Ila Fiete is an Associate Professor in the Department of Neuroscience and the Institute for Neuroscience, at UT Austin. She obtained her Ph.D. at Harvard under the guidance of Sebastian Seung at MIT. Her postdoctoral work was at the Kavli Institute for Theoretical Physics at Santa Barbara, and at Caltech, where she was a Broad Fellow. Ila Fiete is a fellow in the Center for Learning and Memory, a McKnight Scholar, and an ONR Young Investigator. She has been an Alfred P. Sloan Foundation Fellow and a Searle Scholar.
Birgit Kriener, postdoctoral fellow
My background is theoretical physics and I did my diploma work in the Statistical Physics and Quantitative Biology group headed by Michael Laessig at Cologne University. I then moved to Freiburg University to obtain a Dr rer net (PhD) in the field of computational neuroscience in Ad Aertsen's group. After finishing my thesis in 2007, I joined the Network Dynamics group headed by Marc Timme at the Max Planck Institute of Dynamics and Self-Organization in Goettingen, and in 2010 I became a member of Gaute Einevoll's Computational Neuroscience group at the Norwegian University of Life Sciences. My research so far was focused on the collective dynamics of spiking neuronal network models inspired for example by the barrel cortex and the developing hippocampus, but I also studied more abstract properties of spatially structured networks and balanced random networks. My recent work deals with coding and decoding in neuronal networks, in particular the role of spiking neuron models versus rate models in the presence of noise and correlations.
Rishidev Chaudhuri, postdoctoral fellow
I joined the Fiete lab in August 2014. Before that I was a graduate student and then post-doc with Xiao-Jing Wang, first at Yale and then at NYU, where I built models of the large-scale dynamical organization of the cortex and studied related theoretical questions. My research interests lie at the intersection of neuroscience and applied mathematics, and at the moment I'm studying the computational and representational properties of dynamical systems, the representation of space in the hippocampus and entorhinal cortex, and the use of random networks for modeling cortical dynamics. Website
Ingmar Kanitscheider, postdoctoral fellow
After obtaining my PhD in theoretical physics in 2009 at the University of Amsterdam I was a postdoc in the lab of Alexandre Pouget, first at the University of Rochester and later at the University of Geneva in Switzerland. I joined the Center for Learning and Memory in August 2014. My work deals with a broad range of issues around probabilistic computation and representation in neurons, and the impact of noise correlations on information. I'm also interested in probabilistic algorithms of navigation and map-building.
Abhranil Das, graduate student
I finished an integrated Masters in Physics at the Indian Institute of Science Education and Research, Kolkata, in 2013. My masters thesis was on the Thermal Ratchets system that transports diffusive particles. I am currently a PhD student at the Department of Physics at UT Austin, and have been working in Dr Fiete's group since June 2015. My interests lie in theoretical and computational investigations of dynamical and statistical systems. My interests outside academics include photography, web development and design, and long-distance running.
Tzuhsuan (Maz) Ma, graduate student
I am a graduate student in Physics at UT Austin. My previous research can be categorized as photonics, plasmonics, and optoelectronics. Following the discovery of topological insulators in electronic systems, I helped to bring the concept into the realm of photonics and develop photonic topological insulators. I have a broad interest in physics. The field outside of photonics that I have mainly touched upon includes condensed matter physics and quantum optics. In June 2016, I decided to join Dr. Fiete’s lab and started working on computational and theoretical neuroscience. My current project is to study the dynamics of theta phase precession of grid cells and place cells, and to build and understand the mechanistic network model underlies it.
Biraj Pandey, undergraduate student
Berk Gercek, undergraduate student
KiJung Yoon, graduate student
I am a graduate student in the Department of Electrical and Computer Engineering at The University of Texas at Austin. Prior to that I completed my Bachelors (2008) in Electrical Engineering at The Korea Advanced Institute of Science and Technology (KAIST). Now I work in the Center for learning and memory under my advisor Dr. Ila Fiete. I have a wide range of interests in the application of statistical machine learning to neural coding problems. Recent work focuses on investigating predictions of the continuous attractor model based on simultaneously recorded grid cells. Website
Kijung is now a postdoc at Rice University with Xaq Pitkow and Dora Angelaki.
John Widloski, graduate student
I am a PhD student in the physics department at UT Austin. I received a B.S. in physics (2008) at Georgia Tech, working primarily under Roman Grigoriev investigating micro-scale fluid mixing. At UT Austin, following work on Laplacian growth under Harry Swinney and Mike Marder, I found a new home across the street in the Center for Learning and Memory in the Fiete lab. My current work involves dynamic modeling of grid cells with special emphasis on simulating the emergence of a network with grid cell properties from 'scratch'.
John is now a postdoctoral fellow in David Foster's group at Johns Hopkins University in Baltimore.
Yongseok Yoo, graduate student
I am a Ph. D. Student in Electrical and Computer Engineering. I received M.S. and B.S. from Seoul National University, South Korea. Prior to the Ph. D. program, I worked at Samsung Advanced Institute of Technology and researched on computer vision. My research interests include machine learning and computational neuroscience. My current project is to analyze "information processing mechanism" between grid cells and place cells in the light of the Information Theory. It is my privilege to be a Fulbright scholar. The program supports my graduate study and also provides valuable opportunities to interact with Fulbrighters from all over the world. I love to share ideas and cultures with them and treasure their visits in the spirit of "Mi casa es su casa." Website
Yongseok is an Assistant Professor in the department of Computer & Information Communication at Hongik University in South Korea.
O. Ozan Koyluoglu, postdoctoral fellow (affiliate)
I am a Postdoctoral Fellow with Dr. Sriram Vishwanath in the Laboratory for Informatics, Networks, and Communications (LiNC) at the Wireless Networking and Communications Group (WNCG). I am also affiliated with the Fiete Lab and the Neural Coding and Computation Lab in Center for Learning and Memory (CLM), Center for Perceptual Systems (CPS), and Institute for Neuroscience (INS), and working with Dr. Ila R. Fiete and Dr. Jonathan W. Pillow. Website
Ozan is now an assistant professor at the University of Arizona.
Daniel Robles-Llana, postdoctoral fellow
I am trained as a theoretical physicist. I got my PhD in string theory from Stony Brook University and did postdoctoral work at Utrecht University and the Weizmann Institute of Science. While I am still fascinated by particle physics, I have recently decided to take further my comparable, long-standing interests in computational neuroscience. I am studying the dynamics of neural integrators and memory systems, and problems of structure formation in the brain.
Daniel is now a postdoc in the lab of Alex Pouget at the University of Geneva.
Abhinav Singh, postdoctoral fellow
I am interested in the 'neural code', keeping in mind that neurons are noisy and connected to each other. Previously, I worked with Nick lesica at LMU Munich and UCL to analyze connections within neural circuits. As a graduate student at Georgia Tech, I studied the dynamics of the Schelling model and inverted biomass pyramids.
Abhinav is currently a postdoctoral fellow at the University of Sheffield, UK.
Michael Buice, postdoctoral fellow
A theoretical physicist with a background in non-equilibrium statistical mechanics, obtained during a PhD in Physics at the University of Chicago with Jack Cowan in which I extended the Wilson-Cowan neural network equations to include the effects of fluctuations, following a postdoc at the National Institutes of Health in the Laboratory of Biological Modeling with Carson C. Chow in which I constructed a framework for describing the statistical mechanics of dynamical systems, I came to UT Austin, joining the Fiete group, in order to explore the connections between information and dynamics, specifically as they regard the brain and nervous system, while, when away from scientific work, continuing my training in Aikido and Yagyu Shinkage-Ryu Heiho and remaining a casual hobbyist in monosentential biographies.
Michael is currently a senior scientist at the Allen Brain Institute.
Travis Tomlinson, summer research assistant
Travis will be teaching Math in High Schools.
Sameet Sreenivasan, postdoctoral fellow
My primary interest lies in understanding the properties of neural systems at a network level, and I am presently working on a neural circuit which performs computations that are essential to rodent spatial navigation. Prior to my current position, I was a postdoc at the Center for Complex Network Research at the University of Notre Dame, where I worked on understanding how functional modules arise in networked systems. Still prior, I received a PhD in physics from Boston University for my dissertation research on the application of statistical physics to random graph models of networks.
Sameet is currently a senior scientist in the social and cognitive networks group at Rensselaer Polytechnic Institute.
Daniel Chen, summer undergraduate researcher
Daniel continued as undergraduate at Caltech after working in the lab. He is currently a software engineer in the bay area.
Kevin Hannay, summer undergraduate researcher
Kevin joined the Mathematics Department at the University of Michigan as a graduate student, where he is currently pursuing a Ph.D..