I joined IST Austria in 2011. Previously I was a postdoc with Vijay Balasubramanian and Phil Nelson at University of Pennsylvania, working on the theory of neural coding and specifically exploring population coding and adaptation in the retina. I finished my PhD at Princeton with Bill Bialek and Curt Callan in 2007, studying how biological networks can reliably transmit and process information in the presence of intrinsic noise and corrupted signals. I am broadly interested in uncovering general principles that underlie efficient biological computation.
[ CV pdf ]
I am interested in information and signal processing in (noisy) biological systems with a special focus on gene regulation and neural networks. Although I mainly take a theoretical approach, I enjoy the close collaboration with experimental groups.
I am interested in understanding the dynamics of communication in biological systems. In particular on signal transmission and decision making in biochemical networks; with special focus in time-varying signals.
I joined IST as a graduate student in 2013. Previously I worked in the group of Martin Nowak at Harvard University focusing on problems of evolution of infectious diseases in finite populations. Now I am interested in more general questions about organization and information processing in complex systems. In particular, using data-driven approaches, I am trying to understand how local interactions among fish give rise to the collective behavior they exhibit in groups.
PhD, Physics (Universitat de València)
I am generally interested in nonlinear and complex systems dynamics. This interest has taken me to puddle in different fields such as the dynamics of piecewise continuous chaotic maps, adaptive complex networks or time series analysis in neuroscience. My research at IST concerns the processing of visual information in the retina.
Anna M Andersson
PhD, Physics (Niels Bohr Institute)
The question that fascinates me is how bacterial populations deal with uncertainty. A bacterial population makes chemical computations that determine what genes are expressed in single cells and in the population. The outcome of these noisy computations has to convey information about the surrounding environment, a seemingly daunting task. I study this theoretically working with Gasper but also collaborate with Tobias Bergmiller in Calin Guet’s group where we ask these question experimentally in relation to antibiotic resistance.
PhD, Computational Neuroscience (Goethe University, Frankfurt am Main)
I joined the lab as IST fellow in November 2013. Previously, I was a postdoc at the University of Cambridge in the lab of Mate Lengyel and a PhD student at the Frankfurt Institute for Advanced Studies in the lab of Jochen Triesch. In general terms, my research focuses on learning and memory. I use a combination of theoretical modelling, computer simulations and data analysis to explain how different low-level properties of neural circuits support these functions. For further details, please refer to my homepage.
PhD, Biology (Georgia Institute of Technology)
I am interested in organization, dynamics and computation in biological systems. I joined IST in October 2013 and am currently working on developing bottom up models of information processing and collective decision making in fish groups.
PhD, Physics (AMOLF, Amsterdam)
I am interested in mechanisms that make information processing in biological systems robust, with a special focus on spatial aspects. My current research topic is the embryonic development of the fruit fly. Here different body parts are specified by local establishment of confined protein expression patterns. I am studying whether and how diffusive coupling and genetic cross-interactions can enhance information transmission via this process, and under which circumstances this works best. I employ methods from statistical physics, information theory, and spatially resolved stochastic simulations.
PhD (ETH Zurich)
I joined the lab as an IST fellow in November 2014. My research is centered around the stochastic dynamics of biochemical reaction networks. I work mostly on the theoretical side where I focus on developing methods for optimal experiment design, Bayesian parameter inference and model selection for continuous-time Markov chains. In collaborations with experimental groups, I also apply these methods to real systems with the goal of gaining a mechanistic understanding of the underlying biochemical processes.
PhD (University of Goettingen)
I joined the IST in February 2015 after being a postdoc at the Max Planck Institute for Mathematics in the Sciences in Leipzig. I am interested in autonomous learning, that is how an embodied agent can determine what to learn, how to learn, and how to judge the learning success. I am using information theory and dynamical systems theory to formulate generic intrinsic motivations that lead to coherent behavior exploration – much like playful behavior. Furthermore I develop methods to quantify autonomous behavior in robots and animals using information theory and manifold learning.
Vijay Balasubramanian, University of Pennsylvania →
William Bialek, Princeton University →
Michael Berry 2nd, Princeton University →
Thomas Gregor, Princeton University →
Ann Hermundstad, University of Pennsylvania →
Olivier Marre, Vision Institute →
Thierry Mora, Ecole Normale Superiore →
Phil Nelson, University of Pennsylvania →
Elad Schneidman, Weizmann Institute of Science →
Ronen Segev, Ben Gurion University →
Jonathan Victor, Weill-Cornell Medical College →
Aleksandra Walczak, Ecole Normale Superiore →