people

Nick Haber

Principal Investigator

Nick is an Assistant Professor at the Stanford Graduate School of Education, and by courtesy, Computer Science. After receiving his PhD in mathematics on Partial Differential Equation theory, he worked as a postdoctoral fellow at Stanford in both the Wall Lab (working chiefly on the Autism Glass Project) and the NeuroAI Lab (on building curiosity within artificial intelligence, as well as cognitive models).

Logan Cross

Postdoctoral Fellow

Logan received a B.S. from University of Southern California (Neuroscience) and a Ph.D. from the California Institute of Technology (Computation and Neural Systems). During his graduate work, he worked with John O’Doherty and studied how the human brain makes decisions in complex domains by using cutting-edge methods in neuroimaging and machine learning. Logan also completed an internship at Google DeepMind, where he build deep reinforcement learning algorithms to solve a challenging a meta-learning benchmark. His research broadly examines how intelligence arises in humans and can be built in machines by combining approaches and insights from a variety of disciplines, including computational neuroscience, deep learning, and developmental psychology.

Isaac Kauvar

Postdoctoral Fellow

Isaac Kauvar received a B.S. (Engineering Physics), M.S. (Electrical Engineering) and PhD (Electrical Engineering) from Stanford. During his graduate work, jointly in the labs of Gordon Wetzstein and Karl Deisseroth, he developed tools for recording cortex-wide neural activity in mice, and he applied these tools to discover how circuits throughout the brain of behaving mammals function as a coupled system—and the consequences that can arise when they decouple. As a postdoc, he is excited to explore the phenomenon of curiosity

Chris Doyle

Research Scientist

Prior to his work in the lab, Chris was a co-founder of the technology startup Grove, where he designed an automation platform for financial advisors. Before his startup, Chris led an initiative at Malaria No More, sponsored by Google.org, to apply a new data source to identify counterfeit antimalarial medication. Chris started his career trading mortgage derivatives at Barclays and building predictive models of asset prices at a hedge fund. Chris received his undergraduate degree in Mathematics from the University of Virginia, where he was an Echols Scholar. In his research, Chris is working to build agents that are intrinsically motivated and can engage in social learning.

Merve Cerit

PhD Student (Graduate School of Education)

After receiving her B.S. degrees in Computer Engineering and Industrial Engineering from Bogazici University, Turkey, Merve worked as a Data & AI Tech Specialist at Microsoft. She worked on several award-winning projects in the Middle East & Africa region and led their AI Female Talent Program. Her passion for learning science led her to pursue her M.A. in Education at Stanford as a Fulbright Scholar. She studied in the Learning, Design, and Technology (LDT) program at the GSE, focusing on social and emotional learning. She is a huge supporter of women in tech, currently working as a Data Science Lead at an online vocational school for underserved women in Turkey. As a PhD student, she is excited to explore the intersection of affective computing and curiosity within artificial intelligence.

Wanjing Anya Ma

PhD Student (Graduate School of Education)

Anya is a Ph.D. student in the Learning Sciences and Technology Design program at Stanford, co-advised by Jason Yeatman and Nick Haber. She received her B.S. in Computer Science and Teaching Chemistry 7-12 from New York University and M.S.Ed in Learning Sciences and Technologies from the University of Pennsylvania. Anya’s previous research focused on science education and learning analytics under the guidance of Susan Kirch, Camillia Matuk, and Ryan Baker. After teaching middle school chemistry for two years in Brooklyn, NY, she became more interested in developing computational learning tools to support children with special needs. At Stanford, Anya is excited to explore adaptive reading assessments and interventions for children with varied reading abilities.

Fan-yun Sun

PhD Student (Computer Science)

Fan-yun Sun is a CS PhD student working on generating simulations for training embodied agents. He believes in leveraging (3D) vision/graphics and large language models to improve the sample efficiency and generalization ability for reinforcement learning.For more information, visit his personal website.

Eric Zelikman

PhD Student (Computer Science)

Eric Zelikman is a CS PhD student fascinated by how (and whether) algorithms learn meaningful representations and reason, with a particular interest in the way that we can apply inspiration from neuroscience and curiosity. Eric particularly cares about problems which require symbolic, compositional, and multi-step representations, and hopes that machine learning can also teach us about non-machine learning.

Xi Jia Zhou

PhD Student (Graduate School of Education)

Xi Jia is a PhD student studying Developmental Psychology and Learning Sciences and Technology Design in the School of Education. She received her B.S degree in Cognitive Science and Computer Science from Minerva University. Before PhD, she studied social learning and causal learning in Psychology Department at Stanford. Currently, she is curious about curiosity and attached with attachment theory.