
Daniel Yamins
Assistant Professor of Psychology and of Computer Science
On Leave from 09/01/2021 To 06/30/2022
Academic Appointments
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Assistant Professor, Psychology
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Assistant Professor, Computer Science
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Member, Bio-X
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Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
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Member, Wu Tsai Neurosciences Institute
Program Affiliations
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Symbolic Systems Program
Professional Education
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Ph.D., Harvard University, Applied Mathematics (2008)
Current Research and Scholarly Interests
Our lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:
H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.
H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.
We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis.
2021-22 Courses
- Triangulating Intelligence: Melding Neuroscience, Psychology, and AI
CS 322, PSYCH 225 (Win) -
Independent Studies (14)
- Advanced Reading and Research
CS 499 (Aut, Win, Spr, Sum) - Advanced Reading and Research
CS 499P (Aut, Win, Spr, Sum) - Curricular Practical Training
CS 390A (Aut, Win, Sum) - Directed Reading in Neurosciences
NEPR 299 (Aut, Win, Spr, Sum) - Graduate Research
NEPR 399 (Aut, Win, Spr, Sum) - Graduate Research
PSYCH 275 (Aut, Win, Spr, Sum) - Independent Project
CS 399 (Aut, Win, Spr, Sum) - Independent Study
SYMSYS 296 (Win) - Independent Work
CS 199 (Aut, Win, Spr) - Independent Work
CS 199P (Win) - Reading and Special Work
PSYCH 194 (Aut, Win) - Research
PHYSICS 490 (Aut, Win) - Senior Project
CS 191 (Spr) - Special Laboratory Projects
PSYCH 195 (Aut, Win)
- Advanced Reading and Research
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Prior Year Courses
2020-21 Courses
- Advanced Statistical Modeling
PSYCH 253 (Spr) - High-level Vision: From Neurons to Deep Neural Networks
PSYCH 250 (Win)
2019-20 Courses
- Advanced Statistical Modeling
PSYCH 253 (Spr) - Large-Scale Neural Network Modeling for Neuroscience
CS 375, PSYCH 249 (Aut) - NeuroTech Training Seminar
NSUR 239, STATS 242 (Win) - Theoretical Neuroscience
APPPHYS 293, PSYCH 242 (Spr)
2018-19 Courses
- High-Dimensional Methods for Behavioral and Neural Data
PSYCH 253 (Spr) - High-level Vision: From Neurons to Deep Neural Networks
CS 431, PSYCH 250 (Spr) - Large-Scale Neural Network Modeling for Neuroscience
CS 375, PSYCH 249 (Aut) - Theoretical Neuroscience
APPPHYS 293, PSYCH 242 (Spr)
- Advanced Statistical Modeling
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Akshay Jagadeesh, Andrew Nam, tyler bonnen -
Postdoctoral Faculty Sponsor
Daniel Bear, Logan Cross -
Doctoral Dissertation Advisor (AC)
Alex Durango, Kevin Feigelis, Eshed Margalit, Javier Sagastuy Brena, Eli Wang, Chengxu Zhuang -
Orals Evaluator
Alex Tseng -
Doctoral Dissertation Co-Advisor (AC)
Josh Melander, Aran Nayebi -
Master's Program Advisor
Sharan Ramjee, Kannan Sankaragomathi, Danny Schwartz, Anfal Siddiqui, David Zhou -
Postdoctoral Research Mentor
Daniel Bear -
Doctoral (Program)
Honglin Chen