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Call For Chapters | Neural and Machine Learning for Emotion and Empathy Recognition: Experiences from the OMG-Challenges by Springer

by Pablo Barros

Dear Colleagues, We would like to invite you to contribute a chapter for the upcoming volume entitled “Neural and Machine Learning for Emotion and Empathy Recognition: Experiences from the OMG-Challenges” to be published by the Springer Series on Competitions in Machine Learning. Our book will be available by fall 2019. Website: https://easychair.org/cfp/OMGBook2019 Short description of the volume: Emotional expression perception and categorization are extremely popular in the affective computing community. However, the inclusion of emotions in the decision-making process of an agent is not considered in most of the research in this field. To treat emotion expressions as the final goal, although necessary, reduces the usability of such solutions in more complex scenarios. To create a general affective model to be used as a modulator for learning different cognitive tasks, such as modeling intrinsic motivation, creativity, dialog processing, grounded learning, and human-level communication, instantaneous emotion perception cannot be the pivotal focus. This book aims to present recent contributions for multimodal emotion recognition and empathy prediction which take into consideration the long-term development of affective concepts. On this regard, we provide access to two datasets: the OMG-Emotion Behavior Recognition and OMG-Empathy Prediction datasets. These datasets were designed, collected and formalized to be used on the OMG-Emotion Recognition Challenge and the OMG-Empathy Prediction challenge, respectively. All the participants of our challenges are invited to submit their contribution to our book. We also invite interested authors to use our datasets on the development of inspiring and innovative research on affective computing. By formatting these solutions and editing this book, we hope to inspire further research in affective and cognitive computing over longer timescales. TOPICS OF INTEREST The topics of interest for this call for chapters include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Novel neural network models for affective processing - Lifelong affect analysis, perception, and interpretation - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition - New theories and findings on empathy modeling - Multimodal processing of empathetic and social signals - Novel neural network models for empathy understanding - Lifelong models for empathetic interactions - Empathetic Human-Robot-Interaction Scenarios - New neuroscientific and psychological findings on empathy representation - Multi-agent communication for empathetic interactions - Empathy as a decision-making modulator - Personalized systems for empathy prediction Each contributed chapter is expected to present a novel research study, a comparative study, or a survey of the literature. We also expect that each contributed chapter approach somehow at least one of our datasets: the OMG-Emotion and the OMG-Empathy. SUBMISSIONS All submissions should be done via EasyChair: https://easychair.org/cfp/OMGBook2019 Original artwork and a signed copyright release form will be required for all accepted chapters. For author instructions, please visit: https://www.springer.com/us/authors-editors/book-authors-editors/resources-… ACCESS TO THE DATASETS - OMG-EMOTION - https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_emotion.html - OMG-EMPATHY - https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html To have access to the datasets, please send an e-mail to: barros(a)informatik.uni-hamburg.de IMPORTANT DATES: - Submission of abstracts: 08th of February 2019 - Notification of initial editorial decisions: 15th of February 2019 - Submissions of full-length chapters: 29th of March 2019 - Notification of final editorial decisions 17th of May 2019 - Submission of revised chapters: 07th of June, 2019 -- Best regards, *Pablo Barros* *http://www.pablobarros.net <http://www.pablobarros.net>*

7 years

CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data

by Pablo Barros

2nd CALL FOR PAPERS IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201… I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis “in-the-wild” to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of January 2019 Deadline for reviews and response to authors: 06th of April 2019 Camera-ready deadline: 05th of August 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

7 years, 1 month

Call For Participation in Sclera Segmentation Benchmarking Competition (SSBC 2019) in conjunction with ICB 2019

by Abhijit Das

Dear colleagues, We are inviting participation to biometric competition on "6th *Sclera Segmentation Recognition Benchmarking Competition(SSBC 2019)", *in conjunction with the 12th* IAPR **International Conference on Biometrics (ICB 2019)*. Details about the competition can be found at https://sites.google.com/view/ssbc2019/home Please find a call for participation flyer attached with the email. Please feel free to register for the same. *We will** welcome the top ranking participant to join as co-author of the technical report of the competition that will be submitted to ICB 2019**.* Feel free to contact Abhijit Das if you have any further questions. Kindly circulate this email to others who might be interested. We look forward to your contributions! Best regards Organizers SSBC 2019 Abhijit Das (Inria, France) Umpada Pal (ISI, Kolkata, India) Michael Blumenstein (UTS , Australia)

7 years, 2 months

Call for paper: special session on human health monitoring based on computer vision, IEEE International Conference on Automatic Face and Gesture Recognition (FG’19), Lille, France, May 14-18, 2019.

by Abhijit Das

Dear colleagues, We are inviting paper submissions for a special session on “Human Health Monitoring Based on Computer Vision”, as part of the 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG’19, http://fg2019.org/), Lille, France, May 14-18, 2019. Details on the special session can be found in the attached call for paper and at http://fg2019.org/participate/special-sessions/hhmbcv/. IMPORTANT DATES: Full Paper Submission: Dec 14th, 2018 Acceptance Notification: Jan 21st, 2019 Camera-Ready Paper Due: Feb 15th 2019 Feel free to contact Abhijit Das if you have any further questions. Kindly circulate this email to others who might be interested. We look forward to your contributions! François Brémond (INRIA, France) Antitza Dantcheva (INRIA, France) Abhijit Das (INRIA, France) Xilin Chen (CAS, China) Hu Han (CAS, China)

7 years, 2 months

2nd CFP: The OMG-Empathy Prediction Challenge

by Pablo Barros

2nd CALL FOR PARTICIPATION The One-Minute Gradual-Empathy Prediction (OMG-Empathy) Competition held in partnership with the IEEE International Conference on Automatic Face and Gesture Recognition 2019 in Lille, France. https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html I. Aim and Scope The ability to perceive, understand and respond to social interactions in a human-like manner is one of the most desired capabilities in artificial agents, particularly social robots. These skills are highly complex and require a focus on several different aspects of research, including affective understanding. An agent which is able to recognize, understand and, most importantly, adapt to different human affective behaviors can increase its own social capabilities by being able to interact and communicate in a natural way. Emotional expression perception and categorization are extremely popular in the affective computing community. However, the inclusion of emotions in the decision-making process of an agent is not considered in most of the research in this field. To treat emotion expressions as the final goal, although necessary, reduces the usability of such solutions in more complex scenarios. To create a general affective model to be used as a modulator for learning different cognitive tasks, such as modeling intrinsic motivation, creativity, dialog processing, grounded learning, and human-level communication, only emotion perception cannot be the pivotal focus. The integration of perception with intrinsic concepts of emotional understanding, such as a dynamic and evolving mood and affective memory, is required to model the necessary complexity of an interaction and realize adaptability in an agent's social behavior. Such models are most necessary for the development of real-world social systems, which would communicate and interact with humans in a natural way on a day-to-day basis. This could become the next goal for research on Human-Robot Interaction (HRI) and could be an essential part of the next generation of social robots. For this challenge, we designed, collected and annotated a novel corpus based on human-human interaction. This novel corpus builds on top of the experience we gathered while organizing the OMG-Emotion Recognition Challenge, making use of state-of-the-art frameworks for data collection and annotation. The One-Minute Gradual Empathy datasets (OMG-Empathy) contain multi-modal recordings of different individuals discussing predefined topics. One of them, the actor, shares a story about themselves while the other, the listener, reacts to it emotionally. We annotated each interaction based on the listener's own assessment of how they felt while the interaction was taking place. We encourage the participants to propose state-of-the-art solutions not only based on deep, recurrent and self-organizing neural networks but also traditional methods for feature representation and data processing. We also enforce that the use of contextual information, as well as personalized solutions for empathy assessment, will be extremely important for the development of competitive solutions. II. Competition Tracks We let available for the challenge a pre-defined set of training, validation and testing samples. We separate our samples based on each story: 4 stories for training, 1 for validation and 3 for testing. Each story sample is composed of 10 videos with interactions, one for each listener. Although using the same training, validation and testing data split, we propose two tracks which will measure different aspects of self-assessed empathy: The Personalized Empathy track, where each team must predict the empathy of a specific person. We will evaluate the ability of proposed models to learn the empathic behavior of each of the subjects over a newly perceived story. We encourage the teams to develop models which take into consideration the individual behavior of each subject in the training data. The Generalized Empathy track, where the teams must predict the general behavior of all the participants over each story. We will measure the performance of the proposed models to learn a general empathic measure for each of the stories individually. We encourage the proposed models to take into consideration the aggregated behavior of all the participants for each story and to generalize this behavior in a newly perceived story. The training and validation samples will be given to the participants at the beginning of the challenge together with all the associated labels. The test set will be given to the participants without the associated labels. The team`s predictions on the test set will be used to calculate the final metrics of the challenge. III. How to Participate To participate in the challenge, please send us an email to barros @ informatik.uni-hamburg.de with the title "OMG-Empathy Team Registration". This e-mail must contain the following information: Team Name Team Members Affiliation Participating tracks We split the corpus into three subsets: training, validation, and testing. The participants will receive the training and validation sets, together with the associated annotations once they subscribe to the challenge. The subscription will be done via e-mail. Each participating team must consist of 1 to 5 participants and must agree to use the data only for scientific purposes. Each team can choose to take part in one or both the tracks. After the training period is over, the testing set will be released without the associated annotations. Each team must submit, via e-mail, their final predictions as a .csv file for each video on the test set. Together with the final submission, each team must send a short 2-4 pages paper describing their solution published on Arxiv and the link for a GitHub page to their solution. If a team fails to submit any of these items, their submission will be invalidated. Each team can submit 3 complete submissions for each track. IV. Important Dates 25th of September 2018 - Opening of the Challenge - Team registrations begin 1st of October 2018 - Training/validation data and annotation available 3rd of December 2018 - Test data release 5th of December 2018 - Final submission (Results and code) 7th of December 2018 - Final submission (Paper) 10th of December 2018 - Announcement of the winners V. Organization Pablo Barros, University of Hamburg, Germany Nikhil Churamani, University of Cambridge, United Kingdom Angelica Lim, Simon Fraser University, Canada Stefan Wermter, Hamburg University, Germany -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

7 years, 2 months

Postdoctoral Fellowship opportunities in Singapore

by Charles Or

Nanyang Technological University (NTU) in Singapore has open calls for several postdoctoral fellowships, which are also open for research on vision and perception. There are currently three labs in the area of vision research: - Charles OR (charlesor(a)ntu.edu.sg<mailto:charlesor@ntu.edu.sg>) Face perception, motion perception, form perception, EEG, eye movements, computational modelling, psychophysics; http://research.ntu.edu.sg/expertise/academicprofile/Pages/StaffProfile.asp… - Gerrit MAUS (maus(a)ntu.edu.sg<mailto:maus@ntu.edu.sg>) Eye movements, eye blinks, filling-in, interpolation and extrapolation in vision, prediction, motion perception; psychophysics, fMRI, TMS; http://blogs.ntu.edu.sg/perception - Hong XU (xuhong(a)ntu.edu.sg<mailto:xuhong@ntu.edu.sg>) Heading/Self-motion perception in navigation, face and object perception, attention and eye movements, virtual reality, EEG, electrophysiology, modelling, psychophysics; http://www.ntu.edu.sg/home/xuhong/ We have access to state-of-the-art facilities for psychophysics, virtual reality, eye tracking, EEG, MEG, fMRI, fNIRS, TMS, and tDCS. Feel free to contact any of us for more information or to discuss potential proposals. The fellowship ad below (Deadline: 30 November) is currently offered by the College of Humanities, Arts, and Social Sciences, NTU. There are two more opportunities available at NTU: - for research related to Artificial Intelligence (Walllenberg - NTU Presidential Postdoctoral Fellowship, http://www.ntu.edu.sg/ppf/Pages/home.aspx), - for research in any area by PhD graduates from Swedish Universities (Wallenberg - NTU Postdoctoral Fellowship, call open from Dec 1st, https://kaw.wallenberg.org/utlysningar/wallenberg-foundation-postdoctoral-f…) Best Regards, Charles OR, Gerrit MAUS, Hong XU Assistant Professors (Psychology) School of Social Sciences College of Humanities, Arts, and Social Sciences Nanyang Technological University, Singapore ====== The College of Humanities, Arts, and Social Sciences, Nanyang Technological University (NTU) invites applications from eligible candidates to join us as Postdoctoral Fellows for the Academic Year 2019. The Postdoctoral Fellowships are for one year, renewable for a second year, subject to satisfactory performance. Applicants are strongly advised to explore the research interests of the College’s faculty members to identify potential faculty mentors. Applicants must possess a doctoral degree issued no more than 3 years prior to the time of application (i.e. the degree must have been obtained after Jan 1, 2016). Candidates who are finishing up their degrees must have their doctoral degrees conferred by July 2019. Owing to the interdisciplinary nature of the fellowship, applicants are expected to propose a research project to demonstrate how their expertise crosses different disciplines and relates to the specific Research Theme they are applying for. Details are available at: http://class.cohass.ntu.edu.sg/Research/Pages/Postdoctoral-Fellowship-2019.… Applications and Reference Letters must reach the College by 30 November, 2018 (11:59pm Singapore Time UTC+8). Successful candidates are expected to commence their Fellowships in July or August 2019. Owing to the tight deadline, interested candidates are invited to contact potential faculty mentors as soon as possible, with curriculum vitae and a brief research statement provided. Application and enquiries should be addressed to: The Associate Dean (Research) College of Humanities, Arts, and Social Sciences Email: AD-HASS-RESEARCH(a)ntu.edu.sg<mailto:AD-HASS-RESEARCH@ntu.edu.sg> NTU is a young and research-intensive university ranking consistently amongst the top 10 in Asia and the 1st amongst young universities under 50. It has been ranked consistently and progressively under the top 100 universities in the world by the Times Higher Education since 2013, with its latest ranking at 51. Singapore is a fascinating, dynamic multi-cultural city in Southeast Asia with a large expat community, and a great hub for exploring neighbouring travel destinations. ======= ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

7 years, 2 months

Looking for 3D famous faces

by Caspar M. Schwiedrzik

Hi! I am looking for a database of 3D models of famous faces. I found Eric Baird's database at http://www.relativitybook.com/CoolStuff/facebank.html, but was hoping for additional celebrities. If anyone has a database and is willing to share, or could point me to a database, it would be very much appreciated. Thanks! Caspar

7 years, 2 months

CBAR@FG 2019 CFP: 6th International Workshop on Context Based Affect Recognition @ FG 2019

by zakia hammal

Apologies for cross-posting *********************************************************************************** CBAR 2019: CALL FOR PAPERS 6th International Workshop on CONTEXT BASED AFFECT RECOGNITION https://cbar2019.blogspot.com/ Submission Deadline: December 14th, 2018 *********************************************************************************** The 6th International Workshop on Context Based Affect Recognition (CBAR 2019) will be held in conjunction with FG 2019 in May 2019 in Lille France – http://fg2019.org/ For details concerning the workshop program, paper submission, and guidelines please visit our workshop website at: https://cbar2019.blogspot.com/ Best regards, Zakia Hammal Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/

7 years, 3 months

CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data

by Pablo Barros

CALL FOR PAPERS IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201… I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis “in-the-wild” to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of January 2019 Deadline for reviews and response to authors: 06th of April 2019 Camera-ready deadline: 05th of August 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -------------------------- -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

7 years, 3 months

Society for Affective Science conference - Abstract portal now open!

by Rachael Jack

Dear colleagues, The Society for Affective Science is pleased to announce a Call for Abstracts for the SAS 2019 Conference at the Westin Boston Waterfront Hotel in Boston, MA, on March 21-23, 2019. Abstract Submission Formats In addition to invited sessions, we invite attendees to submit abstracts for posters and flash talk sessions. We welcome abstract submissions that describe new research within the domain of affective science. In line with our goal to facilitate interdisciplinary advances, we welcome submissions from affective scientists in any discipline (e.g., anthropology, business, computer science, cultural studies, economics, education, geography, history, integrative medicine, law, linguistics, literature, neuroscience, philosophy, political science, psychiatry, psychology, public health, sociology, theatre), working on a broad range of topics using a variety of measures. Authors at all career stages – trainees, junior faculty, and senior faculty – are encouraged to submit an abstract according to two presentation formats on any topic within the domain of affective science as follows: 1. A poster 2. A flash talk Deadline for Receipt of Abstracts Abstracts must be submitted by Friday, November 9, 2018, at 11:59 p.m. Baker Island Time (BIT; UTC-12) to be considered for inclusion in the program. Please review the abstract submission instructions carefully. Click here<https://t.e2ma.net/click/4fw8pd/824poyb/sqgu0q> to submit your abstract. All presenters must register and pay to attend the meeting. Notification of acceptance or rejection of abstracts will be emailed to the corresponding author by Friday, January 11, 2019. Selection Process All abstracts will be evaluated for scholarly merit by an interdisciplinary group of SAS Program Committee members using blind peer review. Abstracts are also selected at this time for Poster Spotlight presentations and consideration for poster and flash talk awards. Posters and flash talk award nominees will be evaluated during the conference by SAS faculty members. Reviewers do not review abstracts, posters, or flash talks on which they have a known conflict of interest. Awards will be announced at the conference during the closing ceremony. Program Highlights This year's invited program includes new and exciting interdisciplinary conversations in affective science. An opening session "Trajectories, Transitions, and Turning Points," features Phoebe Ellsworth, Valeria Gazzola, and Bob Levenson describing experiences, events, and findings that were key transitions points in their research programs and careers. The presidential symposium will be devoted to research on culture, ethnicity, and emotion. This year's program will also feature a symposium on emotion and health jointly sponsored by SAS and the American Psychosomatic Society called "The Vital Role of Affective Science in Medicine." We will also continue to showcase other exciting formats, such as TED-style talks, salons, methods and speed networking events, flash talks, poster spotlights, and interactive poster sessions. Come see other invited speakers, including Marc Brackett, Cynthia Breazeal, Alan Fiske, Richard Lane, Jenn Lerner, Tali Sharot, and invited flash-talk speakers who will present groundbreaking research representing a wide range of affective science! There are also four exciting pre-conferences that will be held March 21. Please see the conference website<https://t.e2ma.net/click/4fw8pd/824poyb/8ihu0q> for more information. You can register for SAS 2019 starting in November. We're looking forward to seeing you in Boston for what promises to be another great SAS meeting! Relevant Links Check out our new look!<https://t.e2ma.net/click/4fw8pd/824poyb/obiu0q> We are extremely excited about the new Society website! It's been redesigned from the bottom up with clarity and effectiveness foremost in our minds. We hope affective scientists everywhere will find the site easy to navigate and use. Note that our members-only section will open soon. www.facebook.com/affectScience<https://www.facebook.com/affectScience/> twitter.com/affectScience<https://twitter.com/affectScience> Dr. Rachael E. Jack, Ph.D. Reader Institute of Neuroscience & Psychology School of Psychology University of Glasgow +44 (0) 141 5087 www.psy.gla.ac.uk/schools/psychology/staff/rachaeljack/

7 years, 3 months

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