Mehrdad Jazayeri, Ph.D 

Investigator, Howard Hughes Medical Institute
Investigator, McGovern Institute for Brain Research
Professor, Department of Brain and Cognitive Sciences
Director of Education, Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology

Postdocs

Ruidong Chen, Ph.D 

Ruidong is interested in how the brain uses hierarchical structures to make sense of the world and understand other minds.   Ruidong obtained his PhD from Cornell University where he studied the role of basal ganglia in motor skill learning in songbirds.  

Gabriel Stine, Ph.D 

Gabriel is interested in the computational principles that underlie cognitive processing and in the biological principles that govern how computation is achieved by neural circuits. His research is focused on cortical, subcortical, and cerebellar interactions during learning. Gabriel received his PhD from Columbia University where he studied the neurobiology of perceptual decision making.  

Mahdi Ramadan, Ph.D 

Mahdi’s interests lie at the intersection of neural computation and cognition. He uses a combination of computational modeling and electrophysiology to study cognitive inference. Mahdi uses tasks demanding multiple rapid and hierarchically organized decisions to characterize hierarchical and counterfactual reasoning. Through his research, Mahdi hopes to gain a glimpse into how neural dynamics maintain and control internal models involving multiple possibilities. Mahdi is also interested in how inductive biases of objects and events constrain cognitive and neural models. 

Zoe Boundy-Singer, Ph.D 

Zoe is interested in computations and neurobiological basis of confidence in sensorimotor behavior. Her approach consists of a combination of computational modeling, perceptual experiments, and electrophysiological recordings. Zoe received her PhD from the University of Texas at Austin where she studied how activity in early sensory cortex informs perceptual decisions and confidence.

Graduate Students

Setayesh Radkani

Setayesh is interested in using tools from psychology, cognitive neuroscience and machine learning to better understand our social and moral mind. She enjoys thinking about how we make sense of others’ actions, how we use this knowledge to navigate our social life and how we influence and change other minds.

Nicholas Watters 

Nick is interested in the neural basis of sample-efficient learning and structured generalization. He believes that both of these are in large part consequences of compositional representations and factorized computation. He studies these phenomena in the domain of intuitive physics and is particularly interested in how the brain represents and reasons about multiple visual objects. Nick also has a long-standing interest in artificial intelligence and hopes that his research may ultimately contribute to the development of AI algorithms that show more human-like learning efficiency and behavioral flexibility.

Aída Piccato 

Aída is interested in understanding the neural basis of memory strength – the precision and confidence with which we recall information. She is using experimental and computational techniques to identify the computations linking changes in neural activity over time to patterns of remembering and forgetting. She is interested in how these findings might inform models of memory that exhibit human-like flexibility and capacity.

Cheng Tang 

Cheng is interested in understanding how the brain composes new knowledge from known knowledge. Using neurophysiological recording on non-human primates, Cheng aims to find out the neural basis of the ability to solve novel problems with different compositions of known operations. He is also interested in comparing neural network models with biological data to test hypotheses about the brain, and developing biologically inspired artificial intelligence.

Hokyung Sung 

Hokyung is interested in how our brains “make sense” of the world. Concretely, he hopes to understand the neural basis of cognitive phenomena involving violations-of-expectation and their resolutions, with a focus on characterizing the computational principles that underlie explanations and explanation-seeking curiosity. More broadly, he is enthusiastic about investigating fundamental questions about the mind that lie at the intersection of philosophy, artificial intelligence, and neuroscience. 

Jack Gabel 

AI systems can trounce a grandmaster match after match, yet struggle to set up a chess board. Meanwhile, humans effortlessly manipulate a huge variety of objects. What is the neural basis of this behavioral flexibility? To answer this question, Jack aims to model the brain as subjects interact with physical scenes of objects.

Meghana Potta 

Meghana’s research interests lie in understanding the neural basis of flexible behavior. She specifically focuses on how our brains infer context and use inferred contexts to create more detailed and accurate models of the world, which in turn guide adaptive behavior. Additionally, she is interested in studying the neural implementations of canonical neural computations and how they can result in cognitive deficits when they go awry. Meghana holds a Master’s degree from the Institute of Neuroinformatics at ETH Zurich, where she explored and studied the use of linear time-invariant systems to better understand neural dynamics. 

Sol Markman 

Sol is interested in how humans and animals actively seek out information to make inferences and resolve uncertainties about the hidden states of the world. How do we decide which information is worth our time, energy, and cognitive effort to pursue? She hopes to gain insights about the neural circuitry and dynamics that support the computations underlying these flexible information-seeking behaviors.

Collaborators

Valmiki Kothare 

Robotics Engineer – Tabletop Project

Valmiki is interested in the intersection of neuroscience and robotics, from brain-computer interfaces to the study of the human brain as inspiration for robust, sample-efficient reinforcement learning in robot reasoning and motion. In his current role as Robotics Engineer for the Tabletop Project, Valmiki is designing the robotics control software and sensor data collection/processing pipeline that will automate electrophysiology experiments on physical reasoning tasks. Valmiki received his Master’s degree from Carnegie Mellon University, where his research focused on multi-objective path planning and multi-agent collaboration using reinforcement learning.

Other Research Personnel

Tara Sarma

MEng Student

Tara is an incoming MEng student interested in planning, attention, executive function, and the fundamental computations of the brain. She is also interested in how this relates to the production of language in the brain.

Mahdi Afshari

UROP Student

Mahdi is interested in how the brain can process abstract knowledge, logic and emotions into behavior. He is looking forward to further understand the neural basis underlying such internal inputs, how they can related to each other, and to implement a practical version of them in artificial intelligence

Lucas Shoji 

UROP Student

Lucas recently transitioned from a background in physics to neuroscience, driven by his curiosity about how the mind works, how it is rooted in the brain, its relationship with modern AI, and the intersections between these questions. He likes the dynamical systems approach and works with Hokyung to implement contextual inference in neural circuits.

Lab Manager and Technical Associates

Adhara Martellini 

Lab Manager

Adhara is broadly interested in the neural basis of cognition and the mechanisms that underlie complex and creative behaviors. She is also curious about innovative brain-interfacing technologies and about addressing questions at the intersection of philosophy of mind, computational modeling and neuroscience.

Yuelai (Mollie) Feng 

Technical Associate I

Mollie is interested in the neural codes that shape our fundamental human experience—including spatiotemporal perception, memory, abstraction, and decision-making. She would like to explore these topics with electrophysiology experiments and dynamical systems modeling.

Michal De-Medonsa 

Website Manager

Victor de Lafuente
National Autonomous University of Mexico

Ila Fiete
Massachusetts Institute of Technology

Stefano Fusi
Columbia University Medical Center

Valerio Mante
University of Zurich

Srdjan Ostojic
École de Neurosciences Paris

Maneesh Sahani
University College London

Rebecca Saxe
Massachusetts Institute of Technology

Krishna Shenoy
Stanford University

David Sussillo
Stanford and Google AI

Josh Tenenbaum
Massachusetts Institute of Technology

Postdoctoral Research Supervised (primary supervisor)
Aran Nayebi, PhD (2022-2024)
Sujaya Neupane, PhD (2018-2024)
Hansem Sohn, PhD (2015-2023)
Michael Yoo, PhD (2020-2022)
Rishi Rajalingham, PhD (2019-2022)
Egger, Seth, PhD (2013-2019)
Remington, Evan, PhD (2014-2019)
Wang, Jing, PhD (2013-2018)
Narain, Devika, PhD (2015-2017)
Aghdaee, Mehdi, PhD (2013)

PhD Students Supervised (primary supervisor)
Mahdi Ramadan (2024)
Alexandra Ferguson (2023)
Eli Pollock (2022)
Morteza Sarafyazd (2021)
Nicolas Meirhaeghe (2021)

Visiting Members
Albert Qin, UROP Student (2023)
Olivia Gozel, Ph.D (2023)
Isabella Milanes, MSRP Summer Intern (2023)
Adam Gosztolai, Ph.D (2023)
Jason Li, , UROP Student (2022-2023)
Xiaomei Fan, SCGB Fellow (SURF Program) (2022)
Sandy Wang, SCGB Fellow (SURF Program) (2022)
Chisom Ume, SCGB Fellow (SURF Program) (2022)
Clara Melhem, SCGB Fellow (SURF Program) (2022)
Dagim Belete (2021)
Shadi Tasdighi Kalat (2019)
Xiang Li (2017)
Lucy Lai, CSNE (2016)
Elliot Nauert, MSTP CBMM (2015)
Vivian Liu, MSRP (2014)
Chau Vu, UROP, MIT (2013)

Staff
Neelima Valluru (2022 – 2024)
Jack Gabel (2021-2023)
T. Vincenza Parks (2016-2020)
Adam Akkad (2017-2020)
Eghbal Asl Hosseini (2015-2016)
Rossana Chung (2013-2018)