Plenary SPEAKERS
Rita Casadio
Gérard Dreyfus
Manuel Samuelides

 

Professor Rita Casadio
Department of Biology
University of Bologna, Italy
 
Homepage
Email: casadio@kaiser.alma.unibo.it
Abstract of talk


RC is full professor of Biophysics at the University of Bologna, Italy. She has been working mainly in the fields of membrane and protein Biophysics (particularly with bacteriorhodopsin from Halobacterium Halobium and F1F0 ATPases from mesophilic organisms), both experimentally and theoretically, including mechanisms of energy conservation in bacteria. Presently she is interested in computer modelling of relevant biological processes, such as protein folding and modelling and her researches are devoted to different aspects of protein modelling, including prediction of secondary and tertiary structures with neural networks, hidden Markov models and genetic algorithms, molecular docking and drug design, see http://lipid.biocomp.unibo.it. One major field of research is the implementation and developments of tools out of machine-learning approaches for the prediction of secondary and tertiary structure of proteins from their sequences, particularly of membrane proteins and their transmembrane topology. Projects focus on the prediction of contact maps, of protein-protein and protein-DNA interaction, of the bonding state of cysteines and their topology. RC is the author of over 110 scientific papers, one international patent, and presented her work at several (over 200) national and international meeting and (see CV). Since 1995 Rita Casadio is the group leader of the Biocomputing Unit of the University of Bologna. Research interests focus on different aspects of protein sequence analysis, mainly the development and implementation of predictive algorithms based on methods out of machine learning approaches. The results of these works have been selected several times for presentation at the International Forum of Bioinformatics “Intelligent Systems for Molecular Biology (ismb). A method (CORNET) developed in the lab for the prediction of contact maps of proteins (a relevant step for the ab initio prediction of protein 3D structure) has been scored the best of its category in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) No 4 and No 5 (Asimolar, California, 2000 and 2002 ). Recently a method for predicting the topography of outer membrane proteins based on HMM and sequence profile has been acknowledged with the SGI best award at ismb02 (Edmonton, Canada, August 3-7, 2002). The unit is also active in organizing training courses on Bioinformatics.

 

Professor Gérard Dreyfus
ESPCI
Laboratoire d'Électronique, Paris, France
 
Homepage
Email: Gerard.Dreyfus@espci.fr

After spending most of his formative years in Toulouse, Gérard Dreyfus obtained his PhD from Université Pierre et Marie Curie, Paris, in 1976. As a professor at ESPCI (Ecole Supérieure de Physique et de Chimie Industrielles), he created, and heads, a research laboratory on machine learning. The group features seven permanent researchers and a varying number of doctoral students, post-docs and associate professors. Research topics range from industrial applications of machine learning techniques to the investigation of coding mechanisms in nervous systems. Gérard Dreyfus authored or coauthored two textbooks, and over 150 international publications and patents. He is a member of the editorial board of several international journals, and was active in the organization of several conferences: he chaired the first European conference on neural networks, nEuro’88, in Paris. Together with other researchers, he created two companies, in 1973 and 1994 respectively.

 

Professor Manuel Samuelides
ONERA
Ecole Nationale Supérieure de l'Aéronautique et de l'Espace, France
 
Homepage
Email: samuelid@supaero.fr
Abstract of talk

Professor Manuel Samuelides (Ecole Normale Supérieure, Ph.D. in functionnal Analysis at Paris VI in 1971) is Head of the Applied Mathematics Department at "Ecole Nationale Supérieure de l'Aéronautique et de l'Espace since 1978. He holds a joint position as senior scientist at ONERA (French National Agency for Research in Aeronautics and Space) from 1988. He works in the field of Neural Networks since 1988 from the point of view of dynamical systems and probability theory. He is also interested in Machine Learning and Artificial Intelligence. He has developed his research in three different directions. The first one is mostly theoretical and considers large randomly connected recurrent networks, studying their dynamics and attractors in the stationary regime. The second is directed to artificial vision in collaboration with biologists, developing spiking neural networks and studying asynchronous and synchronous firing assemblies, with application to image segmentation and classification. Finally, he works on reinforcement learning, identification and control of dynamical systems with application to mobile robotics. Professor Samuelides has organized several international workshops in the area of "DYNN" (Dynamical Neural Networks and Applications). He has also co-authored more than 50 papers in journals and written two books in the field of Neural Networks in 1991 and 2002.