May 2026 - Infovis - infovis.org

Expressions of Interest to contribute to EuroVIS 2026 - PhD Education Track : You, Me and the VIS PhD
by Turkay, Cagatay 06 May '26

06 May '26

Hi everyone, We are organizing an activity track at the EuroVis 2026 conference<https://eurovis.org.uk/> where we would like to bring together PhD students and academics for a focused activity on PhD Education in Data Visualization. We would like to discuss PhD study, skills and supervision for students and staff and involved in PhD Education in Visualization by connecting, sharing best practice and developing ideas for the future. Details of the activity can be found on this page<https://jsndyks.github.io/diverse-cdt/eurovis/>. The activity is currently scheduled for Tuesday, June 9th in the afternoon (subject to changes until the EuroVis programme is finalized). To kick-start the activity, we are inviting current or prospective PhD students, at any stage in their studies or planning, to introduce themselves and connect with fellow PhDs and supervisors. This is a great opportunity to build a network of fellow PhDs, hear from experienced academics on their PhD experience and contribute to discussions where we will aim to imagine the visualization PhDs of the future. Please submit your expression of interest through a straightforward submission. The submission is a single visual that tells us something about you and your PhD. This can be anything, submitted in advance, but might involve: * your approach to visualization / design * something important to your PhD * why you love visualization * your favourite / least favourite data vis * something about you (or your data, or your cat) * the future of visualization * something you care about You can request a 1, 3 or 5 minute presentation during the submission and we do our best to fit that in during the day! The deadline to send your expressions of interest to participate are: 31 May 2026 (Anywhere on Earth) Submit your visual (PDF) and details through this Google Form<https://docs.google.com/forms/d/e/1FAIpQLSfRlecXFRfDxf9SgmfccJmDEGJYRcz6c02…>. Any questions, please do not hesitate to contact Cagatay Turkay (cagatay.turkay(a)warwick.ac.uk<mailto:cagatay.turkay@warwick.ac.uk>) and/or Jason Dykes (J.Dykes(a)citystgeorges.ac.uk<mailto:J.Dykes@citystgeorges.ac.uk>). We will appreciate if you can share this widely. If you are a supervisor and have PhD students coming to EuroVis, please flag this session to them as well. Thanks! Cagatay & Jason — Dr Cagatay Turkay Professor Director, Centre for Interdisciplinary Methodologies Co-Director, EPSRC DIVERSE CDT University of Warwick w: https://warwick.ac.uk/fac/cross_fac/cim/people/cagatay-turkay

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IEEE vis4climate workshop
by Georgia Panagiotidou 05 May '26

05 May '26

We are pleased to invite you to **vis4climate**, the 4th workshop on Visualization and Climate Change. This half-day workshop will be held at IEEE VIS 2026 in Boston and aims to build a strong transdisciplinary community of researchers and practitioners working in visualization or climate change related areas. The workshop brings together researchers and practitioners from visualization, climate science, policy, and other fields that relate to climate change to discuss how visualization can support climate mitigation, adaptation, and communication. We welcome submissions across research, reflections, and demos/pictorials. Submission deadline: June 25 Location: Boston Time: November 9 to 13 Details: https://vis4climate.ivia.ch/workshop The plan is for a hybrid setup to increase accessibility and allow unconstrained participation. We look forward to receiving your submissions and to building a diverse community of researchers and practitioners interested in visualization for climate. The vis4climate Organizing Committee: Christina Humer, Andreas Hinterreiter, Aymeric Ferron, Marc Streit, Menna El-Assady, Luiz A. Morais, Georgia Panagiotidou, Benjamin Bach, and Fanny Chevalier

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DeepLearn 2026: early registration May 22
by David Silva - IRDTA 02 May '26

02 May '26

****************************************************** 13th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2026 Orléans, France July 20-24, 2026 https://deeplearn.irdta.eu/2026/ ****************************************************** Co-organized by: University of Orléans Centre Val de Loire Doctoral College Institute for Research Development, Training and Advice – IRDTA Luxembourg/London ****************************************************** Early registration: May 22, 2026 ****************************************************** 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 16 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 https://www.univ-orleans.fr/en 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), Convergence Theory: How Fast Do Discrete Diffusion Models Generate? Le Song (Mohamed bin Zayed University of Artificial Intelligence), Towards AI-Driven Digital Organism: A System of Multiscale Foundation Models for Biology PROFESSORS AND COURSES: Nitesh Chawla (University of Notre Dame), [intermediate] Synthetic Data Generation and Learning from Imbalanced Data: From SMOTE to LLMs Jianfei Chen (Tsinghua University), [intermediate] Efficient Large Model Training and Inference 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 Applications in Machine Learning and Foundation Models 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: Integrated Multimodal Sensing, Controlled Inference, and Spatio-Temporal Attention Yan Liu (University of Southern California), [intermediate] Time Series Foundation Models: From Forecasting to Reasoning Zhijin Qin (Tsinghua University), [intermediate/advanced] Token-Based Semantic Communications Aarti Singh (Carnegie Mellon University), [intermediate] Human Centered AI: Challenges and Opportunities Suvrit Sra (Technical University of Munich), [introductory/intermediate] Introduction to the Theory of Learning with Transformers Ivor Tsang (A*STAR Centre for Frontier AI Research), [introductory/intermediate] Long-Horizon Agentic Intelligence 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 Large Language Models 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(a)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(a)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 https://deeplearn.irdta.eu/2026/sponsors/ 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) Florian Nowicki (Orléans, social networks) Philippe Ravier (Orléans, local chair) David Silva (London, organization chair) REGISTRATION: It has to be done at https://deeplearn.irdta.eu/2026/registration/ 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 are available at https://deeplearn.irdta.eu/2026/accommodation/ 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: david(a)irdta.eu ACKNOWLEDGMENTS: Université d’Orléans Collège Doctoral Centre-Val de Loire Universitat Rovira i Virgili Institute for Research Development, Training and Advice – IRDTA, Luxembourg/London

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GD 2026 – Third Call for Papers – Deadline 6 May
by Miksch Silvia 01 May '26

01 May '26

*Call for Papers: The 34th International Symposium on Graph Drawing and Network Visualization (GD 2026)* */August 17-21, 2026, St. Catharines, Canada/* _https://graphdrawing.github.io/gd2026/ <https://graphdrawing.github.io/gd2026/>_ *Graph Drawing *is concerned with the geometric representation of graphs and constitutes the algorithmic core of *Network Visualization*. Graph Drawing and Network Visualization are motivated by applications for which it is crucial to visually analyze and interact with relational datasets. Application areas include data science, social sciences, web computing, information systems, life sciences, geography, business intelligence, information security, and software engineering. The International Symposium on Graph Drawing and Network Visualization has been the main annual conference in this area for more than 30 years. Its focus is on combinatorial and algorithmic aspects of graph drawing, their experimental evaluation, as well as the design of network visualization systems and interfaces. Researchers and practitioners working on any aspects of graph drawing and network visualization are invited to contribute papers and posters and to participate in the symposium as well as the graph drawing contest. GD 2026 will be held at Brock University in St. Catharines, Canada, from August 17-21, 2026. A PhD school will take place August 17-18, 2026, followed by a reception on the evening of August 18. GD 2026 is designed to be held on-site. It is expected that regular papers are presented on site by one of the authors. To address global challenges and as an offer for authors who are unable to attend, we allow for a limited number of remote presentations, as further explained below. * * *Important dates*  Abstract Deadline: Wed May 6, 2026 (AoE) Paper (long and short) Deadline: Wed May 13, 2026 (AoE) Paper (long and short) Notification: Wed June 24, 2026 (AoE) Poster Deadline: Wed July 8, 2026 (AoE) Poster Notification: Wed July 22, 2026 (AoE) Camera-ready Version (papers and posters): Wed July 29, 2026 (AoE) Contest Deadline: Wed August 5, 2026 (AoE) PhD School: Mon August 17 – Tue August 18, 2026 Symposium: Wed August 19 – Fri August 21, 2026 *Conferences Nearby in Time and Location* The 38th Canadian Conference on Computational Geometry (_CCCG 2026 <https://sites.google.com/view/cccg-2026/home>_) will be held at Lakehead University’s Orillia Campus in Orillia, Ontario, from August 12 to 14, 2026. * Tracks* We invite authors to submit work describing original research of theoretical or practical significance to graph drawing and network visualization. To promote a balanced coverage of the field, GD has two distinct tracks, and contributions submitted to one track will not compete with contributions submitted to the other track. *Track 1: Combinatorial and algorithmic aspects* This track is mainly devoted to *fundamental theoretical graph drawing advances*, such as combinatorial and algorithmic aspects. We aim at covering a diverse set of topics, which for this track includes (but is not limited to): * Design and analysis of graph drawing algorithms * Geometric and topological graph theory * Computational topology of graphs on surfaces * Graph representations * Geometric advances and computing in graph drawing * Combinatorics and optimization in graph drawing *Track 2: Experimental, applied, and network visualization aspects* This track is mainly devoted to *conceptual and applied aspects of network visualization in the scope of* * graph drawing*, such as experimental evaluations of graph drawing and network visualization related algorithms, the development and/or evaluation of related libraries and tools, or systems and interfaces in different application areas. We aim at covering a diverse set of topics, which for this track includes (but is not limited to): * Engineering of graph drawing algorithms and network visualization approaches * Interfaces, methods, and high-quality tools for interacting with graphs and networks * Benchmarks and experimental studies in the context of graph drawing and network visualization * Cognitive studies on network visualization aesthetics and user interaction * Visualization of networks in real-world applications * Machine learning methods in graph drawing and network visualization * Graph drawing & network visualization for AI explainability and trustworthiness * * *Contribution Types* Perpendicular to the tracks, GD supports three contribution types, as well as a contest. *Long Papers* The standard contribution type is a /long paper/ that describes relevant and original research in full detail. Accepted papers in this category will be assigned a standard time slot for presentation during the conference. *Short Papers* In addition to long papers, there will be a separate category for /short papers/. Here, we welcome smaller and less extensive contributions on relevant topics. Accepted papers in this category will be assigned a shorter time for presentation during the conference. Short papers undergo the same competitive selection process as long papers. *Posters* Finally, we also solicit /poster/ submissions. Accepted posters will be presented in the poster session, and will provide a forum for the communication of late-breaking research results (which may also appear elsewhere) to the GD community. *Contest* The traditional Graph Drawing Contest is held before and during the conference. Details are provided at the _website <https://mozart.diei.unipg.it/gdcontest/2025/>_. Winning submissions will be invited by the contest committee to submit a /contest contribution/, which will appear in the proceedings. * * *Submission Format* The proceedings will be published in the open-access _LIPIcs <https://www.dagstuhl.de/en/publishing/series/details/lipics>_series. To facilitate the process, submissions have to be prepared in accordance with the _LIPIcs author instructions <https://submission.dagstuhl.de/series/details/LIPIcs#author>_. The page provides links to the LIPIcs class file along with an example and detailed author instructions. For the submission, the use of the LaTeX class file _gd-lipics-v <https://graphdrawing.github.io/gd2026/assets/template/gd-lipics-v3.cls>3 <https://graphdrawing.github.io/gd2026/assets/template/gd-lipics-v3.cls>.cls <https://graphdrawing.github.io/gd2026/assets/template/gd-lipics-v3.cls>_is requested. The class file is a wrapper around the standard LIPIcs class and implements line counting, see _CG-linecount.pdf <https://www.computational-geometry.org/guidelines/linecount_2022_09_19.pdf>_for details, as well as additional macros. Please use the \category macro to specify the track and contribution type, and use the macros \GAIDecl and \USEDecl to include your generative AI declaration and/or user study ethics declaration (see "policies" below). These will be formatted as part of the front matter, and not count towards your line limit. Submissions must not exceed the following limits: * 500 lines for long papers, * 250 lines for short papers, * 80 lines for poster abstracts, * 100 lines for contest contributions (by invitation only). The above limits do not include front matter (title, authors, affiliations, classification, etc.), acknowledgements, references, or appendices. The class files provide line counting which should be accurate in most cases. Authors should avoid substantial amounts of text in unnumbered lines. Accepted papers will have additional space to facilitate incorporating reviewer comments. The claims of long and short papers should be fully substantiated. If this information does not fit within the line limit, the authors should include it in a clearly marked appendix, whose length is not constrained and which the reviewers may read at their own discretion. For poster submissions, no appendix is expected. We also encourage authors to avoid "et al." in citations in favor of an equal mention of the surnames of all authors. For references with few authors, it is recommended to name all of them; if the number of authors is large, consider writing "(It is shown that) X [#]" or "The authors in [#] show that X" instead of "A et al. [#] show that X". *Submission Process* Papers should be submitted electronically via _Easychair <https://easychair.org/conferences/?conf=gd2026>_. Authors of posters should prepare an abstract that must be submitted together with the poster itself. Each submission will thus consist of two pdf files (the abstract and the poster). Selected papers from Track 1 and Track 2 will be invited for submission to a special issue of the *Journal of Graph Algorithms and Applications (JGAA)*. The authors of two selected papers in Track 2 will be invited to submit a substantially extended and enhanced version of their work to *IEEE Transactions on Visualization and Computer Graphics (TVCG)*. A special TVCG papers session at the Graph Drawing conference will also feature regular TVCG papers. Further details can be found at _https://www.computer.org/digital-library/journals/tvcg/tvcg-partners-with-… <https://www.computer.org/digital-library/journals/tvcg/tvcg-partners-with-c…>_ * * *Policies* GD implements a number of policies. */AI policy/* Authors are not prohibited from using generative AI (GAI), but are required to be transparent about its use and are responsible for complying with all relevant policies. PC members are prohibited from using GAI during the review process, because submitted manuscripts are confidential and may not be shared with AI platforms. The full AI policy can be found at _http://graphdrawing.org/ai.html <http://graphdrawing.org/safetoc.html>_ */User Study Ethics policy/* If a paper makes use of data from human subjects, the collection and use of such data should have been conducted carefully and should adhere to ethical standards for responsible research practice, as well as data protection regulations. The full ethics policy can be found at _http://graphdrawing.org/userstudies.html <http://graphdrawing.org/safetoc.html>_ */Code of conduct/* GD is dedicated to providing an environment that is free from harassment, bullying, discrimination, and retaliation for all participants, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices./ / The full code of conduct can be found at _http://graphdrawing.org/safetoc.html <http://graphdrawing.org/safetoc.html>_ * * *MISC TOPICS* *Lightweight Double-Blind Review Process* The review process of long and short papers will be handled in a *lightweight double-blind mode*. This means that authors are not allowed to reveal their identity in the submitted paper, but are free to disseminate draft versions of the paper prior to the conference and to give talks on the topic as they normally would. In particular, the submitted paper should not contain the authors’ names, affiliations, and email addresses. References to their own related work are allowed, as long as the supporting text maintains anonymity (e.g., using sentences in the third person). Members of the Program Committee will not have the identity of the authors of any paper revealed to them during the entire review process. To handle conflicts of interest effectively, authors will be required to declare conflicts of interest with PC members when they submit their paper. Poster submissions will be evaluated by the Program Committee in a *single-blind mode*. In particular, the submitted abstract should contain the authors’ names, affiliations, and email addresses. *Awards* For each of the two tracks, the Program Committee of GD 2026 will bestow a *Best Paper Award*. In addition, to recognize the effort of participants to present their work and to prepare their posters in a clear and elegant way, there will be a *Best Presentation Award *and a *Best Poster Award *voted on by the GD 2026 attendees. Finally, there will be awards for the best submissions in the *Graph Drawing Contest*, decided independently by the Contest Committee. *Remote Presentation* GD 2026 is an in-person meeting. Authors of accepted papers are expected to present their results at the conference. For people who for legitimate reasons cannot participate in person we offer the possibility for remote presentation. To this end, authors may indicate their preference for a remote presentation at the time of submitting their article. Such papers are evaluated and selected by the program committee by applying the same high standards as for the other papers. There is a limit of at most four remote presentations. In case of more requests, decisions may depend on the validity of the reasons mentioned. In all cases, an author of each remote presentation has to register for the conference. *Rules for Submission* Results that have been previously published (or are scheduled for publication) in another conference proceedings or journal, as well as simultaneous submissions of results to other conferences with published proceedings or journals are not permitted, except for poster submissions. With the exception of remote presentations, each paper or poster must be presented at the conference by an author, otherwise the paper can be excluded from publication in the proceedings.

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