Ila Fiete, PI
Ila Fiete is a Professor in the Department of Brain and Cognitive Sciences and an Associate Member of the McGovern Institute at MIT. She directs the K. Lisa Yang Integrative and Computational Neuroscience Center. Ila obtained her undergraduate degrees in Physics and Mathematics at the University of Michigan and her M.A. and Ph.D. in Physics at Harvard, under the guidance of Sebastian Seung at MIT (co-advised by Daniel Fisher). Her postdoctoral work was at the Kavli Institute for Theoretical Physics at Santa Barbara, and at Caltech, where she was a Broad Fellow. She was subsequently on the faculty of the University of Texas at Austin in the Center for Learning and Memory and served as the Inaugural Director of the Center for Theoretical and Computational Neuroscience. Ila Fiete is an HHMI Faculty Scholar. She has been a CIFAR Senior Fellow, a McKnight Scholar, an ONR Young Investigator, an Alfred P. Sloan Foundation Fellow and a Searle Scholar. In 2022, she received the SfN’s Swartz Prize for Theoretical and Computational Neuroscience.
Apart from my science, I love spending time with family. I’m passionate about gardening and restoring native vegetation, as well as cooking, travel, hiking, and food history.
Mara Riley
Administrative Assistant
Mara Riley enjoys a double life as a classical musician and an administrative assistant for the Fiete, Kanwisher, and Tenenbaum Labs at MIT. She joined the Fiete lab in June 2024. She holds a double Master’s degree in Voice and Flute Performance at the New England Conservatory in Boston. She sings with groups such as the Boston Early Music Festival, Emmanuel Music, the Sarasa Ensemble, Aeternum, Nightingale Vocal Ensemble, Colorado Bach Ensemble, Boulder Bach Festival, and the Voces8 US Scholars. As a Baroque flutist, she has performed with BEMF, H+H, and Blue Hill Bach. Website: marariley.com
Mara loves to hike (a recent highlight was a week backpacking in Yosemite!) and can often be found wandering Boston in search of cute dogs.
Caitlin Lienkaemper
Postdoc; Simons Fellow
I am a Swartz postdoctoral fellow for theory in neuroscience, and am interested in geometry, topology, and dynamics in neural codes and neural networks.
I did my PhD with Carina Curto at Penn State, studying geometric constants on neural coding and dynamics of threshold linear networks, then did a postdoc at Boston University working with Gabe Ocker, working on few projects, including how learning does (and doesn’t!) change dynamics in the hippocampus, and how stimulus statistics shape optimal coding in the olfactory system. Outside of work, I love photography, painting, and climbing.
Lakshmi Govindarajan
Postdoc (co-advised with Josh McDermott)
I am interested in studying the role of network dynamics in implementing cortical computations. In the visual domain, my research has focused on understanding the basis of visual “routines” through recurrent neural network models of reentrant processes and, along the way, solutions to the technical challenges that prevent using recurrent models at scale. I am particularly enthusiastic about problems at the interface of perception and cognition, and I build tools to study these at scale in the context of naturalistic tasks. I got my Ph.D. at Brown University under Dr. Thomas Serre’s guidance and my Bachelor’s in Computer Science and Biophysics from National University of Singapore, where I was a Turing Fellow.
Daoyuan Qian
Postdoc (co-advised with Michale Fee)
Daoyuan did his undergraduate studies in theoretical physics from 2017 to 2021 in Cambridge University, where he then continued to do a PhD in protein condensation with Prof. Tuomas P. J. Knowles from 2021 to 2025. He has experience in protein physical chemistry, polymer physics, cell culture, micro-fluidics, confocal microscopy, time-correlated single photon-counting microscopy, differential geometry, reservoir computation, and topology. For post-doctoral research, Daoyuan is interested in various aspects of theoretical neuroscience, including generalisation/modularisation, memory mechanisms, the role of noise, song learning of songbirds, and applications in machine learning.
Hao Zheng
Postdoc (co-advised with Fan Wang)
I am an ICoN postdoctoral fellow in computational neuroscience, broadly interested in the geometry and neural architecture that underpin neural codes and dynamics. I studied theoretical physics at Tsinghua University, where my undergraduate mentor, Michael Zhang, sparked my long-term fascination with the deep connections and mismatches among physics, artificial intelligence, and life. For my PhD at Tsinghua with Luping Shi and Sen Song, I worked on brain-inspired mechanisms for soft feature binding and flexible part–whole representations. My current research extends to the theory of decision-making and emotion, examining how mental disorders such as addiction may emerge from transitions in the underlying neural dynamics. Outside of research, I enjoy weightlifting (three times a week before dinner), playing and watching soccer (a Bayern Munich and German national team fan for 18 years), old-school popping dance, and—perhaps unsurprisingly—regular visits to physical therapy.
Stephan Kim
Postdoc
I am a postdoctoral researcher in the Fiete lab, broadly interested in the intersection of neuroscience and artificial intelligence. In particular, I am interested in studying how humans and animals learn and remember representations, and using these insights to develop better ML/AI algorithms. Prior to joining the Fiete lab, I completed my PhD at Princeton under Prof. Ong, where I conducted transport experiments on condensed matter systems relevant to quantum computing, such as topological superconductors. After a short stint in the ML/AI industry, I decided to return to academia to research topics related to AI. In my free time, I enjoy playing computer games and table tennis or watching various sports.
Jaedong Hwang
Graduate Student
I am a graduate student in the EECS department at MIT. Before that, I completed my MSc degree in ECE advised by Professor Bohyung Han and BS degree in CSE at Seoul National University, mainly focusing on computer vision. My research journey is to reduce the gap between natural and artificial intelligence by discovering what makes humans start to learn or explore such as curiosity and how humans can learn from a small amount of data or coarse-grained data while machines cannot. To do so, I am broadly interested in the intersection of machine learning, neuroscience, and psychology.
Ling Liang Dong
Graduate Student
I am a graduate student in the Brain and Cognitive Sciences department at MIT. I am broadly interested in the intersection between the computational and neurosciences, that is: how can mathematical and computational methods be used to better understand the mind, and how can insights about the mind in turn be used to inform algorithmic and architectural solutions to modern computational challenges? My current focus lies on the cognitive map and how the brain performs abstraction for efficient knowledge representation and flexible inferences.
Previously, I worked on investigating strategies utilizing the unique social roles occupied by robots to elicit social facilitation and improve team dynamics in human-robot teams at the Yale Social Robotics Lab, and on public opinion forecasting as well as analyzing patterns of production and consumption in online news at Microsoft Research New York. More generally, I am interested in the applications of data science for social good, particularly in the fields of education and healthcare.
Adam Joseph Eisen
Graduate Student (co-advised with Earl Miller)
I’m a graduate student in the Brain and Cognitive Sciences department at MIT, co-advised by Earl Miller & Ila Fiete. I’m from Toronto, Canada, and did my undergraduate degree in Applied Mathematics & Computer Engineering at Queen’s University. Currently I’m interested in communication between brain areas, and how this mechanism might underlie cognition and consciousness. To answer this question, I’m using nonlinear dynamics tools to analyze experimental data and performing computational modelling. Prior to joining BCS, I built computer vision algorithms at the solar aerial inspection company Heliolytics and worked on developing machine learning tools to predict disease outcomes from genetics at The Hospital for Sick Children. In my free time, I spend time playing and writing music, getting outside, and cooking.
Ari Liu
Graduate Student
I am a graduate student in the Department of Physics at MIT. Previously I studied physics and psychology at Wesleyan University (CT), where I mostly worked on computational soft matter research. I have long been fascinated by the human brain and cognition, and hoped to investigate the relevant mechanisms using mathematical and computational methods. Therefore, I decided to do research in theoretical neuroscience by joining the Fiete Lab in Fall 2021.
Sunny Duan
Graduate Student
I am a graduate student in the Brain and Cognitive Sciences department at MIT. I am interested in how neural dynamics implement computation within the brain in the context of perception and control. Before joining the Fiete Lab, I studied computer engineering as an undergraduate at the University of Illinois at Urbana Champaign and subsequently worked as a Software Engineer for several years at Google and Deepmind. I’ve worked on various projects ranging from systems engineering for network ASICs to RL for Datacenter cooling. I became interested in neuroscience while studying algorithms for disentangling representations. In my free time, I enjoy running along the Charles and playing tennis.
Bryan Medina
Graduate Student (co-advised with Josh McDermott)
I am a Ph.D. student in Brain and Cognitive Sciences at MIT, where I’m co-advised by Josh McDermott and Ila Fiete. Broadly, I am interested in the interaction between perception and memory for natural quantities, particularly sounds like speech and music. I work on characterizing the representations that underlie recognition memory using various experimental methods and modeling approaches, with goal of understanding why some things are memorable and some are forgettable, why people remember things they did not experience, how our perception is affected by our long term memories, and, ultimately, why human memory is the way it is. Previously, I studied Computer Science, Cognitive Sciences, and Mathematics as an undergraduate at the University of Central Florida. During undergrad, I collaborated with Dr. Rob Kass at Carnegie Mellon University, and with Josh McDermott. In my free time, I enjoy biking, baking, playing instruments like the alto saxophone and bass, and film photography. I’m an avid collector of records and also host a bi-weekly radio show on WMBR, the MIT radio station.
Mitchell Ostrow
Graduate Student
I’m a graduate student in the Department of Brain and Cognitive Sciences. On the methods side, I’m interested in building and applying mathematical tools to better understand the underlying structure of computation in neural networks, both biological and artificial. On the scientific questions side, I’m interested in understanding how neural systems solve cognitive problems such as reasoning and planning.
I did my undergraduate at Yale University, where I majored in statistics & data science as well as neuroscience. Before moving to computational neuroscience in my junior year, I worked in both computational and experimental psychiatry.
Qiyao (Catherine) Liang
Graduate Student
I am a graduate student in the EECS department at MIT. I am generally interested in studying how the biological brain and machine learning models learn efficient representations of knowledge and develop structures that support so. My current focuses include but are not limited to the mechanistic interpretability of deep learning models and discovering biologically plausible rules that enable structural organization in the brain/models to emerge. I am broadly curious about using quantitative tools to investigate topics such as emergence properties in complex systems, intelligence, consciousness, and beyond. Previously I worked on trapped-ion quantum computation as an undergrad at Duke University, where I studied physics and math. In my free time, I enjoy weight-lifting, dancing, drawing, and hanging out with my dogs!
Raymond L. Wang
Graduate Student
I am an amateur dumpling maker in the Fiete Lab. On the side, I am completing a PhD at MIT. I am primarily interested in memory and planning. I am broadly interested at the intersection of neuroscience, machine learning and robotics. Previously I was at UC Berkeley. I really enjoy bowling.
Nathan Cloos
Graduate Student
I’m a PhD student at MIT Brain and Cognitive Sciences, working in computational neuroscience. My research is in brain-inspired modular architectures for efficient learning. Before my PhD, I completed a master’s in Applied Mathematics and Physics at UCLouvain in Belgium. I also worked as a research assistant in Robert Yang’s lab at MIT, and in Omri Barak’s lab at the Technion.
Andrii Zahorodnii
Graduate Student (M.Eng.)
I’m a Master’s of Engineering student at the Brain and Cognitive Sciences department at MIT. Broadly, my research interest is in Science of Intelligence, and how coordinated firing of neurons in brains gives rise to complex behavior. Specifically, lately I’ve been interested in understanding how simple dynamical systems (such as an RNN), when seen as computing architectures, can solve cognitive tasks. Outside of research, I like to travel and teach, compete for MIT in Sport Pistol, and make films.
Affiliates
Eva Yi Xie
Neuroscience PhD Student, Princeton University
I completed my undergrad at MIT with a double major in Mathematics and in AI & Decision-Making. I am now a PhD student at Princeton Neuroscience Institute in pursuit of my interest in cognitive computational neuroscience. Broadly, I think of cognition as a computational process grounded in the basis of neurons, and that we can understand this process through models of neural networks. Under Ila’s mentorship, I study and model how multiple brain regions interact and form a cognitive map in the brain using grid and place cells to support navigation and decision-making.
Undergrads
Patrick Udeh 2021-2023 (now research study coordinator @MGH)
Opalina Vetrichelvan 2022 (now engineer @Meta)
Gabrielle Kaili-May Liu 2022 (now Ph.D. student @Yale)
Keith Murray 2022 (now Ph.D. student @Princeton)
Erdong Guo 2021
Anka Hu 2021
Joy Ma 2021
Anna Rasmussen 2021
Hangdong (Harry) Wang 2021
William Xu 2021
Group Alumni
Sarthak Chandra, Postdoc; Assistant Professor, ICTS India
Laureline Logiaco, Postdoc and Simons Fellow; Assistant Professor, University of Colorado Anschutz School of Medicine
Akhilan Boopathy, Grad student; Research Scientist, Amazon
Federico Claudi, Postdoc; Staff Scientist, Precision Neuroscience.
Mikail Khona, Graduate Student; Research Scientist, NVIDIA
Rylan Schaeffer, Masters student; Grad student, Stanford; Researcher, Google; now: Staff Scientist, Meta.
Abhi Iyer, Graduate student + ICoN Fellow; Grad student, MIT
Sugandha Sharma, Graduate student; Staff Scientist, NVIDIA
Alex Negron, PostBacc; Graduate student, Princeton University
Leo Kozachkov, Postdoc + ICoN Fellow; Assistant Professor, Brown University
Mingye (Christina) Wang Undergrad researcher; Grad student, Columbia.
Aaditya Singh, MEng; Graduate student, UCL
Dounia Mulders, Postdoc.
Mirko Klukas, Postdoc.
Leenoy Meshulam, Postdoc; Swartz Fellow, UWashington; Assistant Professor, Brown University
Manyi Yim, Postdoc; Instructor, SMU; currently in AI industry
Tzuhsuan Ma, Grad Student; Postdoc, HHMI/Janelia
Rishidev Chaudhuri, Postdoc; Assistant Professor, UC Davis
Ingmar Kanitscheider, Postdoc; Research Scientist, OpenAI
Christopher Roth, Grad Student; Graduate student, UT Austin
Berk Gercek Undergrad; Graduate student, University of Geneva
Biraj Pandey, Undergrad; Graduate student, University of Washington
Maxwell Gray, Undergrad; Graduate student, University of Washington
Abhranil Das, Grad Student; Graduate student, UT Austin
Birgit Kriener, Postdoc; Research scientist, University of Oslo, Norway
Kijung Yoon, Grad Student; Associate Professor, Hanyang University, Korea
John Widloski, Grad Student; Postdoctoral researcher, UC Berkeley
Michael Buice, Postdoc; Senior scientist, Allen Institute
Yongseok Yoo, Grad Student; Assistant Professor, Incheon National University, Korea
Abhinav Singh, Postdoc; Data scientist, Peak, UK
Daniel Robles Llana, Postdoc; Postdoc, University of Geneva
Ila Varma, Undergrad; Assistant Professor, UC San Diego
Prashant Joshi, Postdoc; Head, Artificial Intelligence and Machine Learning group, Fractal Analytics, India
Ni Ji, Undergrad; Principal Investigator/Faculty, Chinese Institute for Brain Research
Peter Welinder Undergrad; VP, OpenAI
The Fiete Lab @ MIT 