020) at Indiana University. Between undergrad and master’s, she worked in a financial service company. She is now pursuing her PhD in Psychology. Her research interests are in understanding how experience across multi-modality shapes perception, and building developmentally inspired artificial agents.
PhD student (Psychology)
Violet received BS in Informatics (2016) and MS in computer science (2020) at Indiana University. Between undergrad and master’s, she worked in a financial service company. She is now pursuing her PhD in Psychology. Her research interests are in understanding how experience across multi-modality shapes perception, and building developmentally inspired artificial agents.
Chengxu Zhuang
PhD student (Psychology)
Chengxu received his BEng in Electrical Engineering and BS in Mathematics from Tsinghua University in 2016. He joined the lab in September 2016.
PhD student (Psychology)
Chengxu received his BEng in Electrical Engineering and BS in Mathematics from Tsinghua University in 2016. He joined the lab in September 2016.
Megumi Sano
Undergraduate/MS co-term student
Meg is pursuing a B.S. in Mathematical and Computational Science (’21) and a M.S. in Computer Science (Artificial Intelligence track, ’22) at Stanford. She is interested in using insights from human development, cognition, and behavior to build more flexible and general artificial agents. She joined the lab in the summer of 2019.
Undergraduate/MS co-term student
Meg is pursuing a B.S. in Mathematical and Computational Science (’21) and a M.S. in Computer Science (Artificial Intelligence track, ’22) at Stanford. She is interested in using insights from human development, cognition, and behavior to build more flexible and general artificial agents. She joined the lab in the summer of 2019.
Lab Affiliates
Nisa Cao
administrative assistant
administrative assistant
Lab Alumni
Judy Fan, PhD
postdoctoral researcher
Judy earned her PhD in cognitive psychology from Princeton University in 2016, and her AB in neurobiology from Harvard College in 2010. She is interested in how visual perception, action, and social inference are coordinated to support learning and communication. After spending the 2018-2019 academic year here at Stanford, she started the Cognitive Tools lab in the psychology department at UCSD.
postdoctoral researcher
Judy earned her PhD in cognitive psychology from Princeton University in 2016, and her AB in neurobiology from Harvard College in 2010. She is interested in how visual perception, action, and social inference are coordinated to support learning and communication. After spending the 2018-2019 academic year here at Stanford, she started the Cognitive Tools lab in the psychology department at UCSD.
Nick Haber, PhD
postdoctoral researcher
Nick received his PhD in mathematics from Stanford University in 2013, and subsequently worked on the Autism Glass project. He joined NeuroAILab in January 2017 and finished up in December 2019. Happily, Nick has chosen to stay reasonably close by, starting the Autonomous Agents Lab here at Stanford's Graduate School of Education in January 2020.
postdoctoral researcher
Nick received his PhD in mathematics from Stanford University in 2013, and subsequently worked on the Autism Glass project. He joined NeuroAILab in January 2017 and finished up in December 2019. Happily, Nick has chosen to stay reasonably close by, starting the Autonomous Agents Lab here at Stanford's Graduate School of Education in January 2020.
Stephanie Wang
research associate
Stephanie graduated in 2017 with her BS in Symbolic Systems from Stanford University. She joined SNAIL as a Masters student in Computer Science studying artificial intelligence and machine learning, graduating in June 2018. Previously she worked with Stanford's InfoLab on weak supervision.
research associate
Stephanie graduated in 2017 with her BS in Symbolic Systems from Stanford University. She joined SNAIL as a Masters student in Computer Science studying artificial intelligence and machine learning, graduating in June 2018. Previously she worked with Stanford's InfoLab on weak supervision.
Blue Belmont Sheffer
research assistant
Blue is a recent graduate of the Symbolic Systems Program at Stanford University (B.17) where he studied computational neuroscience and machine learning. While at SNAIL, Blue worked on building modular continual learning agents and PTUtils, a package for reproducible deep learning with PyTorch. He currently works on brain-machine interfaces in Stanford's Neural Prosthetics Systems Laboratory.
research assistant
Blue is a recent graduate of the Symbolic Systems Program at Stanford University (B.17) where he studied computational neuroscience and machine learning. While at SNAIL, Blue worked on building modular continual learning agents and PTUtils, a package for reproducible deep learning with PyTorch. He currently works on brain-machine interfaces in Stanford's Neural Prosthetics Systems Laboratory.