P.I.
CS is an Assoc. Professor in Neural Science and Data Science at NYU and the Director for Graduate Studies (PhD) in the Center for Data Science. After a PhD at Goethe University in Frankfurt, studying the role of different forms of plasticity in unsupervised learning, Cristina worked as postdoctoral researcher at Cambridge University developing normative models of memory. This was followed by a short stint at ENS Paris, modeling probabilistic computation in spiking neurons, and an independent research fellowship at IST Austria, building statistical tools for quantifying learning in multiunit recordings. Her lab at NYU studies neural principles of adaptive computation by combining theory and statistical analyses of experimental data from many collaborators.
Postdoc
Matt earned his Ph.D. in Electrical Engineering from Stony Brook University where he was advised by Il Memming Park. He is broadly interested in developing statistical tools and models of neural computation, with a focus on probabilistic modeling of neural population dynamics, approximate Bayesian inference, and creating efficient, data-driven algorithms.
Postdoc
Harsha earned a BS in Biology and Mathematics from Indian Institute of Science, and a PhD in Neuroscience from University College London. She then worked as a Schmidt Science Fellow with Bing Brunton at University of Washington. Harsha uses data-driven and computational approaches to identify neural dynamics that support flexibility on slow and fast timescales and study how these dynamics are learned via multiple forms of errors. She is also interested in developing statistical methods for designing and interpreting neural perturbations.
Postdoc
David has a B.S. in Chemistry and a B.A. in Mathematics and Italian from Indiana University and a PhD in Physical Chemistry from Princeton, followed by a postdoc with Il Memming Park at Stony Brook University. He is broadly interested in understanding and manipulating low-dimensional neural dynamical systems, with a particular application to cognitive processes such as decision making
PhD student
Born and raised in China, Yaxin moved to New York City for graduate studies in Statistics at Fordham University. Her research interests focus on combining experimental methods and machine learning approaches to understand how information is encoded in the brain and the role of eye movements during navigation. She is also interested in decoding and developing tools to interpret neural activity.
PhD Student (co-advised by Eero Simoncelli)
Ben has a B.A. in Physics from the University of Chicago. Using tools from machine learning and physics, he studies how the brain uses its prior knowledge of the visual world to perform optimal inference across a diverse array of perceptual tasks.
PhD student (co-advised by Eero Simoncelli)
Julie has a BSc in mathematics from the University of Hong Kong. She aims to develop normative theories of how temporal prediction guides learning and how such mechanisms are implemented in the brain. She is also interested in applying these insights to artificial neural networks and engineering problems.
PhD student
William is a PhD student at the NYU Center for Data Science. His interests revolve around continual and multitask machine learning. Prior to NYU, William graduated from Texas A&M University with a Bachelor’s degree in Computer Science and worked as a software engineer in the finance industry
PhD student (co-advised by Christine Constantinopole)
Danilo graduated from the University of Puerto Rico at Cayey in 2017 with a B.S. in Chemistry. For his doctoral research, he is interested in developing computational methods for the characterization of low-dimensional structure of neural firing patterns during decision making.
Current rotation students/interns/visitors
Maanav Chittireddy - research intern
Jordan Glover - Simons-NSBP summer intern
Arihant Goja - UG research
Allen Guo - CDS CURP
Daniel Im - collaborator
JaeHeon Lee - KAIST UG research
Akif Erdem Sagtekin - MS thesis and Flatiron intern
Yanqi Xu - collaborator
Jingya Zhang - NYU Shanghai UG intern
Alumni
Edoardo Balzani, Postdoc; staff scientist Flatiron.
Gauthier Boeshertz - MS from ETH; PhD Imperial
Colin Bredenberg, PhD; postdoc MILA.
Caroline Haimerl, PhD; postdoc Champalimaud.
Pedro Herrero Vidal, PhD; data scientist Amazon.
Owen Marschall, PhD; postdoc Columbia U.
Camille Rullan Buxo, PhD; postdoc Harvard.
Other past lab members
Elliott Capek - rotation
Anthony Chen - rotation
Abdiel Cortes - CURP
Andrea Cumpelik - guest researcher
Isabel Garon - rotation
Laura Green - rotation
Jintao Gu - rotation
Peyiao Hu - rotation
Jianming Hu - UG research
Roman Huszar - rotation
Heejae Jang - rotation
Richard-John Lin - MS
Shenghao Lin - undergraduate intern
Conor McGrory - research assistant
Katie Ross - undergraduate intern
Bria Ross-Butler - CURP
Heike Stein - visiting postdoc
Nicole Tomassi - SURP
Thomas Edward Yerxa - rotation
Klavdia Zemlianova - rotation
Hank Zhang - rotation
Rong Zhao - intern
Sam Zheng - rotation
Collaborators (past and present)
Dora Angelaki, NYU
Gyuri Buszaki, NYU
Christine Constantinopole, NYU
Jozsef Csicsvari, IST Austria, AT
Peter Dayan, Gatsby Unit, UCL, UK
Sophie Deneve, Group for Neural Theory, ENS Paris, FR
Andre Fenton, NYU
Joszef Fiser, CEU Budapest, HU
Rob Froemke, NYU
Roozbeh Kiani, NYU
Mate Lengyel, Cambridge University, UK
Joerg Luecke, Oldenburg University, DE
JP Noel, Minnesota
Dima Rinberg, NYU
Eero Simoncelli, NYU/Flatiron
Gasper Tkacik, IST Austria, AT
Alex Williams, NYU/Flatiron
SCENE team
Open positions
Open call for postdoc interested in working on reinforcement learning theory and its application to animal behavior. Reach out to CS for details.
RA with machine learning and software engineering expertise for updating SCENE relevant statistical data analysis pipelines.
We recruit students via the Neuroscience, Data Science and Bioengineering graduate programs at NYU
Contact CS for PhD rotation
projects and for informal
PhD/Postdoc queries.
We will not be considering new intern requests until spring 2026.
You?