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Position in computational neuroanatomy at the Allen Institute

by Nuno da Costa

Dear comp-neuro list members, We are seeking a scientist to work on the analysis of large scale electron microscopy datasets and to investigate the relationship between structure and function of cortical networks. The scientist will be an essential member of the Neural Coding team studying the relationship between neural circuits and neural dynamics by combining in vivo functional imaging with ex vivo state of the art Electron Microscopy in the visual cortex of mice. If you are interested on know of someone that is interested, the application link is: https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=639564&… Many thanks and kind regards Nuno Nuno Macarico da Costa Assistant Investigator T: 206.548.8437 [cid:image001.png@01D356E8.F5D70FF0] www.alleninstitute.org<http://www.alleninstitute.org/>

Nov. 6, 2017

postdoc in statistical neuroscience of human language

by xaq pitkow

Postdoctoral research position in neuroscience of Human Language POSITION: We seek a highly motivated postdoctoral research fellow for a collaborative team project interpreting intracranial recordings from human patients during language tasks. The fellow will apply statistical models to this neural data, and will help develop a dynamic network model of language. TEAM: The fellow will collaborate primarily with Houston-based neurotheorist Xaq Pitkow (xaqlab.com) and neurosurgeon Nitin Tandon (tandonlab.org) and our labs, and will also interact with other team members including Nathan Crone, Stan Dehaene, and Greg Hickok. The fellow will be a member of the new Center for Neuroscience and Artificial Intelligence housed at the Baylor College of Medicine. The Center brings together interdisciplinary researchers from across Houston, including members from Baylor College of Medicine, Rice University, University of Houston, and University of Texas Health Sciences. Researchers at the Center contribute diverse expertise in fields including neuroscience, machine learning, statistics, physics, computer science, electrical engineering, and applied mathematics. QUALIFICATIONS: Candidates must have outstanding mathematical skills, a PhD in a relevant quantitative discipline, expertise in statistical machine learning, and interest in language processing. APPLYING: Applicants should email a letter of research interests and CV to Xaq Pitkow (xaq(a)rice.edu) along with contact information for three references. We look forward to hearing from you!

Nov. 6, 2017

Call for Participation: IEEE Brain Data Bank Competition – Boston

by Sam Michalka

*Call for Participation: IEEE Brain Data Bank Competition – Boston* The IEEE Brain Initiative is sponsoring several challenges and competitions in 2017 to explore various brain/neuro datasets. You are cordially invited to explore the data and register for this competition in Boston on December 9th 9:45 AM – 4 PM. For more information about the event and how to register, please visit https://brain.ieee.org/news/call-participation-ieee-brain- data-bank-challenge-boston/ *Location* Charles River Analytics 625 Mt. Auburn St. <https://maps.google.com/?q=625+Mt.+Auburn+St.+%0D+Cambridge,+MA,+USA&entry=…> Cambridge, MA, USA Organizers * Seth Elkin-Frankston, Charles River Analytics * Sam Michalka, Olin College of Engineering * Wasim Q. Malik, Harvard/MIT If you have questions, please contact bdb-boston(a)ieee.org *Purpose* The aim of the competition is to bring a diverse group of individuals of varying backgrounds and experience together to analyze, visualize, and evaluate complex datasets. Competitors will have access to a multi-modal dataset that will challenge individuals with varying backgrounds in data science, computer science, biology, or neuroscience. Results will be evaluated on analytic approach, visualization, and final presentation and interpretation. *Background* Datasets are provided by the University of Illinois at Urbana–Champaign and were collected as part of a broader intervention-based study designed to test the effects of efficacy of interventions designed to enhance fluid intelligence. This study was one of several funded as part of the Strengthening Human Adaptive Reasoning and Problem-solving (SHARP< https://www.iarpa.gov/index.php/research-programs/sharp>) program at the Intelligence Advanced Research Projects Activity (IARPA< https://www.iarpa.gov/>). This specific intervention involved 48 training sessions of an adaptive visuo-spatial and change detection task. We provide both behavioral measures and neuroimaging data at pre- and post-intervention time points. We also provide summary and session-level descriptions of the training data collected during the intervention. *Challenge Questions* The goal of this challenge is to encourage thoughtful investigation and discussion around enhancement of human intelligence and strategies for rigorous investigation of these topics. Entries will be judged in three categories: data analysis, data visualization, and presentation and interpretation of findings. Participants can investigate any question(s) about the data that they wish. The following guiding questions are provided as a jumping off point: * Can intervention training predict changes in pre- and post-intervention performance? * How do measures of brain connectivity and structure relate to performance in intervention training? * How do measures of brain connectivity and structure relate to pre- and post-intervention performance? * How well can we predict post-intervention performance? Beyond pre-intervention performance, what factors serve as the best predictors? * Do performance changes on the two training intervention tasks differ? How do they each relate to changes in pre- and post-intervention performance and/or imaging data? *Data* Data is hosted by the IEEE Dataport<https://ieee-dataport.org/competitions/ ieee-brain-data-bank-competition-boston-ma>. To access IEEE Dataport, you need to have an IEEE account. You do not need to be an IEEE member to create an IEEE account, and you can use your own email address to create an account and password. Click here to sign up for an IEEE account.< https://www.ieee.org/profile/public/createwebaccount/showRegister.html> The full dataset is 11.29GB. The dataset can be downloaded in full, or in more manageable chunks separated as: * Behavioral and analyzed fMRI/DTI data * Structural T1 images * Raw resting-state fMRI data (divided in 5 file groups) * Raw DTI data Please note that access from IEEE DataPort will be granted after you have completed an access request. *Judging* Judges will include experts from Industry, Government, and Academia. Entries will be judged in three categories: * Data analysis including well-justified, innovative, and rigorous methodologies * Data visualization including novel, highly informative, and aesthetically appealing visualization techniques * Presentation and interpretation of findings including clear, informative delivery and compelling investigation and interpretation *Awards* IEEE Brain will sponsor cash awards. More details will follow.

Nov. 5, 2017

from normal learning and recognition to Alzheimer's disease

by Stephen Grossberg

Dear Colleagues, I am writing to call your attention to the following article because the neural model that it describes links normal category learning and recognition to clinical disorders such as autism and Alzheimer’s disease, topics that are currently of great interest and concern. The clinical links emerged after the neural dynamics of vigilance control during normal category learning was sufficiently understood. Grossberg, S. (2017). Acetylcholine neuromodulation in normal and abnormal learning and memory: Vigilance control in waking, sleep, autism, amnesia, and Alzheimer’s disease. Frontiers in Neural Circuits, November 2, 2017, https://doi.org/10.3389/fncir.2017.00082 <https://doi.org/10.3389/fncir.2017.00082> Best, Steve Stephen Grossberg http://en.wikipedia.org/wiki/Stephen_Grossberg <http://en.wikipedia.org/wiki/Stephen_Grossberg> http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en <http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en>https://youtu.be/9n5AnvFur7I <https://youtu.be/9n5AnvFur7I> Wang Professor of Cognitive and Neural Systems Professor of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Director, Center for Adaptive Systems http://cns.bu.edu/~steve <http://cns.bu.edu/~steve> steve(a)bu.edu <mailto:steve@bu.edu>

Nov. 4, 2017

Fw: two postdoctoral positions in the Canavier Lab

by Canavier, Carmen C.

The contact information for these positions has been updated. Please contact Carmen Canavier ccanav(a)lsuhsc.edu with any questions. Two Postdoctoral Researcher positions are available in the computational neuroscience lab of Carmen Canavier in the School of Medicine, Department of Cell Biology and Anatomy at LSU Health Sciences Center in New Orleans. The primary duties will involve linear and non-linear analyses, writing code, calibrating single neuron models, and generating predictions that lead to additional experiments. Candidates must have a Ph.D. in Neuroscience, Engineering, Mathematics, Physics, Computer Science or a related field of study. The ideal candidate would have experience with the simulation package NEURON and some knowledge of the basal ganglia for the first position and of the hippocampus for the second position. Familiarity with nonlinear dynamics, signal processing, and coding in C and or python in a Linux environment is also desirable. The first position is to study the dynamic diversity of midbrain dopamine neurons in close collaboration with electrophysiologist Jochen Roeper at Goethe University in Frankfurt, Germany. The successful candidate will construct morphologically and biophysically realistic models of distinct subpopulations of dopamine neurons to account for experimentally observed differences in their bursting and pacemaking dynamics. These simulations will require in some cases incorporation of stochastic channel models and second messenger cascades. Qualified candidates may submit resume along with cover letter and contact information for three references electronically to: https://www.lsuhsc.edu/Administration/hrm/CareerOpportunities/Home/Detail/1…. The second position is to study cholinergic contributions to hippocampal information processing in close collaboration with electrophysiologist Sonia Gasparini. The successful candidate will construct a morphologically and biophysically realistic model of a hippocampal CA1 pyramidal neuron to explain the observed frequency selectivity of different dendritic regions for slow versus fast gamma band inputs. Some network modeling will also be required for the project. Qualified candidates may submit resume along with cover letter and contact information for three references electronically to: https://www.lsuhsc.edu/Administration/hrm/CareerOpportunities/Home/Detail/1… LSUHSC is an Equal Opportunity Employer for females, minorities, individuals with disabilities and protected veterans.

Nov. 3, 2017

Late Bird call for the AoN Brainhack Warsaw [17-19th November 2017]

by Daniel Borek

*AoN Brainhack Warsaw 2017* *November 17-19, 2017* *University of Warsaw, Warsaw, Poland* *— The blitz Late Bird registration open until 7th November 2017 —* On the weekend of *17-19th November 2017*, the first edition of AoN Brainhack Warsaw will take place. During this three-day event dedicated to students and PhD students, we will work in teams on* neuroscience-related projects*. The aim of the event is to meet new, enthusiastic researchers, make new friendships in academia, learn, share the knowledge on data mining and brain research, but also promote open science in the spirit of the whole Brainhack community ( <https://gigascience.biomedcentral.com/articles/10.1186/s13742-016-0121-x> Craddock et al., 2016) <https://gigascience.biomedcentral.com/articles/10.1186/s13742-016-0121-x>. Attendees of various backgrounds are welcome to join! At the moment we are opening the Late Bird registration for project participants, which closes on 7th November 2017. Some of the projects got fully booked already and since they have limitations in terms of the number of participants, these projects have been closed for this round of registration. Please look at the list of the currently available projects : - Functional connectivity research: can we find a common ground? <https://brainhackwarsaw.github.io/#connectivity> - Development of video game for studying joint action dynamics <https://brainhackwarsaw.github.io/#game> - Hypothesis-driven white matter tractography from T1-weighted MRI images <https://brainhackwarsaw.github.io/#whitematter> - One channel EEG sleep staging with open source and open hardware NeuroOn sleep mask <https://brainhackwarsaw.github.io/#neuroon> - Building and using the “FlyPi”: the 3D-printed Neurobiology Lab <https://brainhackwarsaw.github.io/#flypi> - Unfolding the Subcortex <https://brainhackwarsaw.github.io/#subcortex> *All the applications which we received after the end of Early Bird phase, will be automatically considered as the Late Bird applications.* The applications will be reviewed and the notification of acceptance will be sent to the applicants until 10th October2017. A registration fee of *30EUR* (or 120PLN) will be requested upon acceptance. The registration fee will be spent on the catering during the event. In order to register, please visit our website and learn more about AoN Brainhack Warsaw! https://brainhackwarsaw.github.io/ <https://brainhackwarsaw.github.io/> We are looking forward to see you in Warsaw! *The AoN Brainhack Warsaw 2017 team*

Nov. 2, 2017

Faculty position in Math Biology at NJIT

by Victor Matveev

Dear comp-neuro list members, The Department of Mathematical Sciences (DMS) at New Jersey Institute of Technology (NJIT) invites applications for a tenure-track position at the assistant professor level in mathematical biology. A second DMS tenure-track assistant professor position in the broader area of applied mathematics is advertised separately (links provided below). The appointment is to start in Fall 2018. Candidates should have a Ph.D. in mathematics, applied mathematics or a related discipline, with an established record of independent research, strong potential for seeking external research support, and a commitment to teaching at graduate and undergraduate levels. Candidates working in any subfield of mathematical biology will be given consideration. Currently, members of the DMS mathematical biology group are engaged in research in computational neuroscience, biological rhythms, biofluids and mechanosensing. To apply, please visit https://njit.csod.com/ats/careersite/JobDetails.aspx?site=1&id=35 The second position in applied mathematics is advertised separately at https://njit.csod.com/ats/careersite/JobDetails.aspx?site=1&id=30 Submissions must include (a) cover letter, (b) resume/CV, (c) research statement, (d) teaching statement, and (e) names and contact information for at least four references. Review of applications will begin immediately and will continue until the position is filled. Please direct any questions to the search committee chair, Victor Matveev, at matveev(a)njit.edu. DMS is recognized for its strong program in applied mathematics, which offers B.S., M.S., and Ph.D. degrees, with Ph.D. program tracks in applied mathematics as well as in applied probability and statistics. NJIT is in the University Heights neighborhood next to vibrant downtown Newark, about 12 miles west of New York City. The NJIT campus is adjacent to the campus of Rutgers-Newark, with which it shares several academic programs. DMS has close collaborative ties to the Department of Biological Sciences at NJIT. Excellent potential for outside collaboration is also afforded by the close geographic proximity of NJIT to other prominent centers for biological research such as the Center for Molecular and Behavioral Neuroscience at Rutgers-Newark, New Jersey Medical School, NYU, Columbia University, and Rockefeller University. Apart from mathematical biology, DMS faculty work in diverse fields of applied mathematics including fluid dynamics, granular matter, nonlinear waves, applied analysis, scientific computing, dynamical systems, and probability and statistics. NJIT is an Equal Opportunity / Affirmative Action Employer and strongly encourages women, minorities, and persons with disabilities to apply. -- ___________________________________ Victor Matveev, Professor Applied Math, Biophysics & Neuroscience Department of Mathematical Sciences Graduate Faculty, Dept of Biological Sciences New Jersey Institute of Technology Newark, NJ 07102-1982 Office: Cullimore Hall 616 E-mail: matveev(a)njit.edu http://web.njit.edu/~matveev/

Nov. 2, 2017

Post-doctoral Position in Computational Neuroscience

by sujith vijayan

*Post-doctoral Position in Computational* *Neuroscience* The Neural Dynamics and Neural Engineering Lab at Virginia Tech has an opening for a post-doctoral position in computational neuroscience. This position is for three years and is being funded by the Army Research Office (ARO). The research project will involve employing biophysically based computational models to examine the role of rhythmic activity in the expression of emotional memories during behavior and their consolidation during sleep. An additional aim is to employ the newly developed models to gain insight into the pathophysiology of post-traumatic stress disorder (PTSD). Our lab investigates neural dynamics during active behavior and during off-line states, such as sleep, using a combination of computational modeling, signal processing techniques, and both invasive and non-invasive techniques for recording neural activity. The basic science knowledge gathered from these investigations is leveraged to understand how memories are instantiated in the brain, to gain insight into how learning occurs during brain machine interface (BMI) tasks, to improve BMI algorithms, and to develop the framework for stimulation and pharmacological therapies for diseases, especially those marked by abnormal neural dynamics during sleep (e.g., post-traumatic sleep disorder (PTSD) and Parkinson’s disease). Please see the lab website (www.vijayan.neuroscience.vt.edu) for more details. Candidates should have a Ph.D. in applied mathematics, computer science, engineering, neuroscience, psychology, or a related field. Strong programming skills and/or prior experience in modeling would be an asset. Interested candidates should send a CV, a statement of research interests, and the contact information for three references to svijayan9(a)gmail.com. Arrangements can be made to meet with candidates at the Society for Neuroscience conference in Washington, D.C. Sujith

Nov. 2, 2017

Submission deadline extended for the 15th International Multi-Conference on Systems, Signals and Devices SSD' 2018

by Nabil Derbel

This email is a reminder for submitting your proposition to SSD'18 Our apologies if you receive multiple copies of this message. Dear Colleagues, <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=622c400fe7&e=415348fdfa> 15th International Multi-Conference on <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=5b2423bda6&e=415348fdfa> Systems, Signals and Devices SSD' 2018 March 19-22, 2018, Hammamet-Tunisia The International Multi-Conference on Systems, Signals and Devices 2018 will be held on March 19-22, 2018 in Hammamet - Tunisia. The SSD′2018 conference is an international forum dedicated to researchers and specialists in different fields of electrical engineering. It brings together scientists and practitioners from research organizations, universities and companies in a multidisciplinary event, with the aim of strengthening links between researchers of different specialties. This event will provide the opportunity to share together the latest achievements in systems and control. Both theoretical and applied papers are welcomed for submission to this event. Accepted and presented papers during the conference will be published in IEEEXplore. Authors of best papers presented at SSD conference will be offered an opportunity to publish their works in followed international books and in the following international journals: *Advances in Systems, Signals and Devices (ISSN 2365-7507, published by De Gruyter) *International Journal of Digital Signals and Smart Systems (ISSN 2389-0311, Inderscience). We would invite you to submit your recent research via SSD′2018 website ( <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=ba2f080a77&e=415348fdfa> Submission), or directly through EDAS the manager of the conference <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=51f907b252&e=415348fdfa> http://edas.info/N24004. In order to give more success to our Conference, I will be so grateful if you diffuse the Call for Papers of SDD′2018 and the website URL ( <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=abb75c66e2&e=415348fdfa> Call_for_Papers_SDD 2018) to your colleagues and Email contacts. The important dates are: Deadline for paper submission: November 30th, 2017. Notification of Acceptance: January 15th, 2018. Final paper manuscripts: January 31th, 2018. To write your paper, please respect the IEEE templates for LATEX formats or Microsoft Word that may be found at: <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=85b8beb6c0&e=415348fdfa> http://www.ieee.org/ conferences_events/ <https://the-it-expert.us12.list-manage.com/track/click?u=65343825ebc55cbfc5 5959332&id=8fe8bcc4c7&e=415348fdfa> conferences/publishing/ templates.html Best Regards For the organization committee

Nov. 1, 2017

[INNS-BDDL 2018] Call for Papers

by Teng Teck Hou

[Apologies for cross-postings] ########################################################### CALL FOR PAPERS The 3rd INNS Conference on Big Data and Deep Learning 2018 April 17-19, 2018, Bali, Indonesia Homepage: http://www.innsbigdata2018.org #######################Description:###################### The International Neural Network Society (INNS) is the premiere organization for individuals interested in a theoretical and computational understanding of the brain and applying that knowledge to develop new and more effective forms of machine intelligence. INNS was formed in 1987 by the leading scientists in the neural network field. Researchers and colleagues who work in the area of big data and machine learning, we are happy to announce "The 3rd INNS Conference on Big Data and Deep Learning (INNS BDDL) will be held Tuesday through Thursday, April 17 – 19, 2018 at the Grand Inna Bali Beach hotel, Sanur, Bali, Indonesia. The INNS BDDL conference aims to create a valuable and important forum for scientists and engineers throughout the world to present the latest research findings and idea at the forefront of Big Data and Deep Learning." Accepted and presented papers will be published in Procedia Computer Science indexed by Scopus. Several papers will be selected for possible publication in a high-quality journal. A preliminary list of such journals includes: - Cognitive Systems Research (Scopus SJR 0.648, Impact Factor 1.182) - Cognitive Computation (Scopus SJR 0.823, Impact Factor 3.441) - Big Data Analytics - Evolving Systems (Scopus SJR 0.459, Impact Factor 1.067) - International Journal of Neural Systems (Scopus SJR 1.121, Impact Factor 6.333) - and possibly others Several papers will be selected for possible publication in top journals. The conference will feature a comprehensive technical program with technical tracks on: Track 1: Big Data Track 2: Big Data Algorithms Track 3: Deep Learning Track 4: Application Areas ####################Important Dates################################# * Tutorial and workshop proposals (Submission) 30 September 2017 * Tutorial and workshop proposals (Decision) 7 October 2017 * Paper submission 1 December 2017 * Decision notification 8 January 2018 * Camera-ready submission 2 February 2018 * Conference 17 - 19 April 2018 ################################################################### #########################Keynote Speakers########################## * Geoffrey I. Webb, Monash University, Australia * Kay Chen Tan, City University, Hong Kong * Ari Santoso, Ministry of Education and Culture ################################################################### #################### Organizing committees ############### General chairs Seiichi Ozawa, Kobe University, Japan Ah-Hwee Tan, Nanyang Technological University, Singapore Program Chairs Plamen P. Angelov, Lancaster University, UK Asim Roy, Arizona State University, USA Mahardhika Pratama, Nanyang Technological University, Singapore Honorary Board Mohammad Nuh, Institut Teknologi Sepuluh Nopember, Indonesia Joni Hermana, Institut Teknologi Sepuluh Nopember, Indonesia Heru Setyawan, Institut Teknologi Sepuluh Nopember, Indonesia Local Committee Chairs Dieky Adzkiya, Institut Teknologi Sepuluh Nopember, Indonesia Advisory Board Yew-Soon Ong, Nanyang Technological University, Singapore Robert Kozma, University of Memphis, USA Sankar K. Pal, Indian Statistical Institute, India Haibo He, University of Rhode Island, USA Witold Pedrycz, University of Alberta, Alberta, Canada Leszek Rutkowski, Czestochowa University of Technology, Poland Nikola Kasabov, Auckland University of Technology, New Zealand Fernando Gomide, University of Campinas, Brazil Marley Vellasco, Pontifícia Universidade Católica do Rio de Janeiro, Brazil Yoonsuck Choe, Texas A&M University Minho Lee, Kyungpook National University, South Korea Bao-Liang Lu, Shanghai Jiao Tong University, China Irwin King, the Chinese University of Hong Kong, Hong Kong Tutorials/Workshop Chairs Igor Skrjanc, University of Ljubljana, Slovenia Sundaram Suresh, Nanyang Technological University, Singapore Noor Akhmad Setiawan, Universitas Gadjah Mada, Indonesia Poster Sessions Chairs Eko Setiadji, Institut Teknologi Sepuluh Nopember, Indonesia Agus Salim, La Trobe University, Australia Ali Ridho Barakbah, Politeknik Elektronika Negeri Surabaya, Indonesia Special Sessions Chairs Justin Wang, La Trobe University, Australia Yongping Pan, National University of Singapore, Singapore Alfian Futhul Hadi, Universitas Jember, Indonesia Panel Chairs Sreenatha Anavatti, University of New South Wales, Australia Mukesh Prasad, University of Technology, Sydney, Australia Achmad Affandi, Institut Teknologi Sepuluh Nopember, Indonesia Awards Chairs Tapabrata Ray, University of New South Wales, Australia Dejan Dovzan, University of Ljubljana, Slovenia Richard J. Oentaryo, McLaren Applied Technologies, Singapore Publication Chairs Edwin Lughofer, Johannes Kepler University, Austria Jose Antonio Iglesias, Carlos III University of Madrid, Spain Moamar Sayed?Mouchaweh, Institute Mines Telecom Lille Douai, France Publicity Chair Simone Scardapane, Sapienza University, Italy Teng Teck Hou, Singapore Management University, Singapore Kurnianingsih, Politeknik Negeri Semarang, Indonesia International Liaison Chairs Yun Sing Koh, University of Auckland, New Zealand Deepak Puthal, University of Technology Sydney, Australia Wirawan, Institut Teknologi Sepuluh Nopember, Indonesia Webmaster Mohamad Abdul Hady, Institut Teknologi Sepuluh Nopember, Indonesia Andri Ashfahani, Institut Teknologi Sepuluh Nopember, Indonesia Choiru Za’in, La Trobe University, Australia ########################################################## ###### Topics and Areas include, but not limited to the following###### >>BIG DATA Autonomous, online, incremental learning in big data High dimensional data, feature selection, feature transformation for big data Scalable algorithms for big data Big data analytics Data stream analytics Parallel & distributed computing for big data analytics (cloud, map-reduce, etc.) Online learning Online multimedia/stream/text analytics Link and graph mining Big data and cloud computing, large scale stream processing on the cloud Big data and collective intelligence/collaborative learning Big data and hybrid systems Big data and self-aware systems Big data and infrastructure Big data visualization >>Big Data Algorithm Neuromorphic hardware for scalable machine learning Evolving systems for big data analytics Evolutionary systems and big data Fuzzy systems and big data Cognitive modelling and big data Probabilistic approach for big data Concept drift detection for big data Granular computing for big data Transfer learning for big data >>Deep Learning Deep belief network Convolutional neural network Long short term memory Deep network architecture Deep autoencoder Deep stacked network Deep learning for natural language processing Deep learning for machine vision Evolving deep network Transfer learning in deep learning Online deep learning >>Application Areas Banking and Securities Communications, Media and Entertainment Healthcare Providers Education Manufacturing & Natural Resources Government Insurances Retail & Wholesale Trade Transportation Energy & Utilities, Etc. ############################################################################ ##########################Sponsoring Organizations################# * INNS - International Neural Network Society * MTC - Mechatronic Technology Center, Institut Tecknologi Sepuluh Nopember ################################################################ Previous INNS Conference: INNS 2016 in Thessaloniki, Greece INNS 2015 in San Francisco, USA

Nov. 1, 2017