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Save the Date: ISAIM-2022
by Diochnos, Dimitrios 23 Nov '21

23 Nov '21

SAVE THE DATE Seventeenth International Symposium on ARTIFICIAL INTELLIGENCE and MATHEMATICS ISAIM 2022 http://isaim2022.cs.ou.edu/ January 3-5, 2022 Online via Zoom (Fort Lauderdale, Florida) The International Symposium on Artificial Intelligence and Mathematics (ISAIM), is a biennial meeting that fosters interactions between mathematics, theoretical computer science, and artificial intelligence. This will be the seventeenth Symposium in the series, sponsored by Florida Atlantic University and the Annals of Mathematics and Artificial Intelligence. Due to the pandemic the three-day Symposium will take place online. ISAIM-2022 will feature invited speakers and special topic sessions. Registration is free but you need to register in advance so that you can get the Zoom links in a timely manner. KEYNOTE SPEAKERS: o Noa Agmon (Bar-Ilan University) o Cynthia Dwork (Harvard University) o Jerome Lang (LAMSADE, CNRS, Universite Paris-Dauphine, PSL) o Arun Ross (Michigan State University) o Ohad Shamir (Weizmann Institute of Science) o Noam Slonim (IBM Research AI) o Noga Zaslavsky (MIT) SPECIAL TOPIC INVITED SESSIONS: o In Memory of Naftali Tishby -Organized by Martin Golumbic (University of Haifa) o Boolean and pseudo-Boolean Functions -Organized by Endre Boros (Rutgers University) and Yves Crama (University of Liege) o Coalition Formation Games -Organized by Judy Goldsmith (University of Kentucky) and Joerg Rothe (Heinrich-Heine-Universitat Dusseldorf) o Combinatorial and Geometric Problems in Imaging Sciences -Organized by Valentin Brimkov (Buffalo State College) o Formalization in Mathematics -Organized by Gonzalo A. Aranda-Corral (Universidad de Sevilla) and Francisco Jesus Martin Mateos (Universidad de Sevilla) o Sequencing, sequential decision making and scheduling -Organized by Lisa Hellerstein (New York University) and Thomas Lidbetter (Rutgers University) o Uncertain Reasoning -Organized by Alessandro Antonucci (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale - IDSIA), Salem Benferhat (University of Artois), and Kamal Premaratne (University of Miami) ORGANIZERS: o General Chair: Martin Charles Golumbic, University of Haifa o Conference Chair: Frederick Hoffman, Florida Atlantic University o Publications & Publicity Chair: Dimitrios I. Diochnos, University of Oklahoma Send inquiries and requests to <isaim2022 at cs DOT ou DOT edu>. Visit http://isaim2022.cs.ou.edu/. Join isaim(a)googlegroups.com to receive announcements related to ISAIM.

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Readership Position available at the University of Hertfordshire:
by Daniel Polani 23 Nov '21

23 Nov '21

Dear RoboCuppers, please note a unique opportunity (late early or mid-career) at UH below to join our enthusiastic and quirky team. Of course I should mention our Humanoid RoboCup Lab and Robot House facilities. Please feel free to contact me for further information (or follow below link). Readership/Principal Lectureship in Robotics and Adaptive Systems School of Physics, Engineering and Computer Science University of Hertfordshire, Hatfield, UK Closing: 6. December 2021 Applications are invited for a Reader/Principal Lectureship on emerging topics in Robotics/AI, including, but not limited to: - Robotics: embodied and/or cognitive robotics, soft robotics, adaptive or evolutionary robotic design, robot safety and ethics, sensorics and robotics, emotional/social robots, smart homes and sensors, sensor fusion, assistive robotics, human-robot interaction, agricultural robotics, humanoid robots - Machine learning: reinforcement learning, Deep Methods, statistical methods, large scale data modelling/intelligent processing and high-performance learning algorithms - Biological and biophysical computation paradigms, systems biology, neural computation - 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; causality - Emerging Topics in AI: computer algebra and AI, topological methods (e.g. persistent homology), algebraic and category-theoretical methods in AI; modern topics in games and AI; quantum algorithms for 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 Closing Date: 6. December 2021 To apply and for further information, please see: https://www.jobs.ac.uk/job/CKJ638/reader-principal-lecturer-in-robotics-and…, Ref. No.: 032595 - Daniel Polani

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[jobs] Mulitple Openings at Magazino Germany
by Sebastian Eltester 18 Nov '21

18 Nov '21

Dear Robocup community, are you ready to help shape the future of robotics? Then become a Magazino<https://www.magazino.eu/company/?lang=en>!! 🤖 We have plenty of job opportunities open, whether it is a student position, a junior position or a senior position. If you are eager to join a highly divers team with backgrounds from all over the world then hit the apply button to join us! Take a closer look at our vacancies: * Robot Release QA Engineer (f/m/x)<https://www.magazino.eu/apply-now/robot-release-qa-engineer-f-m-x/?lang=en> * Robot Deployment Engineer (f/m/x), Region Munich<https://www.magazino.eu/apply-now/robot-deployment-engineer-f-m-x-region-mu…> * Robot Deployment Engineer (f/m/x), Region NRW/Lower Saxony<https://www.magazino.eu/apply-now/robot-deployment-engineer-f-m-x-region-nr…> * Working Student Remote Operator (f/m/x)<https://www.magazino.eu/apply-now/working-student-f-m-x-remote-operator-rob…> 🌈 We're open to all nationalities and all genders! 🌈 If you have questions, feel free to contact us any time! Cheers! Sebastian PS.: Who else is stoked for RCAP? Sebastian Eltester Operations Center Lead T +49-89-2155-2415-8 M +49-171-9718580 <mailto:waggershauser@magazino.eu>eltester(a)magazino.eu<mailto:eltester@magazino.eu> | [www.magazino.eu]www.magazino.eu [signature_775036230]<https://www.magazino.eu/> [signature_520303617] <https://www.facebook.com/Magazino-GmbH-737817356290011/> [signature_1689280880] <https://www.xing.com/xbp/pages/magazino-gmbh> [signature_607702122] <https://www.linkedin.com/company/magazino-gmbh/> [signature_1213976598] <https://www.instagram.com/magazino_loves_robots/> MAGAZINO GmbH | Landsberger Straße 234 80687 München | Deutschland Amtsgericht München HRB 209758 | USt-IdNr.: DE293308625 Geschäftsführer: Frederik Brantner, Lukas Zanger

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[jobs] Two tenured positions in Autonomous Systems at Bonn-Rhein-Sieg University of Applied Sciences
by Alex Mitrevski 16 Nov '21

16 Nov '21

Dear roboticists, The Department of Computer Science at Bonn-Rhein-Sieg University of Applied Sciences (Sankt Augustin Campus), together with the Bonn-Aachen International Centre for Information Technology (b-it), has the following two permanent professorships (W2) for Computer Science, in particular in Autonomous Systems: 1. Mathematical foundations of autonomous systems 2. Industry-relevant and application-related aspects of autonomous systems. The two position are to be filled as soon as possible. We expect applicants for both positions to meet the following requirements: * the employment requirements of §36 HG NRW, in particular three years of professional experience outside of higher education institutions, * very good knowledge of English, as well as the ability and willingness to teach in English, * pedagogical and didactic skills in teaching complex learning content, * a willingness to participate in activities within the university, as well as national and international committees, * experience in the acquisition, establishment and implementation of internal and externally funded research and development projects, * active participation in the further development and expansion of the MAS program. In addition, the following criteria would be desirable: * teaching experience at universities or comparable institutions, * willingness to also teach undergraduate courses that correspond to the topics of the call for applications, * willingness for interdisciplinary cooperation with other institutions within and outside the university, * evidence of international collaborations and networking with the professional community, * willingness to conduct courses and examinations in German. More detailed information can be found at: 1. Mathematical foundations of autonomous systems: https://stellen.h-brs.de/jobposting/dcdfdd50800036e2492311716a44c03b81a1583… <https://stellen.h-brs.de/jobposting/dcdfdd50800036e2492311716a44c03b81a1583…> 2. Industry-relevant and application-related aspects of autonomous systems: https://stellen.h-brs.de/jobposting/0adf13b597c4a2f154f856c2fcaf65311ffeb2c… <https://stellen.h-brs.de/jobposting/0adf13b597c4a2f154f856c2fcaf65311ffeb2c…> We would like to see more female scientists at our university and are therefore particularly pleased to receive applications from women. We welcome applicants with children. H-BRS is a certified family-friendly university - and proud of it. People with severe disabilities are part of our university. We give them preference in the application process if their qualifications are equal. The position is suitable for part-time work. For information about the professorship to be filled, please contact the head of the appointment committee Prof. Dr. Nico Hochgeschwender (nico.hochgeschwender(a)h-brs.de <mailto:nico.hochgeschwender@h-brs.de>). In addition, the Equal Opportunity Officer of the H-BRS, Dr. Barbara Hillen, is also happy to assist you (www.h-brs.de/de/gi/barbara-hillen <https://www.h-brs.de/de/gi/barbara-hillen>). Regards, Nico Hochgeschwender **************************************************************************************** Prof. Dr. Nico Hochgeschwender Professor of Autonomous Systems B-IT Bonn-Aachen International Center of Information Technology Fon: +49-2241-865-9634 Bonn-Rhein-Sieg University oAS Fax: +49-2241-865-8293 Computer Science Department Net: nico.hochgeschwender(a)h-brs.de Grantham-Allee 20 53757 Sankt Augustin, Germany Web: http://www.h-brs.de/de/inf/nico-hochgeschwender Twitter: @nico_roboticist **************************************************************************************** International Master Program on Autonomous Systems https://www.h-brs.de/en/inf/autonomous-systems-msc ****************************************************************************************

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Postdoctoral Position at University of Glasgow
by Alessandro Vinciarelli 16 Nov '21

16 Nov '21

Dear all, we have a postdoctoral position (3 years) for the European Project SONICOM (http://www.sonicom.eu). The main goal of the successful candidate will be the development of methodologies capable to infer the personality traits of an individual (both self-assessed and attributed) from speech data rendered in VR and, possibly, from other nonverbal behavioural cues. The preferred candidates have an established track record in speech/signal processing and machine learning (in particular deep networks). Please apply by clicking on the following link: https://lnkd.in/dYVpY_KS The deadline is on November 25th at 23.45. Best, Alessandro

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Call for IEEE TNNLS Special Issue on "Stream Learning, " Submission Deadline: December 15, 2021
by Pub Conference 16 Nov '21

16 Nov '21

IEEE TNNLS Special Issue on "Stream Learning," Guest Editors: Jie Lu, University of Technology Sydney, Australia; Joao Gama, University of Porto, Portugal; Xin Yao, Southern University of Science and Technology, China; Leandro Minku, University of Birmingham, UK. Submission Deadline: December 15, 2021 [EXTENDED]. Website: https://cis.ieee.org/images/files/Publications/TNNLS/special-issues/One-Pag…

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PhD/MS Openings in Human-Robot Interaction at University of Pittsburgh's School of Information and Computing
by Michael Lewis 15 Nov '21

15 Nov '21

The PhD programs in Informatics and Networked Systems or Intelligent Systems provide interdisciplinary training in robotics, AI, and HRI. The available position(s) at ULab (http://www.pitt.edu/~cmlewis/research.html) comes with a 2-5 year Graduate Assistantship to study human interaction with AI and robotic systems. You will work in close collaboration with Prof. Sycara's laboratory at Carnegie Mellon University ( http://www.ri.cmu.edu/person.html?person_id=304) to study Theory of Mind models of Artificial Social Intelligence, Human-Autonomy Teams (HATs) and metrics for evaluating them. Applicants at either bachelors or masters level are invited to apply. Please contact Michael Lewis cmlewis(a)pitt.edu to discuss possible assistantship and instructions for application.

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CPS&IoT'2022 - the 10th International Conference on Cyber-Physical Systems and Internet-of-Things
by Jozwiak, Lech 12 Nov '21

12 Nov '21

Special Focus: Green CPS&IoT for Green World Special Theme of CPS&IoT’2022: Artificial Intelligence, Edge Computing, Architectures, Methods and Tools for Autonomous Robots, Vehicles, Assistive, Environmental and other advanced CPS&IoT Dear Colleague, Please find the Call for Papers of CPS&IoT’2022 - the 10th International Conference on Cyber-Physical Systems and Internet-of-Things, Budva, Montenegro, 7-10 June, 2022 attached to this e-mail. CPS&IoT’2022 will be held in the Conference Venue (Hotel Budva) and online. All papers that will be accepted after the conference review process will be published in the CPS&IoT’2022 Conference Proceedings regardless of the authors' physical presence at the conference and will be presented by their authors either in the Conference Venue or online. The CPS&IoT’2022 Conference will host several prestigious keynote speakers from industry and academia. Extended journal versions of selected high-quality papers will be published in a special issue of the ISI indexed journal “Microprocessors and Microsystems” (MICPRO) https://www.journals.elsevier.com/microprocessors-and-microsystems<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.journ…>. The CPS&IoT'2022 Conference<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fembeddedc…> is collocated with the CPS&IoT’2022 Summer School<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fembeddedc…> and MECO'2022 Conference<https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fembeddedc…> - the 11th Mediterranean Conference on Embedded Computing. Together they constitute a major Europe based conference event in CPS and IoT. Please also find attached the Call for Workshops and Special Sessions of CPS&IoT’2022. You are encouraged to submit your papers, as well as, Workshop and Special Session Proposals to the CPS&IoT’2022 Conference, and to participate in the collocated CPS&IoT’2022 Summer School. Paper Submission Deadline: 31 January 2022. Workshop and Special Session Proposal Submission Deadline: 30 November 2021. Best regards, Lech Jozwiak Program Chairman of the CPS&IoT’2022 Conference and Radovan Stojanovic Managing Chairman of the CPS&IoT’2022 Conference

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[Journal] IJAIT Call for Special Issue on Explainable Machine Learning in Methodologies and Applications
by Pub Conference 08 Nov '21

08 Nov '21

Computational Intelligence Journal Special Issue on Explainable Machine Learning in Methodologies and Applications https://onlinelibrary.wiley.com/page/journal/14678640/homepage/special_issu… This special issue aims to bring together original research articles and review articles that will present the latest theoretical and technical advancements of machine and deep learning models. We hope that this Special Issue will: 1) improve the understanding and explainability of machine learning and deep neural networks; 2) enhance the mathematical foundation of deep neural networks; and 3) increase the computational efficiency and stability of the machine and deep learning training process with new algorithms that will scale. Potential topics include but are not limited to the following:  Interpretability of deep learning models  Quantifying or visualizing the interpretability of deep neural networks  Neural networks, fuzzy logic, and evolutionary based interpretable control systems  Supervised, unsupervised, and reinforcement learning  Extracting understanding from large-scale and heterogeneous data  Dimensionality reduction of large scale and complex data and sparse modeling  Stability improvement of deep neural network optimization  Optimization methods for deep learning  Privacy preserving machine learning (e.g., federated machine learning, learning over encrypted data)  Novel deep learning approaches in the applications of image/signal processing, business intelligence, games, healthcare, bioinformatics, and security Important Dates Deadline for Submissions: March 31, 2022 First Review Decision: May 31,‬2022 Revisions Due: June 30, 2022 Deadline for 2nd Review: July 31, 2022 Final Decisions: August 31, 2022  Final Manuscript: September 30, 2022

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Call for paper-Neural Computing and Applications, Topical Collection on Interpretation of Deep Learning
by Pub Conference 08 Nov '21

08 Nov '21

Neural Computing and Applications <https://www.springer.com/journal/521/> Topical Collection on Interpretation of Deep Learning: Prediction, Representation, Modeling and Utilization https://www.springer.com/journal/521/updates/19187658 Aims, Scope and Objective While Big Data offers the great potential for revolutionizing all aspects of our society, harvesting of valuable knowledge from Big Data is an extremely challenging task. The large scale and rapidly growing information hidden in the unprecedented volumes of non-traditional data requires the development of decision-making algorithms. Recent successes in machine learning, particularly deep learning, has led to breakthroughs in real-world applications such as autonomous driving, healthcare, cybersecurity, speech and image recognition, personalized news feeds, and financial markets. While these models may provide the state-of-the-art and impressive prediction accuracies, they usually offer little insight into the inner workings of the model and how a decision is made. The decision-makers cannot obtain human-intelligible explanations for the decisions of models, which impede the applications in mission-critical areas. This situation is even severely worse in complex data analytics. It is, therefore, imperative to develop explainable computation intelligent learning models with excellent predictive accuracy to provide safe, reliable, and scientific basis for determination. Numerous recent works have presented various endeavors on this issue but left many important questions unresolved. The first challenging problem is how to construct self-explanatory models or how to improve the explicit understanding and explainability of a model without the loss of accuracy. In addition, high dimensional or ultra-high dimensional data are common in large and complex data analytics. In these cases, the construction of interpretable model becomes quite difficult and complex. Further, how to evaluate and quantify the explainability of a model is lack of consistent and clear description. Moreover, auditable, repeatable, and reliable process of the computational models is crucial to decision-makers. For example, decision-makers need explicit explanation and analysis of the intermediate features produced in a model, thus the interpretation of intermediate processes is requisite. Subsequently, the problem of efficient optimization exists in explainable computational intelligent models. These raise many essential issues on how to develop explainable data analytics in computational intelligence. This Topical Collection aims to bring together original research articles and review articles that will present the latest theoretical and technical advancements of machine and deep learning models. We hope that this Topical Collection will: 1) improve the understanding and explainability of machine learning and deep neural networks; 2) enhance the mathematical foundation of deep neural networks; and 3) increase the computational efficiency and stability of the machine and deep learning training process with new algorithms that will scale. Potential topics include but are not limited to the following: - Interpretability of deep learning models - Quantifying or visualizing the interpretability of deep neural networks - Neural networks, fuzzy logic, and evolutionary based interpretable control systems - Supervised, unsupervised, and reinforcement learning - Extracting understanding from large-scale and heterogeneous data - Dimensionality reduction of large scale and complex data and sparse modeling - Stability improvement of deep neural network optimization - Optimization methods for deep learning - Privacy preserving machine learning (e.g., federated machine learning, learning over encrypted data) - Novel deep learning approaches in the applications of image/signal processing, business intelligence, games, healthcare, bioinformatics, and security Guest Editors Nian Zhang (Lead Guest Editor), University of the District of Columbia, Washington, DC, USA, nzhang(a)udc.edu Jian Wang, China University of Petroleum (East China), Qingdao, China, wangjiannl(a)upc.edu.cn Leszek Rutkowski, Czestochowa University of Technology, Poland, leszek.rutkowski(a)pcz.pl Important Dates Deadline for Submissions: March 31, 2022 First Review Decision: May 31, 2022 Revisions Due: June 30, 2022 Deadline for 2nd Review: July 31, 2022 Final Decisions: August 31, 2022 Final Manuscript: September 30, 2022 Peer Review Process All the papers will go through peer review, and will be reviewed by at least three reviewers. A thorough check will be completed, and the guest editors will check any significant similarity between the manuscript under consideration and any published paper or submitted manuscripts of which they are aware. In such case, the article will be directly rejected without proceeding further. Guest editors will make all reasonable effort to receive the reviewer’s comments and recommendation on time. The submitted papers must provide original research that has not been published nor currently under review by other venues. Previously published conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended to be considered for this special issue (with at least 30% difference from the original works). Submission Guidelines Paper submissions for the special issue should strictly follow the submission format and guidelines ( https://www.springer.com/journal/521/submission-guidelines). Each manuscript should not exceed 16 pages in length (inclusive of figures and tables). Manuscripts must be submitted to the journal online system at https://www.editorialmanager.com/ncaa/default.aspx. Authors should select “TC: Interpretation of Deep Learning” during the submission step ‘Additional Information’.

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