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[Call for applications] *Graduate Programs in Computational Neuroscience* in Berlin; MSc and PhD; 7 PhD scholarships; deadline March 15, 2015

by Robert Martin

[Apologies for cross-posting] *Doctoral* and *Master Program* "Computational Neuroscience" at the Bernstein Center for Computational Neuroscience Berlin in Berlin, Germany Application deadline: *March 15, 2015* Begin of courses: October 2015 Internet: www.computational-neuroscience-berlin.de _Doctoral Program_ The Bernstein Center for Computational Neuroscience Berlin and the TU Berlin invite applications for *7 fellowships* of the Research Training Group "Sensory Computation in Neural Systems" (GRK 1589/2, https://www.eecs.tu-berlin.de/grk_15891/menue/sensory_computation_in_neural…) The *scientific program* of the research training group combines techniques and concepts from machine learning, computational neuroscience, and systems neurobiology in order to specifically address sensory computation. Doctoral candidates will work on interdisciplinary projects investigating the mechanisms of neural computation, address the processes underlying perception on different scales and different levels of abstraction, and develop new theories of computation hand in hand with well-controlled experiments in order to put functional hypotheses to the test. The training group offers structured supervision complemented by a teaching and training program. Each student will be supervised by two investigators with complementary expertise and will be associated with the Bernstein Center for Computational Neuroscience Berlin (https://www.bccn-berlin.de/) a leading research center dedicated to the theoretical study of neural processing. Candidates are expected to hold a Masters degree (or equivalent) in a relevant subject (e.g., neuroscience, cognitive science, computer science, physics, mathematics, etc.) and have the required advanced mathematical background. Candidates selected in the first application step will be invited for lab visits and an interview, expected to take place in June 2015. The *fellowships of 1468 €/month* - with additional children allowances if applicable---will be granted for up to three years. _Master's Program_ The tuition-free Master program in Computational Neuroscience offers *15 places* per year, has a duration of 2 years and is fully taught in English. The *curriculum* is subdivided into ten modules, whose content includes theoretical neuroscience, programming, machine learning, cognitive neuroscience, acquisition, modelling, and computational analysis of neural data, with a strong focus on a complementary theoretical and experimental training. Three lab rotations and a Master's thesis are accomplished in the second year. The aim of the program is to provide the students with an interdisciplinary education and an early contact to the neurocomputational research environment. *Requirements* BSc or equivalent degree in a relevant subject (typically in the natural sciences, in an engineering discipline, in cognitive science, or in mathematics), certificate of English proficiency, proof of sufficient mathematical knowledge (at least 24 ECTS credit points). ~~~ _For more information_ ... ... come and visit us on our *information day* on January 14, 2015, at 3 PM (sharp) at the BCCN Berlin: https://www.bccn-berlin.de/Calendar/Events/event/?contentId=3667 ... or browse: www.computational-neuroscience-berlin.de ... or e-mail: graduateprograms(a)bccn-berlin.de . Best regards, Robert Martin -- Robert Martin, PhD Teaching Coordinator Bernstein Center for Computational Neuroscience Humboldt-Universitaet zu Berlin Philippstr. 13 House 6; 10115 Berlin; Germany Phone/Fax +49 (0)30 2093 6773/6771 http://www.computational-neuroscience-berlin.de GRK 1589/1, Sensory Computation in Neural Systems Technische Universitaet Berlin Sekretariat MAR 5-6; Marchstr. 23; 10587 Berlin Phone/Fax +49 (0)30 314 72006/73121 http://www.eecs.tu-berlin.de/grk_15891/

Dec. 19, 2014

Advanced Scientific Programming in Python Summer School

by Emanuele Olivetti

Advanced Scientific Programming in Python ========================================= a Summer School by the G-Node, the Bernstein Center for Computational Neuroscience Munich and the Graduate School of Systemic Neurosciences Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques, incorporating theoretical lectures and practical exercises tailored to the needs of a programming scientist. New skills will be tested in a real programming project: we will team up to develop an entertaining scientific computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or Mathematica is absolutely required. Basic knowledge of Python is assumed. Participants without any prior experience with Python should work through the proposed introductory materials before the course. Date and Location ================= August 31—September 5, 2015. Munich, Germany. Preliminary Program =================== Day 0 (Mon Aug 31) — Best Programming Practices • Best Practices for Scientific Computing • Version control with git and how to contribute to Open Source with github • Object-oriented programming & design patterns Day 1 (Tue Sept 1) — Software Carpentry • Test-driven development, unit testing & quality assurance • Debugging, profiling and benchmarking techniques • Advanced Python: generators, decorators, and context managers Day 2 (Wed Sept 2) — Scientific Tools for Python • Advanced NumPy • The Quest for Speed (intro): Interfacing to C with Cython • Contributing to Open Source Software/Programming in teams Day 3 (Thu Sept 3) — The Quest for Speed • Writing parallel applications in Python • Python 3: why should I care • Programming project Day 4 (Fri Sept 4) — Efficient Memory Management • When parallelization does not help: the starving CPUs problem • Programming project Day 5 (Sat Sept 5) — Practical Software Development • Programming project • The Pelita Tournament Every evening we will have the tutors' consultation hour: Tutors will answer your questions and give suggestions for your own projects. Applications ============ You can apply on-line athttps://python.g-node.org Applications must be submitted before 23:59 UTC, March 31, 2015. Notifications of acceptance will be sent by May 1, 2015. No fee is charged but participants should take care of travel, living, and accommodation expenses. Candidates will be selected on the basis of their profile. Places are limited: acceptance rate is usually around 20%. Prerequisites: You are supposed to know the basics of Python to participate in the lectures Preliminary Faculty =================== • Francesc Alted, freelance developer, author of PyTables, Spain • Pietro Berkes, Enthought Inc., UK • Kathryn D. Huff, Department of Nuclear Engineering, University of California - Berkeley, USA • Zbigniew Jędrzejewski-Szmek, Krasnow Institute, George Mason University, USA • Eilif Muller, Blue Brain Project, École Polytechnique Fédérale de Lausanne, Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Germany • Nelle Varoquaux, Centre for Computational Biology Mines ParisTech, Institut Curie, U900 INSERM, Paris, France • Stéfan van der Walt, Applied Mathematics, Stellenbosch University, South Africa • Niko Wilbert, TNG Technology Consulting GmbH, Germany • Tiziano Zito, Forschungszentrum Jülich GmbH, Germany Organized by Tiziano Zito (head) and Zbigniew Jędrzejewski-Szmek for the German Neuroinformatics Node of the INCF Germany, Christopher Roppelt for the German Center for Vertigo and Balance Disorders (DSGZ) and the Graduate School of Systemic Neurosciences (GSN) of the Ludwig-Maximilians-Universität Munich Germany, Christoph Hartmann for the Frankfurt Institute for Advanced Studies (FIAS) and International Max Planck Research School (IMPRS) for Neural Circuits, Frankfurt Germany, and Jakob Jordan for the Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich Research Centre and JARA. Additional funding provided by the Bernstein Center for Computational Neuroscience (BCCN) Munich. Website:https://python.g-node.org Contact:python-info@g-node.org

Dec. 19, 2014

Mathematical post-doc position on the relation of information and causation (Prof. Giulio Tononi)

by albantakis

A postdoctoral position is available at the center for sleep and consciousness science in the laboratory of Dr. Giulio Tononi (University of Wisconsin, Madison), to study the relation of information and causation within the framework of the integrated information theory of consciousness (Balduzzi & Tononi, 2008; Tononi, 2012). Immediate funding is available for a range of projects related to foundational questions regarding the ontological status of information, and its relation to causation, emergence, adaptation, evolution, and consciousness (see detailed scope of work below). The successful candidate will work in the information integration theory group at the center for sleep and consciousness science, which is dedicated to a broad range of research problems focused on two neurobiological problems -- the mechanisms and functions of sleep and the neural substrates of consciousness. Candidates are expected to have strong training in an analytically rigorous discipline such as theoretical biology/neuroscience, physics, mathematics, computer science, or engineering. We explicitly encourage mathematicians to apply. Experience in information theory, complex systems, and an interest in the philosophy of information/causation are a plus. Programming experience is required (knowledge of MATLAB, Python, and/or C++ is of advantage). Appointments are renewable from year to year for up to 3 years, starting as soon as possible or until the positions are filled. Post-doc salaries correspond to the National Institutes of Health National Research Service Award (NRSA) stipend schedule for postdoc trainees, based on number of years of postdoctoral experience. Candidates should send a CV, brief statement of previous research and future research interests, and email addresses and phone numbers of three references to: Giulio Tononi, gtononi(a)wisc.edu. Oizumi M, Albantakis L, Tononi G (2014) From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0. /PLoS Comput Biol/ 10:e1003588 Hoel, E. P., Albantakis, L., & Tononi, G. (2013). Quantifying causal emergence shows that macro can beat micro. /PNAS/, /110/(49), 19790--19795. Tononi G (2012) Integrated Information Theory of Consciousness: An Updated Account. /Arch Ital Biol/ 150:56--90. The scope of work will range from: -theoretical development and computational implementation of the notion of intrinsic causal information -causal analysis, including the systematic use of perturbations, counterfactuals, and irreducibility -analysis of complex systems in terms their causal/informational structure -meaning (understanding and control) from the intrinsic perspective of the system -actual causation (causal explanation) -examining similarities and differences between existing notions of information and causation (Shannon information, algorithmic information,...) -defining emergence in terms of the spatio-temporal grain size at which a system of elements achieves a maximum of causal power -evolutionary/adaptive aspects of information/causation including simulations based on small adaptive neural networks (animats), which evolve and adapt to an environment that requires sensitivity to context for survival -- Larissa Albantakis, PhD Department of Psychiatry University of Wisconsin 6001 Research Park Blvd Madison, WI 53719

Dec. 17, 2014

Announcement of Conference Net-works 2015

by jtorres

Dear Colleagues This is the first announcement for participation in the 7th International conference on Complex Networks and their Interdisciplinary Applications, Net-works 2015, which will be held in Granada (Spain) from September 16th to September 18th 2015 (Please follow the link below for further information) http://ergodic.ugr.es/networks2015/ As in previous editions, this conference is devoted to present and exchange the latest results concerning the theory and application of complex networks in different aspects of nature, society and technology. In the last years, there was an increasing interest of the computational neuroscience community in the study of the features of the complex networks underlying the structure of actual neural systems, and how these features influence their emergent behavior. For this reason, the organizing committee of Net-works 2015 encourages computational neuroscientists interested in this research topic to attend and participate in this conference. The program of Net-Works 2015 includes a set of invited plenary talks from very well- known experts in the field of complex networks, a number to be determined of talks selected from the received abstracts and one or two poster sessions. Tentative list of key-note speakers: -Ginestra Bianconi School of Mathematics. Queen Mary University of London, UK -Stefano Boccaletti Institute for Complex Systems, CNR, Italy -Shlomo Havlin Bar-Ilan University, Israel -JÃ¼rgen KurthsPotsdam Institute for Climate Impact Research, Germany -Miguel A. MuÃ±oz Institute Carlos I for Theoretical and Computational Physics, U. Granada, Spain Important dates for abstract submission and registration follows: Abstract submission: May 22th 2015 Contribution acceptance: June 15th 2015 Early registration (with a reduction of the registration fee): before September 15th, 2015. Abstracts (with a maximum of 250 words) must be submitted to the e-mail address below: abstracts(a)eurocongres.es It is a pleasure for me to kindly invite you to participate in Net-Works 2015. We look forward to seeing you in Granada! Joaquin J. Torres General Chair Net-Works 2015 International Conference Please visit the conference web page for further information: http://ergodic.ugr.es/networks2015/

Dec. 17, 2014

Announcing Okinawa Computational Neuroscience Course 2015

by Erik De Schutter

OKINAWA COMPUTATIONAL NEUROSCIENCE COURSE 2015 Methods, Neurons, Networks and Behaviors June 8 - June 25, 2015 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc The aim of the Okinawa Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling. We invite graduate students and postgraduate researchers to participate in the course, held from June 8th through June 25th, 2015 at an oceanfront seminar house of the Okinawa Institute of Science and Technology Graduate University. Applications will open on January 5th and are through the course web page (https://groups.oist.jp/ocnc) only; they will close February 8th, 2015. Applicants will receive confirmation of acceptance in March. The course has a strong hands-on component based on student proposed modeling or data analysis projects, which are further refined with the help of a dedicated tutor. Applicants are required to propose their project at the time of application. Like in preceding years, OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have lectures by international experts. We invite those who are interested in integrating experimental and computational approaches at each level, as well as in bridging different levels of complexity. There is no tuition fee. The sponsor will provide lodging and meals during the course and may support travel for those without funding. We hope that this course will be a good opportunity for theoretical and experimental neuroscientists to meet each other and to explore the attractive nature and culture of Okinawa, the southernmost island prefecture of Japan. Invited faculty: • Gordon Arbuthnott (OIST) • Axel Borst (MPI, Münich, Germany) • Erik De Schutter (OIST) • Kenji Doya (OIST) • Eugene Izihikevich (Brain Corporation, USA) • Bernd Kuhn (OIST) • Peter Latham (Gatsby Unit, UCL, UK) • Miguel Nicolelis (Duke University, USA) • Steve Prescott (University of Toronto, Canada) • John Rinzel (New York University, USA) • Jackie Schiller (Technion, Israel) • Greg Stephens (OIST) • Jeff Wickens (OIST) • Taro Toyoizumi (RIKEN BSI, Japan) • Xiao-Jing Wang (New York University, USA) • Wako Yoshida (ATR, Japan)

Dec. 17, 2014

workshop on Brain Circuits, Memory and Computation

by Aurel A. Lazar

Columbia Workshop on Brain Circuits, Memory and Computation BCMC 2015 <http://www.bionet.ee.columbia.edu/workshops/bcmc/2015> Monday and Tuesday, March 16-17, 2015 Center for Neural Engineering and Computation <http://www.cnec.columbia.edu/> Columbia University, New York, NY 10027 Overview The goal of the workshop is to bring together researchers interested in developing executable models of neural computation/processing of the brain of model organisms. Of interest are models of computation that consist of elementary units of processing using brain circuits and memory elements. Elementary units of computation/processing include population encoding/decoding circuits with biophysically-grounded neuron models, non-linear dendritic processors for motion detection/direction selectivity, spike processing and pattern recognition neural circuits, movement control and decision-making circuits, etc. Memory units include models of spatio-temporal memory circuits, circuit models for memory access and storage, etc. A major aim of the workshop is to explore the integration of various computational sensory and control models. Confirmed Invited Speakers Yoshi Aso <http://www.janelia.org/people/scientist/yoshi-aso>, Janelia Research Campus, Ashburn, VA. Dmitri "Mitya" B. Chklovskii <http://www.simonsfoundation.org/about-us/staff/staff-bios/>, Simons Center for Data Analysis, Simons Foundation. Damon A. Clark <http://clarklab.commons.yale.edu/>, Department of Molecular, Cellular, and Developmental Biology, Yale University. Daniel Coca <https://www.sheffield.ac.uk/acse/staff/dc>, Department of Automatic Control and Systems Engineering, University of Sheffield. Fabrizio Gabbiani <http://glab.bcm.tmc.edu/>, Dept. of Neuroscience, Baylor College of Medicine, and Computational and Applied Mathematics, Rice University. Charles Randy Gallistel <http://ruccs.rutgers.edu/~galliste/>, Rutgers Center for Cognitive Science, Rutgers University. Charles D. Gilbert <http://lab.rockefeller.edu/gilbert/>, Laboratory of Neurobiology, Rockefeller University. Vivek Jayaraman <http://www.janelia.org/lab/jayaraman-lab>, Janelia Research Campus, Ashburn, VA. Mikko I. Juusola <http://www.shef.ac.uk/bms/research/juusola>, Department of Biomedical Science, University of Sheffield. Anthony Leonardo <http://janelia.org/people/scientist/anthony-leonardo>, Janelia Research Campus, Ashburn, VA. Wolfgang Maas <http://www.igi.tugraz.at/maass/>, Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria. Gary F. Marcus <http://www.psych.nyu.edu/gary/>, Department of Psychology, New York University. Stefan Mihalas <http://www.alleninstitute.org/our-institute/our-team/profiles/stefan-mihala…>, Allen Institute for Brain Science, Seattle, WA. Barbara Webb <http://homepages.inf.ed.ac.uk/bwebb/>, School of Informatics, University of Edinburgh. Further details are available at BCMC 2015 <http://www.bionet.ee.columbia.edu/workshops/bcmc/2015>. Aurel http://www.bionet.ee.columbia.edu

Dec. 16, 2014

Brains, Minds and Machines Summer Course 2015

by Kreiman, Gabriel

Brains, Minds and Machines Course Date: August 13 – September 3, 2015 http://www.mbl.edu/education/special-topics-courses/brains-minds-and-machin… Directors: L. Mahadevan, Harvard University; and Tomaso Poggio, Massachusetts Institute of Technology This intensive three-week course will give advanced students a “deep end” introduction to the problem of intelligence – how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines. Today’s AI technologies, such as Watson and Siri and Deep Learning, are impressive, but their domain specificity and reliance on vast numbers of labeled examples are obvious limitations; few view this as brain-like or human intelligence. The synergistic combination of cognitive science, neurobiology, engineering, mathematics, and computer science holds the promise to build much more robust and sophisticated algorithms implemented in intelligent machines *and* to begin understanding how the brain produces the mind. The goal of this course is to help produce a community of leaders that is equally knowledgeable in neuroscience, cognitive science, and computer science. The first half of the course will focus on the intersection between biological and computational aspects of learning and vision. The second half will focus on high-level social cognition and artificial intelligence, as well as audition, speech and language processing. Throughout the course, students will participate in tutorials to gain hands on experience with these topics. The course will culminate with student projects on a chosen aspect of the problem of intelligence. Course instructors will include: Tomaso Poggio Gabriel Kreiman Nancy Kanwisher Winrich Freiwald Matt Wilson Josh Tenenbaum Liz Spelke Boris Katz L Mahadevan Jim DiCarlo Aude Oliva Gabriel Kreiman klab.tch.harvard.edu Use "9265358979" anywhere in the message body to ensure that your message navigates through anti spam filters

Dec. 16, 2014

Graduate Training in Brain and Cognitive Sciences at the University of Rochester

by Ralf Haefner

The Department of Brain and Cognitive Sciences (BCS) at the University of Rochester offers opportunities for students interested in earning a doctoral degree in one of the most exciting fields of scientific endeavor. Particular areas of research strength include: sensory processing and decision-making, perception and action, development and learning, language, concepts and categories. Full details can be found at: http://www.bcs.rochester.edu/index.php. We seek outstanding candidates from a variety of backgrounds looking for a rigorous program of study and exceptional mentoring in research. All students admitted to the program are offered graduate fellowships that provide a competitive stipend, and that cover the costs of tuition and single plan health insurance. The Department has a number of new faculty with research programs focusing on cognitive neuroscience, development of language and cognition, language learning, theoretical and computational neuroscience, and visual neuroscience. Interested applicants can find details at http://www.bcs.rochester.edu/graduate/admission.html.

Dec. 16, 2014

The First International Conference on Mathematical Neuroscience (ICMNS)

by Olivier Faugeras

*Second announcement* 1st International Conference on Mathematical Neuroscience (ICMNS) June 8 - 10, 2015 Antibes - Juan les Pins, France https://icmns2015.inria.fr The goal of this conference is to bring together theoretical neuroscientists and mathematicians interested in using mathematical concepts and methods for solving problems posed by neuroscience. It is motivated by the idea that many outstanding questions concerning the functioning/dysfunctioning of brains at multiple spatial and temporal scales will require the use of a wide range of mathematical tools, including, but not restricted to, functional analysis, dynamical systems theory, bifurcation theory, probability and statistics, stochastic calculus, geometry, information theory, and numerical analysis. It is also likely that neuroscience will spawn new areas of mathematics. The conference will be single track. It will feature three keynote lectures, oral presentations, and poster presentations. The keynote lecturers are Susanne Ditlevsen (University of Copenhagen, Denmark), stochastic processes in neuroscience, Bard Ermentrout (University of Pittsburgh, USA), neurodynamics, and Yves Frégnac (CNRS, France), neuroscience of vision. Call for contributions Oral presentations will be selected from the submission of one-page abstracts. Poster presentations will be selected from the submissions of a half a page abstracts. Accepted oral contributions will be considered for possible publication in a special issue of the Journal of Mathematical Neuroscience. See the page https://icmns2015.inria.fr/accepted-papers/ for LaTeX and Word templates and how to submit. Important dates: Submission deadline: February 2, 2015 Notification of acceptance: February 27, 2015 Best regards, Olivier Faugeras --------------------------------------------------------------------------------------- : Olivier Faugeras : Professor : Equipe INRIA NeuroMathComp Team : co-editor in chief, Journal of Mathematical Neuroscience : http://www-sop.inria.fr/members/Olivier.Faugeras/index.en.html : Email: olivier.faugeras(a)inria.fr : Tel: +334 92 38 78 31 : Sec: +334 92 38 78 30 : ---------------------------------------------------------------------------------------

Dec. 16, 2014

INNS BigData 2015 San Francisco - New Conference! Calls for Papers, Special Sessions, Tutorials and Workshops!

by Asim Roy

Apologies for cross-posting. <http://www.innsbigdata.org/> [http://innsbigdata.org/wp-content/uploads/2014/09/banner.jpg]<http://www.innsbigdata.org/> INNS Conference on Big Data 2015 New approaches to solving hard Big Data problems! 8 - 10 August 2015, San Francisco www.innsbigdata.org<http://www.innsbigdata.org/> The aim of the INNS BigData conference is to promote new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of Big Data Analytics to solve real-world problems (e.g. weather prediction, transportation, energy management). Please refer to our website for a more detailed list of topics. Being INNS' inaugural conference on the theme of big data, we are especially motivated to synthesize ideas, promote activities and generate broad interest in areas where neural networks have many unique advantages. We also have Twitter<https://twitter.com/inns_bigdata>, Facebook<https://www.facebook.com/innsbigdata15/> and Google+<https://plus.google.com/112891798437473029046> pages! Call for Special Sessions<http://innsbigdata.org/special-sessions/> Any proposal can be sent by e-mail to: INNSBigData2015SpecialSessions(a)gmail.com<mailto:INNSBigData2015SpecialSessions@gmail.com> Deadline: January 22, 2015 Call for Tutorials<http://innsbigdata.org/tutorials/> Any questions can be sent to the Tutorials Chairs: Marley Vellasco (PUC-Rio. Rio de Janeiro. Brazil)<mailto:Marley%20Vellasco%20(PUC-Rio.%20Rio%20de%20Janeiro.%20Brazil)%20%3cmarley@ele.puc-rio.br%3e> and Trevor Martin (Univ. of Bristol, UK)<mailto:Trevor%09Martin%20(Univ.%20of%20Bristol.%20UK)%20%3ctrevor.martin@bristol.ac.uk%3e>. Deadline: January 22, 2015 Call for Workshops<http://innsbigdata.org/workshops/> For further details contact the Workshop Chairs: Marley Vellasco (PUC-Rio. Rio de Janeiro. Brazil)<mailto:Marley%20Vellasco%20(PUC-Rio.%20Rio%20de%20Janeiro.%20Brazil)%20%3cmarley@ele.puc-rio.br%3e> and Trevor Martin (Univ. of Bristol, UK)<mailto:Trevor%09%09%20%20Martin%20(Univ.%20of%20Bristol.%20UK)%20%3ctrevor.martin@bristol.ac.uk%3e>. Deadline: January 22, 2015 [http://innsbigdata.org/wp-content/uploads/2014/09/new.gif]The Elsevier USD 2000 Big Data Best Paper Award:<http://innsbigdata.org/best-paper-award/> This award recognizes the best paper presented at the INNS Big Data conference. Both application and theoretical papers will be considered. It will be awarded by the Big Data Analytics Section of the International Neural Network Society and is sponsored by Elsevier. The Award consists of a plaque and a $2000 honorarium. ________________________________ [http://innsbigdata.org/wp-content/uploads/2014/09/new.gif]Dr. Fen Zhao Talk<http://innsbigdata.org> Dr. Fen Zhao, a Staff Associate at the Office of the Assistant Director (OAD) for Computer & Information Science & Engineering (CISE) at the National Science Foundation, will give a talk on national big data R&D initiative and on building public-private partnerships around CISE's Big Data, next generation internet, and cybersecurity R&D portfolios. ________________________________ Plenary Speakers:<http://innsbigdata.org/> [http://innsbigdata.org/wp-content/uploads/2014/11/Bin-Yu.jpg] Prof. Bin Yu<https://www.stat.berkeley.edu/~binyu/Site/Welcome.html>, Chancellor´s Professor, University of California<http://www.universityofcalifornia.edu/>, Berkeley. Bin Yu is Chancellor’s Professor in the Departments of Statistics and of Electrical Engineering & Computer Science at the University of California at Berkeley. She held faculty positions at UW-Madison and Yale University and was a Member of Technical Staff at Lucent Bell Labs. She was Chair of Department of Statistics at Berkeley from 2009 to 2012, and is a founding co-director of the Microsoft Joint Lab on Statistics and Information Technology at Peking University where she is also Chair of the scientific advisory committee of the Center for Statistical Sciences. She has published over 80 scientific papers in premier journals in statistics, machine learning, information theory, signal processing, remote sensing, neuroscience, network analysis, and bioinformatics. [http://innsbigdata.org/wp-content/uploads/2014/11/Raghu.jpg] Prof. Raghu Ramakrishnan<http://pages.cs.wisc.edu/~raghu/>, Head of Cloud and Information Services Lab (CISL) and big data team, Microsoft<http://research.microsoft.com/en-us/events/fs2013/raghu-ramakrishnan_bigdat…> Raghu Ramakrishnan heads the Cloud and Information Services Lab (CISL) in the Data Platforms Group at Microsoft, and leads development for the Big Data team. From 1987 to 2006, he was a professor at University of Wisconsin-Madison, where he wrote the widely-used text “Database Management Systems” and led a wide range of research projects in database systems (e.g., the CORAL deductive database, the DEVise data visualization tool, SQL extensions to handle sequence data) and data mining (scalable clustering, mining over data streams). In 1999, he founded QUIQ, a company that introduced a cloud-based question-answering service. He joined Yahoo! in 2006 as a Yahoo! Fellow, and over the next six years served as Chief Scientist for the Audience (portal), Cloud and Search divisions, driving content recommendation algorithms (CORE), cloud data stores (PNUTS), and semantic search (“Web of Things”). Ramakrishnan has received several awards, including the ACM SIGKDD Innovations Award, the SIGMOD 10-year Test-of-Time Award, the IIT Madras Distinguished Alumnus Award, and the Packard Fellowship in Science and Engineering. [http://innsbigdata.org/wp-content/uploads/2014/11/brenda.jpg] Prof. Brenda Dietrich,<https://www-03.ibm.com/ibm/history/witexhibit/wit_fellows_dietrich.html> IBM Fellow and VP, Leads the Emerging Technologies Team for IBM Watson, IBM<http://www.ibm.com/ibm/ideasfromibm/us/ibm_fellows/> Brenda Dietrich is an IBM Fellow and Vice President. She joined IBM in 1984 and has worked in the area now called analytics for her entire career, applying data and computation to business decision processes throughout IBM. For over a decade she led the Mathematical Sciences function in the IBM Research division where she was responsible for both basic research on computational mathematics and for the development of novel applications of mathematics for both IBM and its clients. She has been the president of INFORMS, has served on the Board of Trustees of SIAM, and is a member of several university advisory boards. She holds more than a dozen patents, has co-authored numerous publications, and frequently speaks on analytics at conferences. She was elected to the National Academy of Engineering in 2014. She holds a BS in Mathematics from UNC and an MS and Ph.D. in OR/IE from Cornell. Her personal research includes manufacturing scheduling, services resource management, transportation logistics, integer programming, and combinatorial duality. She currently leads the emerging technologies team for IBM Watson, extending and applying IBM’s cognitive computing technology. ________________________________ Important Dates<http://innsbigdata.org/important-dates/> * Paper submission:<http://innsbigdata.org/paper-submission/> March 22, 2015. * Paper Decision Notification: May 22, 2015. * Camera Ready Submission of papers: June 8, 2015. ________________________________ We have an enthusiastic team working hard on the conference program and events. Start thinking about your paper submissions. Our Chairs for the [Special Sessions, Tutorials, and Workshops] are expecting your proposals soon - email them to discuss your ideas. Come to San Francisco next summer to take part in the future of BigData, and to have fun!! Neural Networks Special Issue: Neural Network Learning in Big Data<http://www.journals.elsevier.com/neural-networks/call-for-papers/special-is…> For this special issue of Neural Networks, we invite papers that address many of the challenges of learning from big data. In particular, we are interested in papers on efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of online learning to solve real-world big data problems (e.g. health care, transportation, and electric power and energy management). Manuscript submission due: January 15, 2015 Big Data Analytics Section @ INNS<http://www.inns.org/big-data-section> Considering the growing interest to process and analyse big data, the International Neural Network Society (INNS) has a new Section on Big Data Analytics (BDA) to help the neural network field position itself as a leading technology contributor to big data analytics. Anyone who is interested to know more is encouraged to visit the homepage of the INNS-BDA Section<http://www.inns.org/big-data-section>. General Chairs:<http://innsbigdata.org/committees/> Asim Roy<https://webapp4.asu.edu/directory/person/9973> (email<mailto:Asim%20Roy.%20General%20Co-Chair.%20INNS%20BigData2015.%20Arizona%20StateU.%20USA%20%3cASIM.ROY@asu.edu%3e>) INNS BigData General Co-Chair Arizona State University, USA INNS Board of Governors Plamen Angelov<http://www.lancaster.ac.uk/staff/angelov/> (email<mailto:Plamen%20Angelov.%20General%20Co-Chair.%20INNS%20BigData2015.%20Lancaster%20U.%20UK%20%3cp.angelov@lancaster.ac.uk%3e>) INNS BigData General Co-Chair Lancaster University, UK Chair in Intelligent Systems ________________________________ Many thanks to our Sponsors: [http://www.inns.org/assets/site/neural.png]<http://www.inns.org/> [http://innsbigdata.org/wp-content/uploads/2014/10/elsevier-logo-300x300-150…]<http://www.elsevier.com/> To unsubscribe from this list, send an email to Jose Antonio Iglesias, INNS BigData 2015 Publicity Co-Chair, Carlos III Univ, Madrid, Spain<mailto:Jose%20Antonio%20Iglesias.%20INNS%20BigData%202015%20Publicity%20Co-Chair.%20Carlos%20III%20Univ.%20Madrid.%20Spain%20%3cBigData2015-INNS-SanFrancisco@BillHowell.ca%3e?subject=Remove%20my%20email&body=Click%20to%20send.%20This%20will%20remove%20your%20email%20address%20from%20the%20INNS%20mass%20email%20list.> with the phrase "Remove my email" in the Subject line.

Dec. 16, 2014