AVI 2026: Advanced Visual Interfaces – Call for Contributions

October 21st, 2025 Daniela Lopez de Luise
18th International Conference on Advanced Visual Interfaces (AVI) 2026

Interactive Creativity: Agencies, Interfaces, and Ethics

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                     8-12 June 2026

                      Venice, Italy

                http://unive.it/avi2026


In-Cooperation with ACM SIGCHI and SIGWEB

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IMPORTANT DATES 

Workshop proposals:

  • Submission: December 14, 2025
  • Notification: December 21, 2025

 

Long and Short papers: 

  • Abstract submission: January 18, 2026
  • Paper submission: January 25, 2026

 

Interactive Experiences, Demo and Poster papers: 

  • March 9, 2026

 

Doctoral Consortium papers:

  • March 29, 2026

 

Tutorial proposals: 

  • March 29, 2026

 

(all deadlines are 23:59, AoE)

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DeepLearn 2026: early registration November 11

October 21st, 2025 Daniela Lopez de Luise
13th INTERNATIONAL SCHOOL ON DEEP LEARNING

DeepLearn 2026

Orléans, France

July 20-24, 2026

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Co-organized by:

University of Orléans

Centre Val de Loire Doctoral College

Institute for Research Development, Training and Advice – IRDTA
Luxembourg/London

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Early registration: November 11, 2025

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SCOPE:

DeepLearn 2026 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Luleå, Bournemouth, Bari, and Porto.

Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedicine and healthcare, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, business and finance, biotechnology, physics and astrophysics, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, materials design, video technology, social systems, earth and sustainability, mathematical proofs, etc. etc.

The field is also raising a number of relevant questions about efficiency and robustness of the algorithms, explainability, transparency, interpretability, risks and safety, as well as important ethical concerns at the frontier of current knowledge that deserve careful multidisciplinary discussion.

Most deep learning subareas will be displayed and main challenges identified through 18 four-hour and a half courses, 2 keynote lectures, 1 round table, and a hackathon competition among participants. Renowned academics and industry pioneers will lecture and share their views with the audience. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.

ADDRESSED TO:

Graduates, postgraduates and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, hence people less or more advanced in their career will be welcome as well.

Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses.

Overall, DeepLearn 2026 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.

VENUE:

DeepLearn 2026 will take place in Orléans, located in the heart of the Loire Valley, which was declared by UNESCO a World Heritage Site in 2000. The venue will be:

University of Orléans
Faculty of Law, Economics and Management
11 rue de Blois
45100 Orléans, France

STRUCTURE:

3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.

All lectures will be videorecorded. Participants will be able to watch them again for 45 days after the event.

An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also companies will be able to present their industrial developments for 10 minutes.

The school will include a hackathon, where participants will be able to work in teams to tackle several machine learning challenges.

Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event.

KEYNOTE SPEAKERS:

Yingbin Liang (Ohio State University), Theoretical Characterization of Training Transformers for Chain-of-Thought Reasoning

Le Song (Mohamed bin Zayed University of Artificial Intelligence), Multiscale Foundation Models for Biology

PROFESSORS AND COURSES: (to be completed)

Yuejie Chi (Yale University), [introductory/intermediate] Statistical and Algorithmic Foundations of Reinforcement Learning

Bo Han (Hong Kong Baptist University), [introductory/intermediate] Trustworthy Machine Learning from Data to Models

Jiawei Han (University of Illinois Urbana-Champaign), [intermediate] Structure-Guided, Theme-Based Knowledge Discovery with Large Language Models

Mingyi Hong (University of Minnesota), [intermediate] Bilevel Optimization: Theory, Algorithms and Application in AI

Cho-Jui Hsieh (University of California Los Angeles), [intermediate/advanced] Optimizers for Large Language Model Training

Furong Huang (University of Maryland), [advanced] Generative AI Agents

Tara Javidi (University of California San Diego), [intermediate] Active Physical Intelligence for Industrial Scale Monitoring

Zhijin Qin (Tsinghua University), [intermediate/advanced] Semantic Communications

Aarti Singh (Carnegie Mellon University), [intermediate] Human Centered AI: Challenges and Opportunities

Masashi Sugiyama (University of Tokyo), [intermediate] Learning from Imperfect Supervision

Zhangyang (Atlas) Wang (University of Texas Austin), [intermediate/advanced] Beyond Sparsity or Low Rank: In-Between Neural and Symbolic Learning

Ming-Hsuan Yang (University of California Merced), [advanced] Recent Advances in Multimodal Understanding and Generation

Tong Zhang (University of Illinois Urbana-Champaign), [introductory/intermediate] Reinforcement Learning for Foundation Models

Jun Zhu (Tsinghua University), [introductory/advanced] Generative Models: from Virtual to Physical World

OPEN SESSION:

An open session will collect 5-minute voluntary oral presentations of work in progress by participants.

They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by July 12, 2026.

INDUSTRIAL SESSION:

A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry.

Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event.

Abstracts have to be submitted to david@irdta.eu by July 12, 2026.

HACKATHON:

A hackathon will take place, where participants can voluntarily work in teams to tackle several machine learning challenges. They will be coordinated by Professor Sergei V. Gleyzer (University of Alabama). The challenges will be released 2 weeks before the beginning of the school. A jury will judge the submissions and the winners of each challenge will be announced by the end of August 2026. The winning teams will receive a modest monetary prize and the runners-up will get a certificate.

SPONSORS:

Companies/institutions/organizations willing to be sponsors of the event can download the sponsorship leaflet from

ORGANIZING COMMITTEE:

Karim Abed-Meraim (Orléans, local co-chair)
Sergei V. Gleyzer (Tuscaloosa, hackathon chair)
Meryem Jabloun (Orléans, local co-chair)
Carlos Martín-Vide (Tarragona, program chair)
Santiago Montes (Tarragona, webpage)
Sara Morales (Luxembourg, finances)
Philippe Ravier (Orléans, local chair)
David Silva (London, organization chair)

REGISTRATION:

It has to be done at

The selection of 6 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course.

Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.

FEES:

Fees comprise access to all program activities and lunches.

There are several early registration deadlines. Fees depend on the registration deadline.

The fees for on site and for online participation are the same.

ACCOMMODATION:

Accommodation suggestions will be available in due time at

CERTIFICATE:

A certificate of successful participation will be delivered indicating the number of hours of academic activities (40). This should be sufficient for those participants who plan to request ECTS recognition from their home university.

QUESTIONS AND FURTHER INFORMATION:

ACKNOWLEDGMENTS:

Université d’Orléans

Collège Doctoral Centre-Val de Loire

Universitat Rovira i Virgili

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International Workshop on Deep Learning for Biomedical Big Data Analysis (DL4BBDA) – IEEE Big Data

October 21st, 2025 Daniela Lopez de Luise
The International Workshop on Deep Learning for Biomedical Big Data Analysis (DL4BBDA) will be held online, from 8 to 11 december 2025, in conjunction with the IEEE International Conference on Big Data (IEEE BigData 2025).

https://dl4bbda2025.sciencesconf.org/

Overview

Due to growing innovations in the biomedical research field, substantial huge volumes of data are generated needing to be explored, analyzed and processed using advanced algorithms and techniques. In artificial intelligence, Deep learning (DL) has received a great attention to solve difficult and complex problems in various domains. Its ability to train learning models for large-volume data as well as their performances compared to conventional machine learning algorithms, as made it a major asset. This workshop aims to present and discuss the recent advances in deep learning for biomedical data analysis and processing. It is an opportunity to bring together academic and industrial scientists to discuss recent advances.

Topics of interest include, but are not limited to, the following:

– DL for biomedical signal analysis and processing (e.g., EEG, EMG, ECG, EOG, …)
– DL for medical image analysis and processing (e.g., CT, MRI, fMRI, PET, SPECT, DTI, …)
– DL for diseases detection and diagnosis (e.g., Epileptic seizure, Alzheimer, Sleep disorders, …)
– DL for pandemics detection and forecasting
– DL for biometrics
– DL in biomedical engineering
– DL for health informatics (healthcare, e-health, m-health, telehealth, …)
– DL for brain-computer interfaces
– DL for neural rehabilitation engineering
– Generative AI in biomedical research
– Related applications

Important Dates

Oct. 26, 2025 (11:59 pm CST): Due date for full workshop papers submission
Nov. 15, 2025: Notification of paper acceptance to authors
Nov. 23, 2025: Camera-ready of accepted papers
Dec 8-11, 2025: Workshops

Paper submission

– Please submit a full-length paper (up to 10 pages IEEE 2-column format including references) or a short-length paper (5 to 7 pages including references)  through the online submission system. 
– Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines. See link to “formatting instructions” here : https://www.ieee.org/conferences/publishing/templates.html
– Electronic submissions in PDF format are required.
– All papers accepted for this workshop will be published in the Workshop Proceedings of IEEE Big Data Conference, made available in the IEEE eXplore digital library.

Online Submission 

https://wi-lab.com/cyberchair/2025/bigdata25/scripts/submit.php?subarea=S48&undisplay_detail=1&wh=/cyberchair/2025/bigdata25/scripts/ws_submit.php

Contact
Prof. Larbi Boubchir (Workshop Chair)
University of Paris 8, France
E-mail: larbi.boubchir@univ-paris8.fr

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Call for Paper – MedPRAI 2026

October 21st, 2025 Daniela Lopez de Luise
Dear Colleagues,
We are delighted to invite you to contribute to the 7th Mediterranean Conference on Pattern Recognition and Artificial Intelligence (MedPRAI 2026), taking place on January 23–24, 2026, at Istinye University, Istanbul, Turkiye. The conference will be held in a Hybrid Mode (Online + In-Person).
MedPRAI 2026 is a premier platform for researchers and practitioners from academia and industry to share their latest findings, innovative methodologies, and applications in the fields of Pattern Recognition, Artificial Intelligence, and related technologies.
Key Areas for Submission (Topics of Interest)
We welcome submissions on original research across all related subareas, including (but not limited to) the following detailed topics:
Artificial Intelligence and Applications
Computer Vision and Image Processing
Blockchain, IoT, and Internet of Things

Publication & Indexing
All accepted and presented papers will be submitted for inclusion into Springer proceedings (Lecture Notes in Networks and Systems – LNNS Series) and indexed in prominent databases such as SCOPUS and EI Compendex.
Important Dates
Deadline
Date
Full Paper Submission
November 30, 2025
Notification to Authors
December 30, 2025
Camera Ready Submission
January 20, 2026
Conference Dates
January 23–24, 2026


We warmly encourage you to submit your high-quality research work and join an international community of scholars and innovators shaping the future of AI and Pattern Recognition.
🔗 More Information & Submission Guidelines: 
www.medprai.com     📧 Contact: info@medprai.com” target=”_blank”>info@medprai.com
We look forward to your valuable contributions and to welcoming you to Istanbul!
Best regards,
Shallena Akbar General Secretary 7th Mediterranean Conference on Pattern Recognition and Artificial Intelligence (MedPRAI 2026)
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CFP for ICCV 2025 Artificial Social Intelligence Workshop

October 19th, 2025 Daniela Lopez de Luise
We welcome and invite you to participate in the upcoming ICCV 2025 Workshop on “Artificial Social Intelligence”. This full-day workshop will be held in Honolulu, Hawaii with hybrid participation available.  
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Event: Workshop on Artificial Social Intelligence (4th edition)
Location: Co-located with ICCV 2025 in Honolulu

Time: Full-Day Workshop 
Website: https://sites.google.com/andrew.cmu.edu/social-ai-iccv-25/ 

June 27 deadline for archival papers
August 1 deadline for extended abstracts (non-archival) 
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Workshop Overview: Artificial Social Intelligence

Humans use social intelligence to interpret and navigate multimodal interactions with other agents in our shared world. As artificial intelligence (AI) systems become pervasive in human life, these systems will need social intelligence to seamlessly work with and around humans. There has been a growing interest across computing communities to build competencies for core social intelligence abilities in AI systems, such as social perception (e.g., perceiving gestures), social reasoning (e.g., inferring human intent), and social memory (e.g., representing social knowledge). Artificial social intelligence could enable richer human machine interactions to support human well-being in homes, hospitals, manufacturing, and other settings.  

Research priorities and modeling frameworks to build social intelligence in AI systems can vary across computing communities (and have varied in prior decades). What are core technical challenges and opportunities for cross-field collaboration to advance the science of social intelligence and socially-intelligent AI? A particular focus of the workshop keynotes and discussions will be algorithms for reasoning, multimodality, and embodied learning in socially-intelligent AI systems. Our ICCV 2025 workshop welcomes anyone interested in artificial social intelligence to join us to discuss these topics and more! 

Call-for-Papers

Our workshop will accept submissions to 2 tracks: Papers (archival) and Extended Abstracts (non-archival). 

Papers are 4-8 pages (excluding references) and will be published in the ICCV workshop proceedings. Papers will be considered for oral or poster presentation at the workshop.

Extended Abstracts are up to 2 pages (excluding references) and will not be published in the proceedings, and will be presented as posters. Extended abstracts may be ongoing work, recently published papers at other venues, or papers published at the main ICCV conference.

Topics of interest for papers and extended abstracts include, but are not limited to, the following:

  • Social reasoning algorithms
  • Social perception and social signal analysis
  • Affective computing (e.g. predicting emotion, valence)
  • Generating social signals in artificial agents (e.g., gesture generation) 
  • Social agent frameworks for dynamic social interaction
  • Social robots and socially-intelligent human-robot interaction
  • Datasets, benchmarks, and community resources
  • Ethical considerations for Social AI
  • Applications of artificial social intelligence

Submissions will follow the ICCV paper template and guidelines and must be anonymized. Submissions for the paper track may include an optional appendix after references. Openreview submission information will be listed on the website. 

Important Dates


Papers Track [archival]
Deadline: June 27th, 2025
Notification: July 11th, 2025

Extended Abstracts Track [non-archival]
Deadline: August 1st, 2025
Notification: August 15th, 2025

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Organizing Committee

Leena Mathur, Carnegie Mellon University
Fiona Ryan, Georgia Tech
Anshul Gupta, EPFL
Evonne Ng, Meta
Shiry Ginosar, TTIC/Google
Sangmin Lee, Sungkyunkwan University 
Paul Pu Liang, MIT
Judy Hoffman, Georgia Tech
James Rehg, University of Illinois Urbana-Champaign
Louis-Philippe Morency, Carnegie Mellon University/Meta

Contact 

If you have any questions about the workshop or paper submissions, please email Leena Mathur (lmathur@cs.cmu.edu) or Fiona Ryan (fkryan@gatech.edu)  

Best regards,
Leena, Fiona, Anshul, Evonne, Shiry, Sangmin, Paul, Judy, James, Louis-Philippe 

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