CV of Konrad Paul Körding


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CV of Konrad Paul Körding

  1. 1. CV of Konrad Paul Körding<br />Assistant Professor at Physiology as well as Physical Medicine and Rehabilitation, associated with the Rehabilitation Institute of Chicago <br />Title: PhD ETH <br />Married to Ioana Marinescu Address: Physiology and PM and R, Rehabilitation Institute of Chicago, Northwestern University, 345 E Superior Street, 60611 Chicago, IL, USATel: 773-7826327E-mail:<br /><br />Scientific education<br />2005-2006Heisenberg fellow, at MIT, working with Josh Tenenbaum on the application of ideas from cognitive science to motor learning 2004-2005Postdoc, at MIT in the group of Josh Tenenbaum, learning state of the art machine learning, hierarchical Bayesian models 2002-2004Postdoc, at UCL London, addressing learning and optimality in the motor system with Prof. Wolpert2001-2002Postdoc, at the Collegium Helveticum, Helveticum, studying philosophy and philosophy of science and the statistics of natural scenes 2001PhD Thesis, at the ETH Zurich, " Optimization and Learning: from microscopic cell properties to natural videos" 1997Diploma-thesis, at the ETH Zurich, " On the purpose of a backpropagating action potential." at ETH Zürich 1996-1997Studying Physics, at the ETH Zürich, Switzerland1993-1996Studying Physics, at the Uni. Heidelberg, Germany1993Abitur, at the Alten Kurfürstlichen Gymnasium in Bensheim, Germany <br />Grants and Awards <br />2006NSF/NIH Collaborative Research in Computational Neuroscience with Emo Todorov and Reza Shadmehr (PI), grant is to study Bayesian approaches to motor control2005Heisenberg stipend by the German Science Foundation, to explore links between cognitive science and neuroscience. 2001-2002Postgraduate Support: Collegiate of Collegium Helveticum: " Für den Dialog der Wissenschaften." , to learn about sociology and philosophy of science1997-2001Graduate Support: Boehringer Ingelheim Fonds1993-1997Undergraduate Support: Studienstiftung des Deutschen Volkes (since 1994).1993, 1994Successful participation in the German young scientist competition, “Jugend Forscht”, Price for interdisciplinary work<br />Workshops organized <br />Bayesian approaches to motor control, Neural Control of Movement 2008, together with Max Berniker<br />Asking why: normative models in neuroscience, Cosyne 2007, together with Alan Stocker <br />Bayesian approaches to Sensory and Motor processing, Cosyne 2005 <br />Learning of invariant representations: a Workshop at NIPS 2002 together with Bruno Olshausen<br />Teaching Experience<br />Leading the “Normative models of brain function” winter course in Portugal, 2008<br />Teaching at the Graduate Summer School: Probabilistic Models of Cognition: The Mathematics of Mind, IPAM, UCLA 2007<br />Teaching at the NeuroIT and Neuroengineering Summer School, Delmenhorst, Germany 2007<br />Teaching at the International Spring School on Computational Neurobiology in Shanghai 2007<br />One week school course for high-school students with Katharina Spalek on Seeing and Naming, from perception to image naming <br />Three day school course for high-school students together with Wolfgang Einhäuser on Fooling the Brain to understand it : Optical Illusions<br />Professional Appointments <br />Assistant Editor for Experimental Brain Research<br />Participation in Study Sections for the National Science Foundation programs “Robust Intelligence” and “Collaborative Research in Computational Neuroscience”<br />Reviewer for the Israeli Science Foundation and the Swiss National Funds <br />Reviewer for Behavioral and Brain Sciences, the Cognitive Science Conference, Cognitive Science, Experimental Brain Research, Human Movement Science, Journal of Motor Behavior, Journal of Neurophysiology, Journal of Neuroscience, Journal of Vision, Nature Neuroscience, Neural Computation, the Neural Information Processing Systems Conference, Physics Letters A, PLOS Computational Biology, Rheumatology, Science, Transactions in Biomedical Engineering, Trends in Cognitive Science, Visual Neuroscience<br />Peer Reviewed Papers<br />In press<br />Stevenson, IH, Rebesco, JM, Miller, LE  and Kording, KP (in press),Inferring the functional connections between neurons, Current opinionin neurobiology<br />Stevenson IH, Rebesco JM, Hatsopoulos NG, Haga Z, Miller LE, andKörding KP. (in press),Bayesian inference of functional connectivityand network structure from spikes IEEE Transactions on Neural Systemsand Rehabilitation Engineering<br />Dam, G. and  Kording, KP, (in press) Exploration and exploitation inmovement learning, Cognitive Science<br />Schummers, J Cronin, B , Wimmer, K, Stimberg, M , Martin, R, Obermayer, K , Kording, K and Sur, M (in press) Dynamics of orientation tuning in cat V1 neurons depend on location within layers and orientation maps, Frontiers in Neuroscience <br />2008<br />Berniker, M and Körding, KP, (2008) Motor Adaptation: Estimating the sources of errors, Nature Neuroscience 11, 1454 - 1461 <br />Wei, K and Kording, KP (2008), Relevance estimation in motoradaptation, Journal of Neurophysiology doi:10.1152/jn.90545.2008<br />Ingram JN, Körding KP, Howard IS, Wolpert DM (2008) The statistics ofnatural hand movements. Experimental Brain Research 188:223-236.<br />2007<br />Kording KP (2007) Decision theory: what should the nervous system do? , Review, science, 318: 606-610<br />Kording, KP, Beierholm, U, Ma, WJ, Quartz, S, Tenenbaum, J and Shams, L, Causal (in press) Inference in multisensory perception <br />Kording, KP, (in press) Decision theory, what “should” the nervous system do, invited review, science<br />Kording, KP, Tenenbaum, JB and Shadmehr, R.. The dynamics of memory are the consequence of optimal adaptation to a changing body (2007), Nature Neuroscience 10, 779<br />2006<br />Kording, K., Tenenbaum, J. B., and Shadmehr, R. Multiple timescales and uncertainty in motor adaptation. (2006). Advances in Neural Information Processing Systems 19, eds. Scholkopf, B, Platt, J and Hoffman, T, p 745-752. <br />Kording, K. and Tenenbaum, J. B. Causal inference in sensorimotor integration. (2006). Advances in Neural Information Processing Systems 19, eds. Scholkopf, B, Platt, J and Hoffman, T, p 737-744. <br />Körding and Wolpert, D. (2006) Bayesian decision theory in sensorimotor control. Trends in Cognitive Sciences (TICS) 10(7) 320-326 <br />Purver, M., Kording, K. P., Griffiths, T. L., & Tenenbaum, J. B. (2006) Unsupervised topic modelling for multi-party spoken discourse. Proceedings of Coling/ACL 2006.<br />2004<br />Körding, KP, Ku, SP and Wolpert, D. (2004) Bayesian Integration in force estimation J Neurophysiol 92(5):3161-5 <br />Hafner, VV. , Fend, M. , König, P. and Körding, KP. (2004) Predicting Properties of the Rat Somatosensory System by Sparse Coding, Neural Information Processing Letters and Reviews, 4(1): 11-18 <br />Körding, KP., Fukunaga, I., Howard, IS., Ingram, J. and Wolpert, D. (2004) A neuroeconomics approach to measuring human loss functions, PLOS Biology, In press <br />Körding, KP. and Wolpert, D. (2004) The loss function of sensorimotor learning, Proceedings of the National Academy of Sciences 101:9839-42 <br />Körding, KP. and Wolpert, D. (2004) Bayesian Integration in Sensorimotor Learning, Nature 427:244-247 <br />Körding, KP, Kayser, C., Einhäuser, W. and König,P., How are complex cell properties adapted to the statistics of natural scenes? Journal of Neurophysiology 91(1):206-212<br />Körding, KP. and Wolpert, D. (2003) Bayesian Integration with Multimodal priors, NIPS <br />Betsch, B, Einhäuser, W., Körding, KP and König, P. (2003) Biological Cybernetics, in press <br />2003<br />Hafner, V. V., Fend, M., Lungarella, M., Pfeifer, R., König, P., Körding, K. P. (2003), Optimal coding for naturally occurring whisker deflections, Proceedings of the Joint International Conference on Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP), Springer Lecture Notes in Computer Science, pp. 805-812, ISSN 0302-9743, ISBN 3-540-40409-2, Istanbul<br />Einhäuser, W., Kayser, C., Körding, K.P. and König,P. (2003) Learning distinct and complementary feature-selectivities from natural colour videos. Reviews in the Neurosciences 14, p. 43-52, 2003. <br />Klein, D.J., König, P. and Körding, K.P. (2003) Sparse spectrotemporal coding of sounds. EURASIP Journal of Applied Signal Processing. <br />Körding, K.P., Kayser, C. and König, P. (2003) On the choice of a sparse prior, Reviews in the Neurosciences 14, p. 53-62, 2003 <br />Kayser C, Körding KP, König P. (2003). Learning the nonlinearity of neurons from natural visual stimuli. Neural Computation. 15(8) 1751-1759. <br />2002<br />Einhäuser,W. Kayser,C. Körding K.P. and König,P. (2002) Learning Multiple Feature Representations from Natural Image Sequences Artificial Neural Networks - ICANN, Springer Verlag Berlin Heidelberg New York. <br />Einhäuser, W., Kayser, C. , König, P. and Körding, K.P., (2002) Learning the invariance properties of complex cells from natural stimuli. Eur J Neurosci 15(3):475-86 <br />Konrad P. Körding, Peter König, and David J. Klein (2002) Learning of sparse auditory receptive fields International Joint Conference on Neural Networks <br />2001<br />Körding, K.P., Kayser C., Betsch, B. and König, P., (2001) Non contact eye-tracking on cats. J Neurosci Methods. 110:103-111 <br />Körding, K.P. and König, P., (2001) A spike based learning rule for the generation of invariant representations. Journal of Physiology Paris 94:539-548 <br />Körding, K.P. and König,P., (2001) Neurons with two sites of synaptic integration learn invariant representations. Neural Computation 13:2823-2849 <br />Kayser, C., Einhäuser, W., Dümmer, O., König, P. and Körding, K.P., (2001) Extracting slow subspaces from natural videos leads to complex cells. International conference on artificial neural networks<br />Körding, K.P. and König ,P. , (2001) Supervised and unsupervised learning with two sites of synaptic integration. Journal of Computational Neuroscience 11:207-215 <br />2000<br />Körding, K.P. and König, P., (2000) Two sites of synaptic integration: Relevant for learning International Joint Conference on Neural Networks<br />Körding, K.P. and König,P.,(2000) A learning rule for local decorrelation and dynamic recruitement Neural Networks 13:1-9 <br />Siegel,M. Körding,K.P. and König, P. (2000) Integrating top-down and bottom-up sensory processing by somato-dendritic interatctions J. Comp. Neurosci 8:161-173 <br />Konrad P. Körding and Peter König, (2000) Learning with two sites of synaptic integration Network: Computation in Neural Systems 11:25-39 <br />Invited Talks<br />Computational Workshop on Cue combination, Germany 2008, Causal inference in cue combination<br />Motor economics, Caltech, 2008<br />Symposium Computational Neuroscience BCCN, 2008, Normative models of brain function<br />Understanding Complex Systems symposium 2008<br />Dutch Neuroscience Meeting 2008, Nonlinear processes in motor adaptation<br />VSS conference 2008, Naples, FL, “Causal inference in cue combination”<br />ITMAT Symposium 2008, University of Pennsylvania, Decision theory in human behavior<br />Columbia University 2008, Motor Adaptation<br />Cosyne Conference 2008, Inference of functional connectivity using Bayesian methods<br />Marquette University 2008, Estimating the sources of movement errors<br />IPAM, UCLA 2007, Decision making in the motor system<br />IPAM, UCLA 2007, Causal inference in sensorimotor integration<br />Tuebingen, Germany 2007, Adaptation in the visuomotor system<br />Delmenhorst, Germany 2007, Introduction to decision theory<br />Shanghai, 2007, Normative models of motor Control: why do we move the way we do<br />NYU, 2006, Causal Inference in Cue Combination<br />Giessen, 2006, The dynamics of motor learning and memory are the result of optimal adaptation to a changing body<br />Northwestern, 2006, Human movement as an optimal decision process<br />Cornell, 2006, Human movement as an optimal decision process<br />Yale, 2006, Human movement as an optimal decision process<br />Brown, 2006, Human movement as an optimal decision process<br />Paris, 2005, Calcul bayesien dans le systeme sensorimoteur<br />University of Chicago, 2005, Motor control as a decision problem <br />Johns Hopkins, 2005, Probabilities and Utilities: deciding how to move<br />Cosyne Workshop, 2005, Bayesian Methods in Sensory and Motor processing <br />Harvard, 2005, Motor economics: deciding how to move<br />Berkeley, 2005, Motor economics: deciding how to move<br />Cornell, 2004, Optimal processing in sensorimotor integration <br />Institute for cognitive research Osnabrück, 2004, What is optimal in sensorimotor integration<br />Functional Imaging Lab, London, 2004, Optimal statistical processing in the sensorimotor system<br />Nijmegen institute for cognition and information, 2004, Probabilistic processing in sensorimotor integration<br />Neurovision meeting Bochum, 2004, Bayesian Processing in the human sensorimotor system<br />MIT, Cambridge, 2004, Optimality criteria for visual representations and sensorimotor integration <br />Cold Spring Harbour Labs, 2004, Towards a Bayesian Nose<br />Brain and Mind Institute Lausanne, 2003, Optimality in visual representations and sensorimotor integration<br />Institute of Theoretical Biology Berlin, 2003, Bayesian integration in sensorimotor learning<br />GATSBY, London, 2003, The sensorimotor system uses the Bayes rule <br />Cambridge, 2003, Bayesian integration in the sensorimotor system <br />Plymouth, 2003,Learning from the real world - one algorithm for visual and auditory stimuli. <br />Oldenburg, 2003,Sparse Coding of speech data predicts properties of the auditory system <br />GATSBY, London, 2003, Learning hierarchical representations from videos of natural scenes<br />Center for Neuroscience, Davis CA, 2002, Complex Cells, A question of time <br />Asilomar, 2002, Complex Cells, optimality to natural scenes <br />Wolpert Lab 2002, Optimality of Complex Cells<br />Seung Lab MIT, 2000, Learning Invariant Representations <br />Brown University, 2000, Invariant Representations and the Binding Problem <br />Cold Spring Harbor Lab , 2000, Complex Cells emerge from natural Videos <br />Banbury Meeting : Statistics of Natural Scenes , 2000, What cats see and what networks can learn from this <br />Heidelberg Max Planck Institute for Medical Research, 2000, The significance of two sites of synaptic integration <br />GATSBY and University College London, 2000, Physiologically realistic mechanisms for learning <br />ITB Berlin,1999, Significance of two sites of synaptic integration <br />