December 2018 - Comp-neuro - lists.cnsorg.org

Creating a list of important computational predictions
by Yiota Poirazi Jan. 4, 2021

Jan. 4, 2021

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

2 1

[publication and call for dialog] IEEE CIS Newsletter on Cognitive and Developmental Systems
by Pierre-Yves Oudeyer Jan. 23, 2020

Jan. 23, 2020

Dear colleagues, we are happy to announce the release of the latest issue of the IEEE CIS Newsletter on Cognitive and Developmental Systems (open access). This is a biannual newsletter addressing the sciences of developmental and cognitive processes in natural and artificial organisms, from humans to robots, at the crossroads of cognitive science, developmental psychology, artificial intelligence, machine learning and neuroscience. It is available at: https://goo.gl/NAwBfD Featuring dialog: === "Curiosity as Driver of Extreme Specialization in Humans" == Dialog initiated by Celeste Kidd with responses from: Elizabeth Bonawitz, Maya Zhe Wang, Brian Sweis, Benjamin Hayden, Susan Engel, Abigail Hsiung, Shabnam Hakimi, Alison Adcock, Moritz Daum, Arjun Shankar, Tobias Hauser, Goren Gordon and Perry Zurn == Topic: Curiosity-driven learning is probably one of the most fundamental mechanisms in human learning, and yet it is also probably one of the least understood. Broadly construed as spontaneous exploration and engagement with activities or material without any extrinsic goal (as opposed to searching for information useful for an extrinsic goal), many mysteries remain to be uncovered. What are the causal links between curiosity and learning? How does prior knowledge about a topic or an activity relates to curiosity about this topic? What is the role of curiosity in life-span development? Can human curiosity explain the apparently unique tendency of humans for extreme specialization? Reversely, how do different forms of curiosity (diversive or specific) evolve as children grow up and become adults? While early computational models of curiosity propose theoretical approaches to understand their cognitive mechanisms, how can we understand the affective/ emotional dimensions of curiosity? And how has the linguistic concept of “curiosity” evolved in occidental culture? Call for new dialog: === « Leveraging Adaptive Games to Learn How to Help Children Learn Effectively" == Dialog initiated by George Kachergis == Topic: How can one achieve efficiently “translational educational sciences” and get these principles used in real-world large-scale educational technologies? In this dialog, Georges Kachergis highlights challenges related to collaborations between cognitive scientists and game developers, how to deploy real world experiments, and how to enable scientific understanding when many variables cannot easily be controlled? Those of you interested in reacting to this dialog initiation are welcome to submit a response by December 15th, 2018. The length of each response must be between 600 and 800 words including references (contact pierre-yves.oudeyer(a)inria.fr) Let us remind you that all issues of the newsletter are all open-access and available at: https://goo.gl/ZjjZNz I wish you a stimulating reading! Best regards, Pierre-Yves Oudeyer, Editor of the IEEE CIS Newsletter on Cognitive and Developmental Systems Research director, Inria Head of Flowers project-team Inria and Ensta ParisTech, France http://www.pyoudeyer.com Twitter: https://twitter.com/pyoudeyer and Fabien Benureau, Editorial Assistant Cognitive NeuroRobotics Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Okinawa Japan Email: fabien.benureau [at] oist [dot] jp

1 1

Postdoc positions on Consciousness Research at Monash Uni, Australia
by Naotsugu Tsuchiya Jan. 13, 2020

Jan. 13, 2020

Position A: DP180100396 (in collaboration with Masafumi Oizumi, Hiroto Kawasaki, Giulio Tononi) No report paradigm in EEG/MEG/intracranial recordings and the analysis of integrated information across sensory and prefrontal cortex Position B: DP180104128 (in collaboration with Marta Garrido, Ueli Rutishauser, Ralph Adolphs) The analysis of MEG/intracranial recordings, using Granger causality and integrated information We are looking for highly talented postdocs (application from PhD students with a prospect of getting PhD in 1 year are welcomed) for the above two ARC-funded positions. Ideal candidates in both positions would have strong publications, strong programming skills in Matlab/Python, strong background in data analysis, preferably neuroimaging data or neural spikes. The projects include 1) design of various psychophysical paradigms (*pdf <https://academic.oup.com/nc/article/doi/10.1093/nc/niw023/2970153/Are-we-un…>)*, including no-report paradigms (*pdf <https://drive.google.com/file/d/0B9N0ysU85rs7bEF5d1VVX3J4T3c/view>*), which can be used for subsequent EEG/MEG/intracranial recording experiments and 2) analysis of EEG/MEG/intracranial data using the approximations of integrated information (link1 <http://www.eneuro.org/content/4/5/ENEURO.0085-17.2017>, *link <https://drive.google.com/open?id=0B9N0ysU85rs7NFVSQlIza215eVU> *, *link <http://www.pnas.org/content/early/2016/12/02/1603583113.abstract>*, *link <http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.10046…>)* ). Please send the inquiry with your CV to naotsugu.tsuchiya(a)monash.edu. Applicants with most fit background and skills will be contacted for subsequent interview over the internet. The positions will be available until they are filled. Regards Nao Tsuchiya -- -- *Nao (Naotsugu) Tsuchiya* Associate Professor *Monash Institute of Cognitive and Clinical Neurosciences* Attention and Memory Program School of Psychological Sciences Monash University 770 Blackburn Monash Brain Imaging facility, Clayton, VIC 3800 Australia T: +61 3 9905 4564 E: naotsugu.tsuchiya(a)monash.edu W: homepage: http://users.monash.edu.au/~naotsugt/Tsuchiya_Labs_Homepage http://med.monash.edu.au/psych/email-sig/miccn-email-sig.jpg <http://www.monash.edu/neuro-institute/> 2. Visiting Researcher at Department of Dynamic Brain Imaging, Advanced Telecommunications Research (ATR), Japan 3. Visiting Researcher at CiNet, Osaka University, Japan orcid.org/0000-0003-4216-8701

1 2

Professorship in Artificial Intelligence
by Steuber, Volker May 8, 2019

May 8, 2019

Professor of Artificial Intelligence University of Hertfordshire, UK School of Computer Science, College Lane Campus, Hatfield Salary £58,293 to £64,397 pa dependent on skills and experience FTE: Full time position working 37 hours per week (1.0FTE) Duration of Contract: Permanent position Closing date: 3 September 2018 Applications are invited for an exceptionally well qualified Professor of Artificial Intelligence of international standing who shares our commitment to research-informed teaching, embraces the research impact agenda, and values collegiality. Applicants will strengthen existing activity within the School and develop it further, enhancing the research strengths and external reputation of the School of Computer Science and contributing significantly to its performance in future research assessments and collaborations with public and commercial partners. The successful applicant will connect to and complement the research conducted by the Adaptive Systems Research Group within the Centre for Computer Science and Informatics Research. The School hosts the University of Hertfordshire Robot House, a facility ubiquitously equipped with low-cost sensors providing a realistic environment for experiments with robotics in a smart home; a fully-fledged RoboCup lab for development of humanoid robots participating in international competitions, and a large variety of different robotic platforms, including iCub and Baxter. We encourage applications from researchers across a wide spectrum of AI, and particularly encourage applications from researchers working on emerging topics in AI. Possible fields include, but are not limited to: • Machine learning: reinforcement learning, Deep Methods, statistical methods, large scale data modelling/intelligent processing and high-performance learning algorithms • Robotics: embodied and/or cognitive robotics, HRI, robot safety, emotional/social robots, smart homes and sensors, sensor fusion, assistive robotics • Complex Systems: collective intelligence, adaptive, autonomous and multi-agent/robot systems, collective and swarm intelligence, social and market modelling, adaptive, evolutionary and unconventional computation • Mathematical Modelling: statistical modelling, information-theoretic methods, compressive sensing, intelligent data visualization, multiscale models, optimization • Emerging Topics in AI: computer algebra and AI, topological methods (e.g. persistent homology), modern topics in games and AI • AI and applications: financial modelling, AI and biology/physics/cognitive sciences • Foundations: fundamental questions of intelligence and computation, emergence of life/intelligence, Artificial Life As well as providing research supervision at PhD and MSc level, the School of Computer Science offers modules in Artificial Intelligence, machine learning, neural and evolutionary computing, as well as Artificial Life on the BSc and MSc programmes. Applicants will be committed to a strong research and research-informed teaching agenda, and will actively contribute to increase research impact of the School, in the enthusiastic, welcoming and collegiate environment of the school. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English, an internationally excellent research record and reputation, including publications of the highest quality suitable for submission to the REF (UK Research Excellence Framework). Applicants are expected to show evidence of experience and success in research/commercial income generation, engagement with the research impact agenda, engagement with key stakeholders in the relevant Artificial Intelligence community and management and leadership ability. The professor will have opportunity to contribute actively to interdisciplinary research projects at the school and university level. Applications must be made online https://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies?, reference 016194?. Informal enquiries may be addressed to Dr Volker Steuber (Associate Dean Research, v.steuber(a)herts.ac.uk) or Professor William Clocksin (Dean of School, w.clocksin(a)herts.ac.uk) Please note that applications sent directly by email will not be accepted.

2 2

[journals] CfP : Special Issue on Continual Unsupervised Sensorimotor Learning
by Nguyen, Sao Mai March 14, 2019

March 14, 2019

Dear Colleagues, IEEE Transactions on Cognitive and Developmental Systems is currently running a Special Issue entitled " Continual Unsupervised Sensorimotor Learning". Dr. José Antonio Iglesias Martínez, Assoc. Prof. We would like to invite you to prepare a research article or a comprehensive review to be published in this special issue. AIM AND SCOPE Although machine learning algorithms continue to improve at a rapid pace enabling technologies and products such as autonomous driving cars and sophisticated image and speech recognition, it is often forgotten that these applications represent tailored solutions to specific tasks. Thus it is not clear if or how these autonomous systems can pave the road to general purpose machines envisioned by many. The pursuit for higher levels of autonomy and versatility in robotics is arguably lead by two main factors. Firstly, as we push robots out of the labs and productions lines, it becomes increasingly difficult to design for all possible scenarios that a particular robot might encounter. Secondly, the cost of designing, manufacturing, and maintaining such systems becomes prohibitive. As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance in order to get more autonomous artificial systems. These challenges include multi-task learning, multimodal sensorimotor learning and lifelong adaptation to injury, growth and ageing. Addressing these challenges promise higher levels of autonomy and versatility of future robots. This special issue on Continual Unsupervised Sensorimotor Learning is primarily concerned with the developmental processes involved in unsupervised sensorimotor learning in a life-long perspective, and in particular the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The special issue will highlight behavioural and neural data, and cognitive and developmental approaches to research in the areas of robotics, computer science, psychology, neuroscience, etc. Contributions might focus on mathematical and computational models to improve robot performance and/or attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. Contributions from multiple disciplines including cognitive systems, cognitive robotics, developmental and epigenetic robotics, autonomous and evolutionary robotics, social structures, multi-agent and artificial life systems, computational neuroscience, and developmental psychology, on theoretical, computational, application-oriented, and experimental studies as well as reviews in these areas are welcome. THEMES This special issue aims to report state-of-the-art approaches and recent advances on Continual Unsupervised Sensorimotor Learning with a cross-disciplinary perspective. Topics relevant to this special issue include but are not limited to: Emergence of representations via continual interaction Continual sensory-motor learning Action-perception cycle Active perception Environmental-driven scaffolding Intrinsic motivation Neural substrates, neural circuits and neural plasticity Human and animal behaviour experiments and models Reinforcement learning and deep reinforcement learning for life-long learning Multisensory robot learning Multimodal sensorimotor learning Affordance learning Prediction learning SUBMISSION Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/component/content/article/7/131-ieee-transactions-on-au…. Submissions must be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee. Please select the category “SI: Continual Unsupervised Sensorimotor Learning”. IMPORTANT DATES 6th January 2019 – Paper submission deadline 15th March 2019 – Notification for authors 31st May 2019 – Deadline revised papers submission 30th June 2019 – Final notification for authors 31st July 2019 – Deadline for camera-ready versions September 2019 – Expected publication date More information on Continual Unsupervised Sensorimotor Learning http://projects.au.dk/socialrobotics/news-events/show/artikel/special-issue… GUEST EDITORS Nicolás Navarro-Gerrero Aarhus University, Aarhus, Denmark nng(a)eng.au.dk Sao Mai Nguyen IMT Atlantique, Francenguyensmai(a)gmail.com Erhan Öztop Özyeğin University, Turkeyerhan.oztop(a)ozyegin.edu.tr Junpei Zhong National Institute of Advanced Industrial Science and Technology (AIST), Japanjoni.zhong(a)aist.go.jp ---- Nguyen Sao Mai nguyensmai(a)gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr

1 3

Postdoctoral positions in computational neuroscience and artificial intelligence
by Maxim Bazhenov March 1, 2019

March 1, 2019

Applications are invited for post-doctoral research positions in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to study memory and learning and to develop neuroscience inspired computer algorithms capable of continual learning and adapting to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design neural network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation in sleep and awake based on experimental data. These models will be used to derive learning principles that can be combined with advances in artificial intelligence and machine learning. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning, or, alternatively, experience in machine learning algorithms and some basic knowledge of neuroscience. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov(a)ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/

1 2

PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)
by James Rankin Jan. 3, 2019

Jan. 3, 2019

*PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)* General information & apply (funding is primarily targeted at UK students): http://www.exeter.ac.uk/studying/funding/award/index.php?id=3386 Project description: http://www.exeter.ac.uk/codebox/phdprojects/Rankin-EPSRC-DTP-Project.pdf *Closing date 7th Jan 2019* This interdisciplinary project will develop computational and mathematical models of the auditory system to understand how complex stimuli like speech are encoded by spiking neurons in the midbrain. The auditory midbrain is a key hub in the auditory processing pathway, functioning as an important junction that relays and shapes neural signals as they ascend towards auditory cortex. Knowledge of the way in which complex sounds, e.g. speech, are encoded in the midbrain is crucial for understanding how dysfunction in the earlier auditory processing pathway (cochlea, auditory nerve, cochlear nucleus) leads to different types of hearing loss (a problem affecting 1 in 6 people in the UK). Working with neural recordings from the auditory midbrain in gerbils, a commonly-used animal for the study of low-frequency hearing, this project will develop mathematical and computational models of the auditory processing pathway. The aim is to understand the different roles of the patterns of inputs to midbrain neurons and their intrinsic response properties (e.g. their spiking rate) in shaping their responses to complex sounds. The project will use a dynamical systems approach to model the intrinsic properties of individual neurons in the midbrain in a biologically plausible way (working with, e.g. adaptive exponential integrate-and-fire neurons or the Hodgkin-Huxley equations). Inputs to these neurons will be based on established cochlear models and the biological details of the auditory nerve and cochlear nucleus. The resulting model will produce firing patterns directly comparable with neural recordings provided by the experimental supervisor. This data will be used to train and parameter fit the model using e.g. Bayesian optimisation or genetic algorithms. The resultant model will have explanatory power for the extent to which midbrain responses are shaped by its inputs from cochlear nucleus. Further, it will make predictions, testable in new experiments, of how midbrain responses will be affected by different dysfunctions of the early auditory system relating to hearing loss. The successful candidate will receive training dynamical systems theory and in the development and analysis of individual neuron and neural network models. An interdisciplinary approach, incorporating known biological details of the auditory processing pathway, will require the candidate to learn the relevant biology and neuroscience along with mathematical and computational techniques. The project will involve working closely with experimental neuroscientists and experimental data. This project provides a unique opportunity to receive training in mathematical modelling in close collaboration with experimentalists using cutting-edge methods recording spikes simultaneously from hundreds of neurons. Experience working on such interdisciplinary projects is highly sought after. Candidates with quantitative backgrounds (mathematics, physics, engineering) and from neuroscience programmes are encouraged to apply. Programming experience, knowledge of dynamical systems theory and experience in biological modelling are a plus. For further information, please contact me at the email address above. *For further information, please contact Dr James Rankin, email j.a.rankin(a)exeter.ac.uk <j.a.rankin(a)exeter.ac.uk>* http://emps.exeter.ac.uk/mathematics/staff/jar226

1 1

Post-doc or engineer: image analysis to study astrocyte-synapse/circuit signaling in Lausanne/Switzerland
by Carlos Vivar Rios Dec. 30, 2018

Dec. 30, 2018

We seek a highly motivated post-doc or engineer with solid experience in computer programming and analysis of biological fluorescence signals (e.g. 3D two-photon and microendoscopy Ca2+ imaging), to develop innovative analytical pipelines for studying astrocyte-synapse/circuit computations. Research in our lab is interdisciplinary and focuses on decoding the mode of astrocyte communication and the role of astrocytes in synaptic/circuit functions in the normal and pathologic brain. More info at: https://www.fbm.unil.ch/dnf/group/glia-an-active-synaptic-partner. Publications at: https://www.ncbi.nlm.nih.gov/pubmed/?term=Volterra+A Website at: https://www.fbm.unil.ch/dnf/group/glia-an-active-synaptic-partner Relevant papers: - Savtchouk et al. Front Cell Neurosci, 12:98 (2018); - Bindocci et al., Science, 356.6339 (2017); - Volterra A et al., Nat Rev Neurosci 15:327-35 (2014); - Di Castro et al. Nat Neurosci, 14(10):1276-84 (2011) The ideal candidate is a highly interactive team player in a multidisciplinary English-speaking team; must have solid background in image analysis approaches, experience with most common analysis tools (Imaris, ImageJ, etc), excellent computer programming skills (Python, MATLAB) and knowledge in design of analysis pipeline (linux/windows-based). Expected tasks include: 1) develop both novel analysis approaches and existing programs/interfaces to fit the evolving lab needs in day-by-day interaction with biologists. 2) Maintain and extend our large existing codebase of dedicated analysis scripts for extract and analyze imaging datasets (using proper documentation and exploiting GitHub) and 3) keep track of novel technological and algorithmic developments. Requirements: documented record of productivity, excellent command of English, communication skills and team-working capacity. Applicants should send (as a single PDF file): motivation letter, detailed curriculum vitae, and contact information for 2 references, by email to volterralab(a)gmail.com<mailto:volterralab@gmail.com>, indicating “Candidate - data analysis” in the subject field. Job Information Closing date: 2019-01-15 Employment start date: 2019-03-01 Contract length: Typical post-doc contract may last up to 5 years and renewals are 1+2+2 years Institution: University of Lausanne Department: Fundamental Neuroscience|volterra Kind regards, Carlos Vivar Rios UNIL - Université de Lausanne Département des Neurosciences Fondamentales Groupe de Andrea VOLTERRA Bugnon 9 | CH-1005 | Lausanne | Suisse +34 666 05 42 42 carlos.vivarrios(a)unil.ch<mailto:carlos.vivarrios@unil.ch>

1 0

PhD Studentships in Systems/Computational Neuroscience
by Jian Liu Dec. 26, 2018

Dec. 26, 2018

PhD Studentships in Systems/Computational Neuroscience Centre for Systems Neuroscience at the University of Leicester, UK. www.le.ac.uk/csn A number of PhD studentships are available in a wide range of research topics. Please find the details of all the projects below. The deadlines are different. Please contact the PIs on the list, or Dr. Jian K. Liu directly: Project: Neural mechanisms of memory formation, consolidation and recall PI: Prof R Quian Quiroga https://www.findaphd.com/phds/project/neural-mechanisms-of-memory-formation… Project: Towards a Functional Model for Associative Learning and Memory Formation PI: Dr Jian K. Liu, Prof Rodrigo Quian Quiroga https://www.findaphd.com/phds/project/towards-a-functional-model-for-associ… Project: Dynamics of a minimal neuronal network with multisynaptic dendrites PI: Dr Jian K. Liu, Dr. V Marra https://www.findaphd.com/phds/project/dynamics-of-a-minimal-neuronal-networ… Project: Interpretation of social behaviours among mice with Parkinson’s disease PI: Dr. H Zhou, Dr Jian K. Liu https://www.findaphd.com/phds/project/interpretation-of-social-behaviours-a… Project: Serotonergic modulation of functional connectivity in cortical microcircuits PI: Dr M Okun, Prof Rodrigo Quian Quiroga https://www.findaphd.com/phds/project/serotonergic-modulation-of-functional… -- ************************************************************************** Jian K. Liu, Ph.D. Mathematics Centre for Systems Neuroscience Department of Neuroscience, Psychology and Behaviour University of Leicester, Leicester, UK Phone: +44 (0)116 373-6860 email: jian.liu(a)leicester.ac.uk <jl634(a)leicester.ac.uk> Webpage: https://sites.google.com/site/jiankliu ************************************************************************** <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_cam…> Virus-free. www.avg.com <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_cam…> <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>

1 0

SoAIR 2019 [Extended Deadline]: JST-CREST / IEEE-RAS Spring School on "Social and Artificial Intelligence for User-Friendly Robots" in Japan
by Amir Aly Dec. 26, 2018

Dec. 26, 2018

CALL FOR APPLICATIONS **Apologies for cross posting ** We are pleased to call for applications for the *JST-CREST / IEEE-RAS* spring school on: "*Social and Artificial Intelligence for User-Friendly Robots*" * Which will be held from 17-24 March, 2019 in Shonan Village, Japan *after the *Human-Robot Interaction (HRI)* conference that will be held in the near South Korea. *Webpage: **https://inic8.bitbucket.io/SoAIR19/* <https://inic8.bitbucket.io/SoAIR19/> *I. Aim and Scope *Autonomous and intelligent systems are progressively moving into spaces, which have previously been predominantly shaped by human agency. Unlike in the past where machines obediently served their human operators, machines now increasingly act without the intervention of a human. Artificial intelligence is meeting new challenges in the world, though human-like intelligence may still be a distant goal. Robots in factories are coming out of their cages. Autonomous cars are being tested on streets with regular human-driven cars. The private household is changing with the appearance of not only robotic vacuum cleaners, but also with the first-generation of social robots and smart devices. The challenges that face both the robotics and artificial intelligence communities are how the necessary intelligence for such new environments can be created as well as how to make artificial agents capable of not only solving tasks at hand but also considering social environments around them during interaction with human users so as to behave appropriately. Within the school, we plan to address the tension created by the balance between task-specific artificial intelligence and the demands of sociability required to function effectively in human-centered environments. ** *Who should apply?* We invite *Masters and PhD students* as well as *post-doctoral candidates and researchers from industry* with relevant research background to apply for this spring school. *Additional support could be available based on eligibility.* ** *This spring school is a Technical Education Program (TEP) endorsed and supported by JST-CREST / IEEE-RAS*. ** *The school aims at bridging the gap between social and cognitive Human-Robot Interaction (HRI), Artificial Intelligence (AI), and Autonomous Vehicles (AV) through high level talks, tutorials, and hands-on workshops (the program will be announced soon).* *II. Keynote Speakers: * 1. * Takayuki Nagai, *Osaka University, Japan 2. * Jun Tani *– Okinawa Institute of Science and Technology (OIST), Japan 3. *Daniele Magazzeni *– King's College London, UK 4. * Yukie Nagai *– National Institute of Information and Communications Technology (NICT), Japan 5. * Tetsuya Ogata* – Waseda University, Japan 6. *Mohamed Chetouani *– University of Pierre and Marie Curie (UPMC), France 7. *Silvia Rossi* – University of Naples, Italy 8. *Agnieszka Wykowska *– Italian Institute of Technology (IIT), Italy 9. *Tetsunari Inamura *– National Institute of Informatics (NII), Japan 10. *Amit Kumar Pandey *– SoftBank (Aldebaran) Robotics, France 11. *Mehul Bhatt* – Orebro University, Sweden (Tutorial) 12. *Mohsen Kaboli –* Bavarian Motor Works (BMW), Germany (Tutorial) 13. *Francesco Maurelli *– Jacobs University, Germany (Preparing Marie Curie funding proposal) 14. *Atsuko Nakatsuka* – Japan Society for the Promotion of Science (JSPS), Japan (Preparing JSPS funding proposal) *III. Submission * The applications must include the following files (combined into one file). No other documents would be necessary (More information is available on the school's webpage). 1. *Curriculum vitae*: A CV detailing relevant aspects of the candidate's academic career that demonstrates her/his relevance to the school theme. Please consider including the list of publications. 2. *Research abstract*: A 200-word research abstract that the candidate intends to present during the school. 3. *Letter of recommendation*: A brief letter from the academic advisor or the employer of the candidate supporting her/his application. Please also indicate if additional support would be required to attend the school. *Application submission*: Please use the following EasyChair web link:* Application Submission <https://easychair.org/conferences/?conf=soair2019>.* *IV. Important Dates * 1. Application submission *[Extended]*: *10-January, 2019 * 2. Notification of acceptance: *14-January, 2019 * 3. Spring School: *17-24 March, 2019* *V. Organizers * 1. *Amir Aly *– Ritsumeikan University – Japan 2. *Franziska Kirstein *– Blue Ocean Robotics, Denmark 3. * Shashank Pathak *– Visteon Corporation, Germany --------------------- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

1 0