Call for Papers – ACM GoodIT 2024

March 12th, 2024 Daniela Lopez de Luise
;word-spacing:0px”>4-6 September 2024, Bremen, Germany

https://blogs.uni-bremen.de/goodit2024/

 

The ACM 4th International Conference on Information Technology for Social Good (GoodIT 2024)  is a premier international forum for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of data and technology for addressing Social Good and the UN Sustainable Development Goals. We welcome contributions that delve into the nexus of technology, data science, and social well-being, exploring how these domains interconnect and impact society.

 

Alongside the main track, the conference includes the Work-in-Progress and PhD Track. The Work-in-Progress Track is an excellent opportunity for practitioners and researchers to present early-stage work, offering a platform for sharing innovative ideas, receiving feedback, and fostering discussions and collaborations. The PhD Track is designed for PhD students at different stages of their research. It provides a valuable opportunity for these students to present and refine their research under the guidance of experienced researchers. 

Additionally, the program will be enriched with several Special Tracks. The forthcoming Call for Papers will outline these tracks' details and specific topics.

 

We welcome submissions on a wide range of topics, including but not limited to:

 

  • IT and Data Science for Social Good:
    • Social Impact of Machine Learning Applications
    • Data and algorithmic biases and potential societal risks 
    • Large language models (LLMs) and GenAI models impact on society
    • Fairness, Accountability, and Transparency in Machine Learning
    • Citizen Science
    • IT for smart living,  Health and social care

 

  • Technology for Social Good:
    • AI and Machine Learning for Social and Humanitarian response
    • IoT Solutions for Sustainable Development
    • Decentralized approaches to IT
    • Digital Solutions for Cultural Heritage
    • Game, entertainment, and multimedia applications
    • IT for education

  • Environmental Sustainability and Technology:
    • Green Computing and Energy-Efficient Technologies
    • Climate Change Modeling and Environmental Science
    • Smart Cities and Sustainable Urban Development
    • Sustainable Networking and Communication Systems
    • Technology addressing the digital divide

 

  • Ethics, Policy, and Governance in Tech for Social Good:
    • Regulatory and Policy Frameworks for Ethical Tech
    • Governance of AI and Autonomous Systems in Social Contexts
    • Digital Rights and Freedom in the Age of Technology
    • Data Privacy and Security in Social Applications

 

Submission Guidelines:

Submitted papers must be original works and must not have been previously published. 

All papers must clearly outline the research question, methodology, results, and implications for social good.

The papers should follow the new ACM format (https://authors.acm.org/proceedings/production-information/taps-production-workflow). 

  • Main Track and Special Tracks Full Paper Submission should be a maximum of 12 pages; 
  • Work-in-Progress papers should be a maximum of 8 pages;  
  • Ph.D. track papers should be a maximum of 5

The indicated paper length includes references, tables, and figures. Documents with a length disproportionate to their contribution will be rejected. 

 

These submissions will undergo a single-blind peer review process involving three evaluations each.  Accepted papers will be included in the ACM Digital Library.  

Each accepted paper must have at least one of its authors register for and physically present the work at the conference. Please consider that this is a condition to ensure the paper is included in the conference proceedings.

For additional details, please check the  “Submission of Papers”  (https://blogs.uni-bremen.de/goodit2024/submission-of-papers/) web page.

 

Important Dates:

  • Full Paper Submission Deadline: May 17th, 2024
  • Notification of Paper Acceptance: July 8th, 2024
  • Camera-Ready Submission: July 19th, 2024 
  • Conference Dates: 4-6 September 2024, Bremen, Germany

 

Submission Portal:

Please submit your papers through our online submission portal available at https://goodit2024.hotcrp.com/

 

Contact Us:

For any inquiries regarding the call for papers, please contact pmanzoni@disca.upv.es” target=”_blank”>pmanzoni@disca.upv.es

We look forward to your contributions and to seeing you at the ACM GOODIT 2024 Conference!

ACM GOODIT 2024 Conference Committee


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CPS&IoT’2024 Summer School and Conference – New Deadlines

March 12th, 2024 Daniela Lopez de Luise

Paper Submission Deadline: 15 April 2024

Reduced participation fee: till 30 March 2024

 

Dear Colleagues,

 

You are encouraged to participate in the CPS&IoT’2024 Summer School – the 5th Summer School on Cyber-Physical Systems and Internet-of-Things and submit papers to the CPS&IoT'2024 Conference – the 12th International Conference on Cyber-Physical Systems and Internet-of-Things that will be held in the Conference Venue: Hotel Budva, Budva, Montenegro, and online, 11-14 June, 2024.

 

Special Focus: Green CPS&IoT for Green World

 

Special Theme of CPS&IoT’2024: Artificial Intelligence, Edge Computing, Architectures, Methods and Tools for Autonomous Robots, Vehicles, Assistive, Environmental and other advanced CPS&IoT

 

The Summer School as a part of a major European CPS&IoT’2024 Conference Event composed of:

(more details: https://mecoconference.me/ss-cpsiot2024/).

 

Registration to CPS&IoT’2024 Summer School entitles to free participation in CPS&IoT’2024 Conference and MECO’2024 Conference sessions.

 

A distinguishing feature of the CPS&IoT’2024 Summer School is that its lectures, demonstrations, and practical hands-on sessions:

–      are based on results from numerous currently running or recently finished European R&D projects in Cyber-Physical Systems (CPS), Internet-of-Things (IoT) and Artificial Intelligence (AI), and

–      will be given by top specialists in particular CPS, IoT and AI fields form European industry and academia, and will deliver very fresh advanced knowledge.

The School gives a unique opportunity to interact with outstanding specialists in the CPS, IoT and AI area.

 

Both industrial participation and academic participation are encouraged.

Ph.D. students and Postdocs participation is especially encouraged.

 

Only a limited number of participants will be admitted to the CPS&IoT’2023 Summer School.

Register as soon as possible. Reduced participation fee is till 30 March 2024.

To submit your application and register follow the instructions at the CPS&IoT’2024 Summer School web-page: https://mecoconference.me/ss-cpsiot2024/#registration

 

In case of any problem or question related to the registration or fee payment please do not hesitate to contact Radovan Stojanović (stox@ac.me).

 

In case of questions related to the CPS&IoT’2023 Summer School Program please contact Lech Jóźwiak (L.Jozwiak@tue.nl).

 

You are encouraged to submit your papers to the CPS&IoT’2024 Conference or MECO’2024 Conference – Paper Submission Deadline: 15 April 2024. To submit papers follow the instructions at the CPS&IoT’2024 Conference web-page: https://mecoconference.me/cpsiot-submissions/.

 

Please distribute this Call among your colleagues, students, and within your project consortia.

 

Best regards,

 

Lech Jóźwiak

Program Chairman of the CPS&IoT’2024 Summer School and Conference Event

Eindhoven University of Technology, The Netherlands

and

Radovan Stojanović

Organizing Chairman of the CPS&IoT’2024 Summer School and Conference Event

University of Montenegro, Montenegro

_____________________________

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Call for papers | Special Issue: “Latest Research on Eye Tracking Applications” | Applied Sciences (IF: 2.7, ISSN 2076-3417)

March 12th, 2024 Daniela Lopez de Luise


Dear Colleagues,


We would like to inform you that the Special Issue “Latest Research on Eye Tracking Applications” in Applied Sciences (IF: 2.7, ISSN 2076-3417) is now open to receive submissions. This Special Issue belongs to the section “Computing and Artificial Intelligence”.


Special Issue Information:

Eye tracking constitutes a powerful technology which can be used for the examination of visual behavior and strategy during the observation of different types of (audio)visual stimuli presented either on a digital monitor, in the physical (real world) space, as well as in a virtual/augmented reality environment. At the same time, eye tracking has the potential to enhance the human–computer interaction experience by providing the ability to manipulate modern digital devices with human eyes. Nowadays, considering the huge amount of eye tracking applications available in various and different scientific/research and professional domains, gaze data collection, analysis, visualization, and modeling face several challenges. Such challenges mainly include the manipulation of big gaze data, the performance of remote (through the internet) experimentation, the semantic extraction of valuable knowledge from collected gaze data, gaze data synchronization during combined implementation with other experimental techniques, and real-time and/or post-experimental data collection using low-cost solutions (including webcams).

This Special Issue aims to collect high-quality original research papers, review studies, and short communications in any field connected to eye tracking research and technology. There is no restriction on the length of the submitted manuscripts. New techniques, methods, procedures, experimental frameworks, and applications related to eye tracking technology and analysis are welcome. Moreover, authors are encouraged to share innovative and open source software (e.g., a toolbox) for gaze data recording, processing, analysis, and/or visualization, as well as open access and well-documented eye tracking datasets acquired over diverse or original types of visual stimuli or conditions.


More specifically, potential topics include, but are not limited to, the following:

  • Research on eye tracking hardware development

  • Low-cost eye tracking solutions

  • Event detection algorithms in eye tracking data

  • Gaze data analysis and visualization software

  • Eye tracking in laboratory, real world, and web environment

  • Human–computer interaction applications

  • Gaze datasets

  • Eye tracking studies and applications in different research domains

We welcome comprehensive and systematic literature reviews on any of the aforementioned topics.


Keywords: eye tracking; eye movements; eye movement events detection; gaze data analysis; gaze data modeling;gaze data visualization; eye tracking hardware; eye tracking datasets; eye tracking data toolboxes; gaze interaction; webcam eye tracking; low-cost eye tracking


Deadline for manuscript submissions: 6 December 2024


For more information about the submission process and the article processing charges, please visit the website of the Special Issue:

https://www.mdpi.com/journal/applsci/special_issues/99E2K700SK


Please do not hesitate to contact us in order to express your interest and/or if you have any questions.

We look forward to your contributions.

Kind regards,
Dr. Vassilios Krassanakis (Department of Surveying and Geoinformatics Engineering, School of Engineering, University of West Attica, Greece)
Dr. Erwan David (Computer Science Laboratory (LIUM), Le Mans University, Le Mans, France)
Dr. Olivier Le Meur (InterDigital R&D, Rennes, France)
Guest Editors

Dr. Vassilios Krassanakis | Assistant Professor
University of West Attica | Department of Surveying and Geoinformatics Engineering Egaleo Park Campus, Ag. Spyridonos Str., 12243 Egaleo (Athens), Greece  Building: K10 | Office: K10.101 | Email: krasvas@uniwa.gr | Tel.: (+30) 210 538 7345
Webpages:  [UNIWA]: https://geo.uniwa.gr/en/profile/krassanakis-vassilios/  [Personal]: https://sites.google.com/site/vassilioskrassanakis   [GitHub]: https://github.com/krasvas [Google Scholar]: https://scholar.google.gr/citations?user=62pBQHwAAAAJ&hl=el&oi=ao  [Scopus]: https://www.scopus.com/authid/detail.uri?authorId=56094634800 [Web of Science]: https://www.webofscience.com/wos/author/record/2292078  [Semantic Scholar]: https://www.semanticscholar.org/author/Vassilios-Krassanakis/3163032   [ResearchGate]: https://www.researchgate.net/profile/Vassilios-Krassanakis [ORCID]: https://orcid.org/0000-0002-3030-4203

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International Summer School in Jyvaskyla, Finland, in August offers e.g. a course on Bayesian multiobjective optimization – registration is open till end of April

March 12th, 2024 Daniela Lopez de Luise

 

The 33rd Jyvaskyla Summer School will be organized on August 5–16, 2024 at the University of Jyväskylä, Finland.

 

The Summer School welcomes students from all around the world to learn from top-level scientists, expand their professional network, and create new memories. The Summer School offers courses for advanced Master’s students, PhD students and post-docs in various fields of natural sciences, mathematics and information technology including multiobjective optimization. All courses are taught in English by distinguished researchers. Participation in all Summer School courses is free of charge. For more information about the Summer School, please visit https://www.jyu.fi/jss

 

Deadline for applications to attend courses: end of April. For more information, see How to apply to Jyväskylä Summer School | University of Jyväskylä (jyu.fi)

 

Information about the courses available: Jyväskylä Summer School Course Programme | University of Jyväskylä (jyu.fi)

 

For example, we offer the following course related to multiobjective optimization on August 12-16:

 

COM2: Beyond Conventional Optimization: Data-Driven Multiobjective Bayesian Optimization

Lecturer: Dr. Tinkle Chugh (University of Exeter, UK)

 

Many real-world optimization problems involve computationally (or financially) expensive evaluations. For example, the shape design of a component in an air intake ventilation system [1] and the stator design in a hydrodynamic pump [2], involve computationally expensive fluid dynamics simulations. Another example of a computationally expensive problem involving a hydrogeological simulation model is the management of hydraulic barriers in coastal aquifers [3]. All these problems are black boxes without any information on gradients and closed-form expressions of objectives. Bayesian optimization is an efficient tool for solving such kinds of problems. The course will bridge the gap between traditional optimization limitations and the demands of modern decision-making. By exploring advanced Bayesian techniques integrated with data-driven approaches, the course will cover different approaches for solving complex multiobjective optimization problems [4] and provide methods to make informed decisions efficiently. The potential of Bayesian optimization will be shown by providing examples of real-world applications. The course aims to provide a comprehensive understanding of cutting-edge optimization methodologies and their potential in solving real-world optimization problems.

References:

[1] T. Chugh, T. Kratky, K. Miettinen, Y. Jin, P. Makkonen P. (2019) Multiobjective Shape Design in a Ventilation System with a Preference-driven Surrogate-assisted Evolutionary Algorithm, In the proceedings of The Genetic and Evolutionary Computation Conference, Pages 1147–1155, 2019

[2] T. Kratky. Shape optimization of hydraulic surfaces of the impeller and stator parts of hydrodynamic pumps, 2021. Available from: https://theses.cz/id/6ihxiw/. Doctoral theses, Dissertations. Palacky University Olomouc, Faculty of Science.

[3] S. Saad, AA Javadi, T. Chugh, R. Farmani (2022) Optimal management of mixed hydraulic barriers in coastal aquifers using multi-objective Bayesian optimization, Journal of Hydrology, volume 612, pages 128021-128021, 2022

[4] T. Chugh. Mono-surrogate vs multi-surrogate in multi-objective Bayesian optimisation. In the proceedings of The Genetic and Evolutionary Computation Conference, Pages 2143–2151, 2022.

 

For further information, see COM2 at Jyväskylä Summer School Course Programme | University of Jyväskylä (jyu.fi)

 

There are also many other courses, for example, introduction to quantum computing.

Please, forward information about the summer school to colleagues and students who could be interested in attending.

With best regards, Kaisa Miettinen

 

************************************

Professor Kaisa Miettinen, PhD

University of Jyvaskyla

Multiobjective Optimization Group: http://www.mit.jyu.fi/optgroup/

Faculty of Information Technology, P.O. Box 35 (Agora)

FI-40014 University of Jyvaskyla, Finland

– – –

* Director of the thematic research area Decision Analytics utilizing Causal Models

and Multiobjective Optimization, http://www.jyu.fi/demo

– – –

tel. +358 50 3732247 (mob.)

email: kaisa.miettinen at jyu.fi

homepage: http://www.mit.jyu.fi/miettine and http://www.mit.jyu.fi/miettine/engl.html

* Developing open source software framework DESDEO for interactive methods: https://desdeo.it.jyu.fi

My book: Nonlinear Multiobjective Optimization, Kluwer (Springer):  http://www.mit.jyu.fi/miettine/book/

* My publications: http://www.mit.jyu.fi/miettine/publ.html 

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CVPR 2024 Workshop: Federated Learning for Computer Vision

March 12th, 2024 Daniela Lopez de Luise

                           The Third Workshop on Federated Learning for Computer Vision (FedVision)

in Conjunction with CVPR 2024

6/17/2024 (All Day)

https://fedvision.github.io/fedvision2024/

 

Call for paper

Main research topics of relevance to this workshop include, but are not limited to:

  • Novel FL models for computer vision tasks, e.g., scene understanding, face recognition, object detection, person re-identification, image segmentation, human action recognition, medical image processing, etc.
  • Privacy-preserving machine learning for computer vision tasks
  • Personalized FL models for computer vision applications
  • Novel computer vision applications of FL and privacy-preserving machine learning
  • FL frameworks and tools designed for computer vision applications and benchmarking
  • Novel vision datasets for FL
  • Optimization algorithms for FL, particularly algorithms tolerant of data heterogeneity and resource heterogeneity
  • Approaches that scale FL to larger models, including model pruning and gradient compression techniques
  • Label efficient learning in FL, e.g., self-supervised learning, semi-supervised learning, active learning, etc.
  • Neural architecture search (NAS) for FL
  • Life-long learning in FL
  • Attacks on FL including model poisoning, data poisoning, and corresponding defenses
  • Fairness in FL
  • Federated domain adaptation
  • Privacy leakage and defense in the FL environments
  • Privacy-preserving Generative models for CV
  • FL based CV pipeline for scene understanding and visual analytics

 

Keynote speakers

  • Dr. Lingjuan Lyu, Senior research scientist and team leader in Sony AI
  • Dr. Nathalie Baracaldo, Research Staff Member at IBM’s Almaden Research Center in San Jose, CA
  • Dr. Virginia Smith, Machine Learning Department at Carnegie Mellon University
  • Dr. Peter Richtaìrik, Computer Science at the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
  • Dr. Zhangyang “Atlas” Wang, Department of Electrical and Computer Engineering, The University of Texas at Austin
  • Dr. Mang Ye, School of Computer Science, Wuhan University, China
  • Dr. Peter Kairouz, Google Research, USA

 

Organizers

 

  • Dr. Chen Chen, Assistant Professor, Center for Research in Computer Vision, University of Central Florida
  • Matias Mendieta, Ph.D. Candidate, Center for Research in Computer Vision, University of Central Florida
  • Salman Avestimehr, Professor, University of Southern California, Inaugural Director of the USC-Amazon  Center for Secure and Trusted Machine Learning
  • Zhengming Ding, Assistant Professor, Tulane University
  • Mi Zhang, Associate Professor, Ohio State University
  • Ang Li, Assistant Professor, Department of Electrical and Computer Engineering, University of Maryland (UMD) College Park
  • Bo Li, Associate Professor, Department of Computer Science, University of Chicago
  • Shiqiang Wang, Staff Research Scientist, IBM T. J. Watson Research Center
  • Yang Liu, Associate Professor, Institute for AI Industry Research (AIR), Tsinghua University
  • Gauri Joshi, Associate Professor, Department of Electrical and Computer Engineering, Carnegie Mellon University
  • Saeed Vahidian, Postdoctoral Associate, Department of Electrical and Computer Engineering, Duke University

 

Paper (& supplementary material) Submission Deadline: March 20, 2024 (11:59 PM, PST)

Notification: April 6, 2024 (11:59 PM, PST)

Camera-Ready: April 14, 2024 (11:59 PM, PST)

Accepted papers will be published in conjunction with CVPR 2024 proceedings. Paper submissions will adhere to the CVPR 2024 paper submission style, format, and length restrictions.

The CVPR 2024 author kit is available: https://github.com/cvpr-org/author-kit/releases

Paper submission website: https://cmt3.research.microsoft.com/FEDVISION2024

 

For any questions, please contact Dr. Chen Chen (chen.chen@crcv.ucf.edu)

——————————————————————————————
Dr. Chen Chen, Assistant Professor
CRCV | Center for Research in Computer Vision
HEC 221 | University of Central Florida 
4328 Scorpius St., Orlando, FL 32816-2365
E-mail: chen.chen@crcv.ucf.edu | URL: https://www.crcv.ucf.edu/chenchen/
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