January 2015 - Comp-neuro - lists.cnsorg.org

Postdoctoral and PhD positions in computational neuroscience at Harvard

by Haim Sompolinsky

Dear colleagues, I have several openings for research in computational neuroscience at the doctoral and postdoctoral levels. See the following announcement. Best, Haim Opportunities in Theoretical Neuroscience Doctoral and Postdoctoral Opportunities in Theoretical Neuroscience I am seeking doctoral and postdoctoral associates for research on theoretical neuroscience projects. Creativity, analytical and numerical skills, drive, and a background in physics, computational neuroscience, applied mathematics, or computer science are expected. Research topics span a broad range of topics dealing with the principles underlying the links between neuronal circuits' structure, dynamics, behavior and cognition. Positions are available for work in the Swartz theoretical neuroscience group at Harvard http://cbs.fas.harvard.edu/ <http://cbs.fas.harvard.edu/> . Please submit your application including CV, list of publications and names of three possible referees to Prof. Haim Sompolinsky: haim(a)fiz.huji.ac.il <mailto:haim@fiz.huji.ac.il>. -- Haim Sompolinsky The Hebrew University For research positions, see: http://neurophysics.huji.ac.il/Opportunities

Jan. 15, 2015

CFP: HRI 2015 Workshop on “Cognition: A Bridge between Robotics and Interaction”

by Yukie Nagai

============================================================ Workshop “Cognition: A Bridge between Robotics and Interaction”, at HRI 2015, Portland (OR) USA ============================================================ March 2, 2015 Submission deadline: January 20, 2015 Notification of acceptance: January 30, 2015 website: http://www.macs.hw.ac.uk/~kl360/HRI2015W/ ============================================================ INVITED SPEAKERS: - Prof. David Vernon, Sk?vde University - Prof. Andrew Meltzoff, University of Washington INVITED PANELISTS: - Prof. Giulio Sandini, Italian Institute of Technology - Prof. Minoru Asada, Osaka University A key feature of humans is the ability to anticipate what other agents are going to do and to plan accordingly a collaborative action. This skill, derived from being able to entertain models of other agents, allows for the compensation for intrinsic delays of human motor control and is a primary support to allow for efficient and fluid interaction. Moreover, the awareness that other humans are cognitive agents who combine sensory perception with internal models of the environment and others, enables easier mutual understanding and coordination. Cognition represents therefore an ideal link between different disciplines, as the field of Robotics and that of Interaction studies, performed by neuroscientists and psychologists. From a robotics perspective, the study of cognition is aimed at implementi ng cognitive architectures leading to efficient interaction with the environment and other agents. From the perspective of the human disciplines, robots could represent an ideal stimulus to study which are the fundamental robot properties necessary to make it perceived as a cognitive agent, enabling natural human-robot interaction. Ideally, the implementation of cognitive architectures may raise new interesting questions for psychologists, and the behavioral and neuroscientific results of the human-robot in teraction studies could validate or give new inputs for robotics engineers. The aim of this workshop will be to provide a venue for researchers of different disciplines to discuss the possible points of contact and to highlight the issues and the advantages of bridging different fields for the study of cognition for interaction. T his workshop will represent an ideal continuation of the discussion began at HRI 2014, in the workshop “HRI: a bridge between Robotics and Neuroscience” (http://www.macs.hw.ac.uk/~kl360/HRI2014W/index.html) LIST OF TOPICS ------------- - Cognitive Architecture - Development of Social Cognition - Interaction - Prediction - Embodiment - Self and Other FORMAT AND SUBMISSIONS ----------------------- The workshop will consist of invited keynotes, time for discussions and will also feature a poster session. Prospective participants are invited to submit full papers (up to 8 pages) or short papers (2 pages). Submissions will be accepted in PDF format only, using the HRI formatting guidelines (http://www.macs.hw.ac.uk/~kl360/HRI2015W/papers.html) and including author names. Authors should send their papers to hri2015workshop(a)gmail.com . All submissions will be peer-reviewed. Upon available time, selected contributions may have the opportunity to be presented in the oral session. The other selected contributions will be presented as posters during a dedicated session. The submission must include 1 answer to one of the following questions: - How should cognitive research be structured to yield results useful for robotics and HRI? - How can robotics have a direct influence on neuroscience and cognitive psychology aimed at interaction studies? - Which is the minimal level of cognition needed in a robot to be able to interact with a human? - Does a robot really need cognition to be perceived as a cognitive agent by a human? - Does inserting a cognitive agent into an interaction pose a risk to the human partners? - How important is the embodiment of a robot for the development of its cognitive architecture and its social cognition? Upon available time, those questions/answers will be used to "drive" a final discussion. IMPORTANT DATES ---------------- Submission deadline: January 20, 2015 Notification of acceptance: January 30, 2015 Workshop at HRI 2015: March 2, 2015 ORGANIZERS ----------- - Alessandra Sciutti Istituto Italiano di Tecnologia - Katrin Solveig Lohan Heriot-Watt University - Yukie Nagai Osaka University — Yukie Nagai, Ph.D. Specially Appointed Associate Professor, Osaka University Visiting Researcher, Bielefeld University yukie(a)ams.eng.osaka-u.ac.jp http://cnr.ams.eng.osaka-u.ac.jp/~yukie/

Jan. 14, 2015

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

by Asim Roy

Apologies for cross-posting. Note the plenary talk by Juergen Schmidhuber (Prof. Jürgen Schmidhuber<http://people.idsia.ch/~juergen/>) on Deep Learning. There will also be a tutorial and a workshop on Deep Learning by Juergen Schmidhuber and Dong Yu of Microsoft Research (Dong Yu<http://research.microsoft.com/en-us/people/dongyu/>, Microsoft Research<http://research.microsoft.com/en-us/>). Note the deadlines for submission of proposals for special sessions, tutorials and workshops. See you in San Francisco. <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! ________________________________ [http://innsbigdata.org/wp-content/uploads/2014/09/new.gif]PLENARY TALK<http://innsbigdata.org/> [http://innsbigdata.org/wp-content/uploads/2014/11/juergen.jpg] DEEP LEARNING Prof. Jürgen Schmidhuber<http://people.idsia.ch/~juergen/>, Professor of Artificial Intelligence at the University of Lugano<http://www.inf.usi.ch/index.htm>, and the Swiss AI Lab IDSIA.<http://www.idsia.ch/> Since age 15 or so, Prof. Jürgen Schmidhuber’s main scientific ambition has been to build an optimal scientist through self-improving Artificial Intelligence (AI), then retire. He has pioneered self-improving general problem solvers since 1987, and Deep Learning Neural Networks (NNs) since 1991. The Long Short-Term Memory (LSTM) recurrent NNs (RNNs), developed by his research groups at the Swiss AI Lab IDSIA & USI & SUPSI & TU Munich, were the first RNNs to win official international contests. LSTM recently helped to improve connected handwriting recognition, speech recognition, machine translation, optical character recognition, image caption generation, and are now in use at Google, Microsoft, IBM, and many other companies. IDSIA’s Deep Learners were also the first to win object detection and image segmentation contests, and achieved the world’s first superhuman visual classification results, winning nine international competitions in machine learning & pattern recognition (more than any other team). Since 2009 he has been member of the European Academy of Sciences and Arts. He has published over 300 peer-reviewed papers, earned seven best paper/best video awards, and is recipient of the 2013 Helmholtz Award of the International Neural Networks Society. ________________________________ 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. Call for Special Sessions:<http://innsbigdata.org/special-sessions/> * Deadline: January 22, 2015 * Any proposal can be sent by e-mail to: INNSBigData2015SpecialSessions(a)gmail.com<mailto:INNSBigData2015SpecialSessions@gmail.com> Call for Tutorials<http://innsbigdata.org/tutorials/> and Workshops:<http://innsbigdata.org/workshops/> * Deadline: January 22, 2015 * Any questions can be sent to the Tutorials & Workshops 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>. ________________________________ [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. ________________________________ 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. She is a Member of the U.S. National Academy of Sciences, and a Fellow of the American Academy of Arts and Sciences. [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. ________________________________ [http://innsbigdata.org/wp-content/uploads/2014/09/new.gif]TUTORIALS & WORKSHOPS: TUTORIALS * Deep Learning - Profs. Juergen Schmidhuber<http://people.idsia.ch/~juergen/> (University of Lugano<http://www.inf.usi.ch/index.htm>, and the Swiss AI Lab IDSIA<http://www.idsia.ch/>) and Dong Yu<http://research.microsoft.com/en-us/people/dongyu/> (Microsoft Research<http://research.microsoft.com/en-us/>) * Introduction to How Brain Deals with Big Data - Juyang Weng<http://www.cse.msu.edu/~weng/> (Michigan State University<http://www.msu.edu/>) * Platforms and Algorithms for Big Data Analytics - Prof. Chandan K. Reddy<http://www.cs.wayne.edu/~reddy/> (Wayne State University<http://wayne.edu/>) * Big Data Analytics, Machine Learning Cognitive Algorithms and the Mind - Prof. Leonid I. Perlovsky<http://www.northeastern.edu/cos/psychology/people/faculty/> (Northeastern University<http://www.northeastern.edu/>) * Spiking Neural Networks and Neuromorphic Spatio-Temporal Data Machines - Prof. Nikola Kasabov <http://www.aut.ac.nz/profiles/nikola-kasabov> (Auckland University of Technology<http://www.aut.ac.nz/>) * Online Learning for Big Data Analytics - Prof. Irwin King<https://www.cse.cuhk.edu.hk/irwin.king.new/> (Chinese University of Hong Kong<http://www.cuhk.edu.hk/english/index.html>) WORKSHOPS * Deep Learning - Profs. Juergen Schmidhuber<http://people.idsia.ch/~juergen/> and Dong Yu<http://research.microsoft.com/en-us/people/dongyu/> * Neuromorphic Spatio-Temporal Big Data Machines - Prof. Nikola Kasabov <http://www.aut.ac.nz/profiles/nikola-kasabov> * Neural networks and wearable devices - Prof. Danilo Mandic<http://www.commsp.ee.ic.ac.uk/~mandic/> * Big Data and Power Systems - Profs. Dejan Sobajic and Kumar Venayagamoorthy * Crowd Behaviour and Big Data - Profs. Chrisina Jayne and Mehmed Kantardzic ________________________________ 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>. ________________________________ 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!! ________________________________ 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.

Jan. 14, 2015

RLDM2015: Abstract submissions deadline in one month!

by Yael Niv

The 2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2015) www.rldm.org<http://www.rldm.org/> June 7-10, The University of Alberta, Edmonton, Alberta, Canada ====================================================== Submissions to RLDM2015 are now being accepted at https://cmt.research.microsoft.com/RLDM2015 Deadline: 13 February 2015, midnight EST We invite extended abstracts for contributed poster presentations and oral presentations. We welcome submissions of original research related to “learning and decision making over time to achieve a goal”, coming from any discipline or disciplines, describing empirical results from human, animal or animat experiments, and/or theoretical work, simulations and modeling. Contributions should be aimed at an interdisciplinary audience, but not at the expense of technical excellence. This is an abstract-based meeting, with no published conference proceedings. As such, work that is intended for, or has been submitted to, other conferences or journals is also welcome, provided that the intent of communication to other disciplines is clear. Submissions should consist of a summary (max 2000 characters; text only), and an extended abstract of between one and four pages (including figures and references). LaTeX and RTF templates, and sample submissions, are available from http://rldm.org/rldm2015/submission-procedure/ Note: Only the summary will be made available in the (electronic) abstract booklets. The extended abstract will be used for reviewing, and will be available online only pending on authors’ separate explicit permission. Online availability will have no bearing on the review process and authors are encouraged to include new, unpublished, findings which they do not want to make publicly available. To submit your abstract please go to https://cmt.research.microsoft.com/RLDM2015 Submissions will be reviewed for relevance to the topic and for quality. Exceptional abstracts will be selected for oral presentations and for poster spotlight presentations. IMPORTANT DATES: Submissions open: 13 Dec 2015 Submissions close: 13 Feb 2015, 11:59pm EST Notification of acceptance: by March 28, 2015 (expedited reviewing for those needing an international visa can be requested) Early registration: 21 April 2015 Meeting: 7-10 June 2015, Edmonton, Alberta (*NEW* this year: Tutorials on the 7th) RLDM2015 Invited speakers: http://rldm.org/rldm2015/invited-speakers2015/ RLDM2015 Tutorials: http://rldm.org/rldm2015/tutorials/ RLDM2015 Programme Committee: http://rldm.org/rldm2015/committees/rldm2015-program-committee/ To ensure that you receive future announcements about RLDM2015 please join our mailing list at http://tinyurl.com/RLDMlist (you must log in to google to see the “join list” button, and choose “all email” from the options at the bottom).

Jan. 14, 2015

CFP: ICC'15 Workshop - 4th IEEE SCPA 2015 - June 8-12, 2015. London, UK

by Sandra Sendra

Apologies for crossposting -------------------- CALL FOR PAPERS (DEADLINE EXTENDED) ----------------- 4th IEEE International Workshop on Smart Communication Protocols and Algorithms (SCPA 2015) June 8-12, 2015. London, UK In conjunction with IEEE ICC 2015 http://scpa.it.ubi.pt/2015/ Selected papers will be invited to the Special Issue on Smart Protocols and Algorithms of the International Journal Network Protocols and Algorithms (ISSN 1943-3581) or to the Special Issue on Recent Patents on Telecommunications Journal ((Online)ISSN 2211-7415, (Print) ISSN 2211-7407) Communication protocols and algorithms are needed to communicate network devices and exchange data between them. The appearance of new technologies usually comes with a protocol procedure and communication rules that allows data communication while taking profit of this new technology. Recent advances in hardware and communication mediums allow proposing new rules, conventions and data structures which could be used by network devices to communicate across the network. Moreover, devices with higher processing capacity let us include more complex algorithms that can be used by the network device to enhance the communication procedure. Smart communication protocols and algorithms make use of several methods and techniques (such as machine learning techniques, decision making techniques, knowledge representation, network management, network optimization, problem solution techniques, and so on), to communicate the network devices to transfer data between them. They can be used to perceive the network conditions, or the user behavior, in order to dynamically plan, adapt, decide, take the appropriate actions, and learn from the consequences of its actions. The algorithms can make use of the information gathered from the protocol in order to sense the environment, plan actions according to the input, take consciousness of what is happening in the environment, and take the appropriate decisions using a reasoning engine. Goals such as decide which scenario fits best its end-to-end purpose, or environment prediction, can be achieved with smart protocols and algorithms. Moreover, they could learn from the past and ! use this knowledge to improve futur e decisions. In this workshop, researchers are encouraged to submit papers focused on the design, development, analysis or optimization of smart communication protocols or algorithms at any communication layer. Algorithms and protocols based on artificial intelligence techniques for network management, network monitoring, quality of service enhancement, performance optimization and network secure are included in the workshop. We welcome technical papers presenting analytical research, simulations, practical results, position papers addressing the pros and cons of specific proposals, and papers addressing the key problems and solutions. The topics suggested by the conference can be discussed in term of concepts, state of the art, standards, deployments, implementations, running experiments and applications. Topics of interest: Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal, including, but are not limited to, the following topic areas: - Smart network protocols and algorithms for multimedia delivery - Application layer, transport layer and network layer cognitive protocols - Cognitive radio network protocols and algorithms - Automatic protocols and algorithms for environment prediction. - Algorithms and protocols to predict data network states. - Intelligent synchronization techniques for network protocols and algorithms - Smart protocols and algorithms for e-health - Software applications for smart algorithms design and development. - Dynamic protocols based on the perception of their performance - Smart protocols and algorithms for Smartgrids - Protocols and algorithms focused on building conclusions for taking the appropriate actions. - Smart Automatic and self-autonomous ad-hoc and sensor networks. - Artificial intelligence applied in protocols and algorithms for wireless, mobile and dynamic networks. - Smart security protocols and algorithms - Smart cryptographic algorithms for communication - Artificial intelligence applied to power efficiency and energy saving protocols and algorithms - Smart routing and switching protocols and algorithms - Cognitive protocol and algorithm models for saving communication costs. - Any kind of intelligent technique applied to QoS, content delivery, network Monitoring and network management. - Smart collaborative protocols and algorithms - Problem recognition and problem solving protocols Genetic algorithms, fuzzy logic and neural networks applied to communication protocols and algorithms Important Dates Submission Deadline: 31st January, 2015 (FINAL DEADLINE - no further extensions) Acceptance Notification: 1st March, 2015 Camera Ready Deadline: 15th March, 2015 Submission guidelines: All submissions must be full papers in PDF format and uploaded on EDAS (http://edas.info/newPaper.php?c=18713) All submissions should be written in English with a maximum paper length of five (5) printed pages (10-point font) including figures without incurring additional page charges. General Chairs Jaime Lloret Mauri, Universitat Polit�cnica Val�ncia, Spain Joel Rodrigues, Instituto de Telecomunica��es, Univ. of Beira Interior, Portugal TPC Chairs Ivan Stojmenovic, University of Ottawa, Canada Guangjie Han, Hohai University, China Panel Chairs Honggang Wang, University of Massachusetts, USA Daqiang Zhang, Tongji University, China Industry Chairs Antonio S�nchez-Esguevillas, Telefonica R&D, Spain Neeraj Kumar, Thapar University, Patiala (Punjab), India Publicity Chair Sandra Sendra, Universitat Polit�cnica Val�ncia, Spain Web Chair Alejandro C�novas Solbes, Universitat Polit�cnica Val�ncia, Spain

Jan. 13, 2015

ECMLPKDD 2015: Call for Papers, Tutorials and Workshops

by ECMLPKDD 2015

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) will take place in Porto, Portugal, from September 7th to 11th, 2015 (http://www.ecmlpkdd2015.org) This event is the leading European scientific event on machine learning and data mining and builds upon a very successful series of 25 ECML and 18 PKDD conferences, which have been jointly organized for the past 14 years. ECMLPKDD 2015 will host three tracks, tutorials and a set of workshops. Therefore, we invite all researchers and practitioners from different communities to submit papers and/or present tutorial and workshop proposals. ************************* CALL FOR PAPERS ************************* JOURNAL TRACK ********************* Articles for this track are submitted all year long directly to either Machine Learning or Data Mining and Knowledge Discovery, and are reviewed like regular journal articles. Accepted articles appear in full in the journal and the authors are given a presentation slot at the conference. Articles deemed insufficiently mature for journal publication may be accepted for inclusion in the proceedings. Submissions to the journal track will be managed by the Guest Editorial Board. Paper Submission: Cut-off dates for the bi-weekly batches are 18 Jan, 1 Feb, 15 Fev, 1 Mar, 15 Mar, 29 Mar, 12 Apr, 26 Apr of 2015 Web Page: http://www.ecmlpkdd2015.org/submission/journal-track RESEARCH PROCEEDINGS TRACK ******************************************* The research proceedings track, which is organized in the traditional way. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/research-proceedings-track INDUSTRIAL, GOVERNMENTAL & NON-GOVERNMENTAL PROCEEDINGS TRACK **************************************************************************** ************************** The NEW industrial, governmental & non-governmental (NGO) proceedings track is independent and distinct from the Research Track. Submissions to this track should solve real-world problems and focus on engineering systems, applications, and challenges. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/industrial-proceedings-track ***************************************************************** CALL FOR TUTORIAL AND WORKSHOP PROPOSALS ***************************************************************** TUTORIALS ************** The tutorials are intended to provide a comprehensive introduction to established or emerging research topics of interest for the machine learning and the data mining community. These topics include related research fields or applications. The ideal tutorial should attract a wide audience. It should be broad enough to provide a basic introduction to the chosen research area, but it should also cover the most important topics in depth. We welcome half day workshop proposals. Proposal Deadline: March 2, 2015 Proposal Acceptance Notification: March 23, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/call-for-tutorials WORKSHOPS **************** The workshops will be on relevant and current topics in Machine Learning and Data Mining. The scope of the proposal should be consistent with the conference themes as described in the ECMLPKDD 2015 Call for Papers (http://www.ecmlpkdd2015.org/submission) Interdisciplinary workshops that bring together researchers and practitioners from different communities are especially welcome. We encourage workshops that bridge the gap between theoretical advances and important and/or innovative applications of machine learning and data mining. We welcome both full and half day workshop proposals. Proposal Deadline: March 2, 2015 Proposal Acceptance Notification: March 23, 2015 Workshop Websites and Call for Papers Online: March 27, 2015 Workshop Proceedings (Camera-ready): August 3, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/call-for-workshop-proposals Hope to see you all soon in Porto, Portugal!!! The publicity chairs of the ECMLPKDD 2015, Carlos Abreu Ferreira Ricardo Campos --- Este e-mail foi verificado em termos de vírus pelo software antivírus Avast. http://www.avast.com

Jan. 12, 2015

Fwd: Summer CAMP@Bangalore: Short course in Computational Approaches to Memory and Plasticity

by U.S.Bhalla

We would like to announce CAMP@Bangalore 2015 from 27 June 2015 to 12 July 2015. Please see the course website at http://camp.ncbs.res.in/ CAMP @ Bangalore (Computational Approaches to Memory and Plasticity at NCBS, Bangalore) is a 16-day summer school on the theory and simulation of learning, memory and plasticity in the brain. The course will start with remedial tutorials on neuroscience / math / programming and then work upwards from sub-cellular electrical and chemical signaling in neurons, onward to micro-circuits and networks, all with an emphasis on learning, memory and plasticity. Students worldwide are encouraged to apply. Accommodation and food will be free for the selected students. There is no registration fee. Students are advised to obtain independent travel grants. Instructors include: Ad Aertsen (Bernstein Center, Freiburg) Dan Johnston (UT-Austin) Sumantra Chattarji (NCBS, Bangalore) Suhita Nadkarni (Indian Institute of Science Education and Research, Pune) Michael Hausser (University College, London) Stefano Fusi (Columbia University, New York) Raghav Rajan (Indian Institute of Science Education and Research, Pune) Eric DeWitt (Champalimaud, Lisbon) Mohan Raghavan (Indian Institute of Technology, Hyderabad) Course Organizers: Upinder Bhalla (NCBS, Bangalore) Arvind Kumar (KTH Stockholm) Rishikesh Narayanan (Indian Institute of Science, Bangalore) Thank you, Upi Bhalla

Jan. 12, 2015

Postdoctoral positions in computational neuroscience at Wright State University

by Sherif Elbasiouny

*_Postdoctoral positions in computational neuroscience_* Two postdoctoral Fellow positions in Computational Neuroscience are available immediately in the laboratory of Dr. Sherif Elbasiouny (/T//he Neuro Engineering, Rehabilitation, and Degeneration Lab/) at the Department of Neuroscience, Cell Biology, and Physiology, Wright State University, Dayton, Ohio. The research work involves the development of anatomically detailed computational models of neurons in the spinal cord to investigate the basis of their neuronal excitability. Dr. Elbasiouny’s lab is currently investigating the ionic mechanisms underlying motoneuron function for neurorehabilitation applications and in neurodegenerative diseases, such as amyotrophic lateral sclerosis. *Required*: The successful applicant should have: 1) a PhD in computational neuroscience, engineering, computer science, mathematics, or related areas, 2) previous research experience in computational neuroscience. *Desired*: Although not mandatory, it is it highly desirable if the applicant has: 1) experience in the development of anatomically detailed computational models of single cells, and 2) experience in using the NEURON simulation environment. The positions are available immediately. The salary package is competitive and will be based upon the applicant’s experience. Funding for these positions is available for couple of years with possible extension upon research progress. Qualified applicants should email Dr. Elbasiouny at sherif.elbasiouny(a)wright.edu <mailto:sherif.elbasiouny@wright.edu>with the following: 1) CV including a list of publications, 2) a brief statement of research interests, and 3) three recommendation letters emailed directly by the references to Dr. Elbasiouny.For full consideration, please apply before March 1, 2015. Wright State University is an Equal Opportunity/Affirmative Action Employer. It is the university's policy to prohibit discrimination and provide equal opportunity to all employees and applicants for employment, without regard to their race, sex (including gender identity/expression), color, religion, ancestry, national origin, age, disability, veteran status, military or sexual orientation. Regards, Sherif Elbasiouny -- Sherif M. Elbasiouny, PhD, PE Assistant Professor Departments of Neuroscience, Cell Biology, & Physiology (NCBP) and Biomedical, Industrial & Human Factors Engineering (BIE) Wright State University 143 Biological Sciences II (mail) 243 Biological Sciences II (lab) 251B Biological Sciences II (office) 3640 Col Glenn Hwy Dayton OH 45435 Office Phone: 937-775-2492 https://www.med.wright.edu/ncbp/elbasiouny

Jan. 12, 2015

MOOSE 3.0.1 "Gulab Jamun"

by U.S.Bhalla

We announce the release of MOOSE 3.0.1 "Gulab Jamun" The Gulab Jamun release is the second in series 3 of MOOSE releases. Websites: http://moose.ncbs.res.in, http://sourceforge.net/projects/moose MOOSE is the Multiscale Object-Oriented Simulation Environment. It is designed to simulate neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, circuits, and large networks. MOOSE can operate at many levels of detail, from stochastic chemical computations, to multicompartment single-neuron models, to spiking neuron network models. MOOSE 3.0.1 is an evolutionary increment over 3.0.0:: - The GUI moves into beta with substantially more kinetic modeling features, as well as an early release of the neuronal modeling interface in the GUI. - Multiscale modeling updates including better cross-compartment reaction support, including stochastic reactions in subsets of the compartments. - General robustness and error reporting improvements for solvers. - HSolver updates to handle NMDA and derived classes of channels with Ca currents. - Better release packaging About the name: Gulab Jamun is a classic North Indian sweet consisting of deep brown spheres involving milk solids, cardamom and other spices, floating in a rich syrup. Best wishes and Happy New Year, The MOOSE team: Harsha Rani, Aviral Goel, Dilawar Singh, Aditya Gilra, Subhasis Ray, Upi Bhalla

Jan. 11, 2015

tenure-track faculty position - Assistant Professor - Systems biology and Alzheimer's disease

by Christopher Gaiteri

tenure-track faculty position - Assistant Professor - Systems biology and Alzheimer's disease Make creative analytic contributions to understanding Alzheimer's disease at Rush University, a major center for aging and age-related disease research, located in Chicago, IL. Our Alzheimer's center offers an integrated clinical and research environment that has a constantly growing collection of multi-omic data on hundreds of individuals, at various ages and levels of cognitive function. These omics data can be studied against a backdrop of hundreds of cognitive and behavioral phenotypes that are tracked longitudinally in these subjects and thousands of others. We are searching for a tenure-track assistant professor to construct and contribute to systems biology models that enhance our understanding of age-related dysfunction and Alzheimer's disease. These models should lead to actionable, molecular or tissue-level predictions, which can be tested in experimental systems. Requirements: MD/PhD or PhD in Neuroscience, Mathematics, Systems Biology or related fields Experience with omics and big data, including any or ideally all of: structural and functional neuroimaging, proteomics, RNAseq, genetics and methylation Expertise in R, matlab and python Interests in network-based analysis of disease-related data Preference for: Publication history in graph theory, systems biology and neuroscience Familiarity with complex disease neurobiology Experience in design and implementation of large-scale cellular simulations Java, perl, parallel programming and batch execution systems Experience designing or performing high-throughput experiments Post-doctoral training The ideal candidate is free to develop an independent research program around aging, age-related disease and/or systems biology analysis. He/she will also collaborate with current faculty and develop and maintain external funding. Salary commensurate with relevant experience and skills. Instructions for applying: Send your CV to gaiteri(a)gmail.com AND ALSO include a paragraph on one of the following topics: 1. How will you identify key pathological mechanisms in a multi-omic disease setting, potentially in collaboration with experimental labs? 2. How will you develop multi-modal or multi-scale models of complex brain diseases? 3. What is the most under-appreciated statistical or mathematical technique that you expect could lead to insights in brain diseases?

Jan. 11, 2015