About me
Research staff member, biometaphorical computing
Research lab: Watson Research Center (Yorktown)
Guillermo Cecchi received an education in Physics (MSc, University of La Plata, Argentina, 1991), Physics and Biology (PhD, The Rockefeller University, 1994-1999), and Imaging in Psychiatry (Postdoctoral Fellow, Cornell University 2000-2001). He has been interested in diverse aspects of theoretical biology, including Brownian transport, molecular computation, spike reliability in neurons, song production and representation in songbirds, statistics of natural images and visual perception, statistics of natural language, and brain imaging. In 2001 he joined IBM Research to be part of the Biometaphorical Computing project, where he has been working on computational approaches to global brain function. Currently, his research is focused in a number of topics:
--Machine learning applications to the study of fMRI signals.
--Statistical network theory approaches to understand the topological structure of complex biological networks.
--Network-based approaches to the characterization of dysfunctional brain states, with an emphasis on schizophrenia.
--Large-scale structure of cortical visual maps, and its relationship with self-organized models of map formation and the statistics of visual inputs.
--Computational models of adult neurogenesis.
--Learning and dynamics in oscillatory neural networks.
Selected Publications
-"Self-tuned critical networks", Physical Review Letters (2009).
-"High throughput image analysis and reconstruction", Artech House (2009)
-"Ordered cyclic motifs contribute to dynamic stability in biological and engineered networks", PNAS (2008)
-“Unsupervised segmentation with dynamical units”, IEEE Transactions on Neural Networks (2008).
-“Scale-free brain functional networks”, Physical Review Letters (2005).
-“Global properties of the Wordnet lexicon”, PNAS (2002).
-“Unsupervised learning and adaptation in a model of adult neurogenesis”, Journal of Computational Neuroscience (2001).
-“Simple motor gestures for birdsong”, Physical Review Letters (2001).
-“On a common circle: natural scenes and Gestalt rules”, PNAS (2001).
-“Noise in neurons is message-dependent”, PNAS (2000).
-“Toward a Song Code: Syllabic Representation in the Canary Brain”, Neuron (1998).
-“Efficiency of DNA Replication in the Polymerase Chain Reaction”, PNAS (1996).
-“Negative Resistance and Rectification in Brownian Transport”, Physical Review Letters (1996).
Last updated 29 May 2009