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 ]
Graduate Student, co-advised by Tobias Bollenbach
Predicting responses of organisms in different environments is a long-standing goal. In my project I combine experimental and theoretical approaches to study the bacterial responses to the combinations of antibiotics. In particular, I use well established “growth-laws” together with microscopic kinetics of antibiotic transport and binding to predict quantitative features of the experimentally observed dose-response curves for translation inhibitors and their combinations. On the experimental end, I use genetical perturbations that change model parameters in predictable ways thus enabling verification of model predictions.
Graduate Student, co-advised by Calin Guet
Which phenotypes can be realized by evolution is determined by the biological and physical constraints acting on the regulatory networks. In my project I study the effect of regulatory network topology on the distribution of mutational effects and evolutionary accessibility of dynamical phenotypes. I hope to make the evolutionary connection between the documented interesting dynamical properties of the regulatory networks, and the regulatory genotype. Understanding the biophysical constraints posed by the topology of the regulatory network, and through it the genotype-phenotype map for a dynamical phenotype, would form a basis to infer how dynamical properties in a cell can evolve.
Graduate Student, co-advised by Nick Barton
Mutations can affect the expression of a gene either directly (e.g. mutations in its promoter region) or indirectly, by first perturbing other genes upstream in a regulatory network. We can see many such indirect effects in the data as trans-eQTLs. I study how the properties of the regulatory network shape genetic variation in expression levels of many genes across a population. In particular, I am interested in what the network needs to be like for the indirect/trans effects to contribute substantially to expresion variation. To do this, I use simple biophysics-inspired models of gene regulation and genotype + expression data analysis.
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.
The question encapsulating my research interests is that of the relation between the properties of biophysical organization and information processing of biological sensory systems. Currently, my work focuses on the auditory system. Applying the tools and concepts of information and statistical learning theories, I study how various structures in the auditory periphery are adapted to encode and transmit information to the brain efficiently. On a more theoretical side, I am developing a mathematical framework for calculating the responses of dynamical systems described by partially observed Markov processes. These are the underlying mathematical models of diverse phenomena related to the processing of biological information, e.g., gene regulation and neurotransmission.
I joined the group as an IST Plus fellow in October 2018. Before that I was a postdoc at MIT Brain and Cognitive Sciences Department, and got my PhD at the Max-Planck Institute for Mathematics in the Sciences. In my work I try to understand fundamental limits and principles which govern the function of sensory systems. To that end I analyze the statistical structure of natural stimuli, develop optimal processing strategies which might be approximated by biological systems and verify theoretical predictions through experimental data analysis. To read more about my work please see my homepage.
I joined the group in May 2019 as an ISTplus fellow, moving from Boston University, where I was postdoc at the Department of Physics. My research interests fall into the realm of theoretical and computational statistical physics, with a particular inclination towards non-equilibrium phenomena and emergent collective behaviors in biological, ecological and physiological systems. Recently I have been focusing on criticality in brain dynamics and non-equilibrium effects in homeostatic sleep regulation, and in developing a holistic approach to human physiology that aims to associate distinct conditions with networks of interactions inferred from synchronous recordings of several organs across the human body and predict their evolution in response to perturbations (e.g. organ failure, medical treatments). I approach problems at the interface of physics and life sciences combining data analysis and computational modeling, and make use of concepts and methods from statistical mechanics, non-linear dynamics and theory of stochastic processes, with the objective of explaining large scale collective behaviors in term of key properties that characterize basic constituents and their interactions.
Former group members
Anna M Andersson, postdoc, 2019 starting as a data scientist at Equiniti
Katarína Boďová, postdoc, cosupervised with Nick Barton; 2017 starting as Assistant Professor at the Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava
Vicent Botella-Soler, postdoc, 2016 starting as freelance data analysis consultant, now at ForwardKeys
Remy Chait, IST Fellow, cosupervised with Calin Guet, 2019 starting as Lecturer in the biosciences department, University of Exeter
Matthew Chalk, postdoc, 2018 starting as INSERM Researcher at Institute of Vision, Paris
Sarah Anhala Cepeda-Humerez, PhD student (defended Feb 27, 2019)
Jan Humplik, PhD student, 2019/2020 starting at DeepMind, London
Daniele De Martino, postdoc, 2019 starting as Postdoc at Jozsef Stefan Institute, Ljubljana; Winter 2019 starting as Assistant Professor at Basque Center for Biophysics
Tamar Friedlander, IST Fellow, 2017 starting as Assistant Professor at Hebrew University of Jerusalem
Aditya Gilra, IST Fellow, 2020 starting as Lecturer at Department of Computer Science, University of Sheffield
Anna Levina, IST Fellow, 2017 starting as Group Leader at University of Tübingen, recipient of Sofja Kovalevskaja Award (2017)
Georg Martius, IST Fellow, 2017 starting as Max Planck Group Leader at MPI for Biological Cybernetics
Gabriel Mitchell, postdoc
Roshan Prizak, PhD student, cosupervised with Nick Barton (defended Jan 14, 2019), since 2019 postdoc with Lennart Hilbert at KIT Karlsruhe
Georg Rieckh, PhD student (defended June 28, 2016); 2016 starting as postdoc with Sergey Kryazhimskiy at UC San Diego, now at Accenture Vienna
Jakob Ruess, IST Fellow, 2016 starting as INRIA Palaiseau Researcher at Institut Pasteur
Cristina Savin, IST Fellow, 2017 starting as Assistant Professor at NYU in Neuroscience and Data Science
Murat Tugrul, PhD student, cosupervised with Nick Barton (defended June 27, 2016); 2016 starting as postdoc at St. Anna Kinderspital, Vienna