Kavli Scholars

Ishmail Abdus-Saboor is an Associate Professor of Biological Sciences at Columbia University and a Freeman Hrabowski Scholar at the Howard Hughes Medical Institute. He studies how the nervous system encodes touch, from soft gentle caresses to itchy mosquito bites to harsh painful stimulation. And he has been opening new ground in sensory science by uncovering skin-to-brain circuits that underlie rewarding social touch. His research lab uses systems neuroscience, computation genetics, and mathematics to link animal behavior with genes and neural circuits. In 2024, he was named in a list of “50 Scientist that Inspire” by Cell Press and was the recipient of a One Mind Rising Star Award. Abdus-Saboor holds a PhD degree in Cell and Molecular Biology from the University of Pennsylvania and received his bachelor’s degree in Animal Science from North Carolina A&T State University.  

Vikram Gadagkar is an Assistant Professor of Neuroscience at Columbia University. His research centers on how the brain learns skills and evaluates behaviors—both self-generated and the behaviors of others. A deeper cellular and neurochemical understanding of these processes could provide leads for treating neurological disorders such as Parkinson's disease and autism. His research lab studies songbirds, exploring how young male finches learn mating songs and how female finches evaluate those songs. He has earned numerous awards and honors, including the NIH Director’s New Innovator Award. Gadagkar received a PhD in Physics from Cornell University, an MS in Physics from the Indian Institute of Science, and a BS in Physics, Chemistry, and Mathematics from Bangalore University.

Rainer Engelken's work focuses on understanding the stability and dynamics of recurrent neural networks with biological constraints. He investigates how time-varying stimuli are encoded and processed in neural populations, how one brain area influences another despite unpredictable neural activity, and how neural networks can maintain stable dynamics. By connecting theory with experiment, Engelken’s research provides insights into temporal learning and how perturbations like optogenetic stimulation impact neural activity. His findings have implications for designing experiments and understanding the brain’s remarkable ability to process information across time.

Salomon Muller explores the computational principles underlying how the cerebellum and associated neural structures form and use internal models to improve sensory encoding and refine behavioral control. Currently, Salomon is developing computational models to understand how the Dorsal Cochlear Nucleus learns to modulate its response to predicted auditory signals, effectively smoothing out responses to expected sounds. His work also examines the mechanisms through which cerebellar wiring during critical developmental periods addresses credit assignment challenges—determining how specific neural connections contribute to adaptive learning through plasticity in post-critical period. Muller collaborates with experimental neuroscientists to bridge theoretical models and cerebellar physiology, contributing to a deeper understanding of cerebellar function across sensory and motor domains.

Tala Fakhoury is a PhD student studying reasoning, planning, and working memory. She combines computational modeling with cutting-edge electrophysiology, using Neuropixels technology to record from thousands of neurons in the prefrontal cortex. Her goal is to uncover fundamental insights into how humans tackle complex decision-making and problem-solving. Fakhoury earned her undergraduate degree in Biomedical Engineering and Neuroscience at Duke University, followed by a master's in Computational Neuroscience at the University of Pennsylvania, under the mentorship of Dr. Dani Bassett.

David Clark investigates how fundamental properties of neural circuits—their large scale, nonlinear dynamics, and plastic connections—give rise to computation and learning. By combining statistical physics with machine learning approaches, he develops theoretical frameworks to understand how neural networks process information. Clark completed his undergraduate studies in Physics and Computer Science at UC Berkeley and is currently pursuing his PhD in Neurobiology and Behavior at Columbia University's Theory Center.

Minni Sun studies navigational algorithms in fruit flies. She combines data analysis and neural circuit modeling to investigate neural mechanisms underlying flexible navigation strategies. Sun completed her undergraduate studies in Machine Intelligence at Peking University and is currently a PhD candidate in the Center for Theoretical Neuroscience at Columbia University. 

Elom Amematsro, a PhD student in the Neurobiology and Behavior program, combines theoretical and experimental approaches to study the neural mechanisms underlying our ability to acquire and adapt large sets of skills for solving novel problems. He does so by combining approaches from theoretical neuroscience and machine learning with state-of-the-art electrophysiology to identify how these cognitive abilities arise from the interactions of distributed neural circuits. Prior to joining Columbia's Center for Theoretical Neuroscience, Amematsro completed his undergraduate degree in Physics and Mathematics at the University of Utah.

Tuan Nguyen is a PhD student studying the connectivity and sensory feature encoding of the mammalian primary visual cortex and the development of these properties in the absence of visual experience. Through statistical analyses of biologically-plausible theoretical models, he seeks to elucidate the mechanisms by which visual inputs and behavioral state signals are integrated and modulate neural population responses. His research also explores computational models of cortical feature map development, examining how experience-dependent synaptic plasticity drives feature selectivity prior to eye-opening. Nguyen completed his undergraduate studies in Physics at MIT.