CASA 2025    Call for Papers (Hybrid conference)

https://casa2025.sciencesconf.org/

The 38th International Conference on Computer Animation and Social Agents (CASA 2025) will be held on June 4-6, 2025, in Strasbourg, France. The conference is organized by the University of Strasbourg and the ICube laboratory. Founded in Geneva in 1988 under the name of Computer Animation (CA) by the Computer Graphics Society (CGS), CASA is the oldest international conference in computer animation and social agents in the world.

In the past few years, CASA has been held in Europe, Asia, North America, and Australia. CASA 2025 will provide a great opportunity to interact with leading experts, share your own work, and educate yourself through exposure to the research of your peers from around the world.

This year, the conference will be in HYBRID format. Authors will have the option to present their paper either in person or online.

IMPORTANT DATES

* Submission deadline: March 8, 2025

* Preliminary Notification to Authors: April 15, 2025

* Revised papers submission deadline for CAVW journal: May 5, 2025

* Final Notification of CAVW Journal: May 15, 2025

* Author Registration: May 18 (final deadline)

PAPER SUBMISSION

We invite submissions of research papers on a broad range of topics, including but not limited to Computer Animation, Embodied Agents, Social Agents, Virtual and Augmented Reality, and Visualization (see below for a detailed list). This year, we particularly welcome papers in the following domains: AI image generation, AI video generation, AI music generation, AI storytelling, and AI applications in VR.

Submitted papers will be reviewed by the program committee and papers of high quality will be referred for publication in the Computer Animation and Virtual Worlds (CAVW, Impact Factor: 0.9) journal published by Wiley. The papers accepted as is or with minor revisions will be in a special issue. Those requiring major revision will be given a chance to resubmit and reviewed again by the conference PC for acceptance in a subsequent issue of CAVW. The rest will be either rejected or recommended for publication in conference proceedings. Authors will have to register and present the papers at the conference either onsite or online.

SCOPE AND LIST OF TOPICS

CASA invites submissions on a broad range of topics, including but not limited to:

Computer Animation

  *   Motion Control

  *   Motion Capture & Retargeting

  *   Path Planning

  *   Physics-based Animation

  *   Vision-based Techniques for Animation

  *   Behavioral Animation

  *   Deformation

  *   Facial Animation

  *   Image-based Animation

  *   AI Storytelling

  *   AI Visual Generator

  *   Group and Crowd Simulation

  *   Modeling Natural Phenomena

  *   Deep Learning based Animation

  *   Fluid Animation

  *   Multi-scale Models

  *   Animation Compression & Transmission

  *   Machine Learning for Animation

  *   Advanced Multimodal Models

  *   Game-based Learning

Virtual Worlds

  *   Virtual Heritage

  *   Humanoid and Social Robots

  *   User Studies on AI or Robots Acceptance

  *   Machine Learning for VR and AR

  *   Artificial Agents in Virtual Reality

  *   Mixed and Augmented Reality

  *   Population Generation for Virtual Worlds

  *   Virtual Cities

  *   Virtual Humans and Avatars

  *   Anthropometric Virtual Human Models

  *   Digital Clones

  *   VR Health Applications

  *   Shared Virtual Environments

  *   Semantics & Ontologies for Animation in VR

  *   AI applications in VR and AR experiences

  *   Anthropometric Virtual Human Models

  *   Metaverse

  *   3D Telepresence

  *   Haptics

  *   Locomotion and Navigation

  *   Presence and Immersion

  *   Cultural Heritage Applications

  *   Social Agents

WEBSITE: https://casa2025.sciencesconf.org/ 

CONFERENCE CO-CHAIRS

  *   Frederic Cordier (University of Haute-Alsace, France)

  *   Kun Zhou (Zhejiang University, China)

  *   Nadia Magnenat-Thalmann (MIRALab–University of Geneva, Switzerland)

PROGRAM CO-CHAIRS

  *   Christos Mousas (Purdue University, United States)

  *   Hyewon Seo (CNRS–University of Strasbourg, France)

  *   Daniel Thalmann (École Polytechnique Fédérale de Lausanne, Switzerland)

INTERNATIONAL COORDINATOR

  *   Bin Sheng (Shanghai Jiao Tong University)

PUBLICITY CHAIR

  *   Xiaosong Yang  (Bournemouth University, UK)

ORGANIZATION CHAIR

  *   Hadrien Courtecuisse  (CNRS–University of Strasbourg, France)

The 34th Jyvaskyla Summer School will be organized on August 4–15, 2025 in the beautiful campus located next to the lake, 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 (but the participants are responsible for their own travel and accommodation costs). 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: https://www.jyu.fi/en/study-with-us/summer-and-winter-schools/jyvaskyla-summer-school/jyvaskyla-summer-school-course-programme

For example, we offer the following course related to multiobjective optimization on August 11-15:

COM3: Interactive Multiobjective Optimization: Applications and Tools to Support Decision Making   

Lecturers: Dr. Giovanni Misitano, Dr. Bhupinder Saini, Dr. Giomara Lárraga, Dr. Juho Roponen and Juuso Pajasmaa (all from the Multiobjective Optimization Group at the University of Jyvaskyla) 

Modes of study: Attendance and exercises, optional final project

Credits: 2/4 ECTS 

The course will award 2-4 credits depending which option participants choose:

– Option 1: 2 credits for attending lectures and exercise sessions;

– Option 2: 2 additional credits will be awarded to participants who, on top of attending lectures and practical sessions, also complete a final project.

Evaluation: Pass/Fail. The minimum requirement for passing the course is to take part in the daily lectures and exercise sessions.

Contents: Real-life optimization problems rarely involve only a single objective. Instead, meaningful decision-making requires optimizing multiple conflicting objectives simultaneously. To navigate these conflicts and find a satisfactory solution, preference information from a domain expert, the decision maker, is essential. Based on these preferences, we can search for solutions that best align with their goals. However, exploring such problems is often computationally and cognitively demanding, making decision support crucial.

Understanding how a decision maker expresses their preferences and how these preferences are utilized is crucial. This course introduces interactive multiobjective optimization methods, which address these key questions. Given the increasing role of data in real-world decision-making, we will also explore techniques for modeling data-driven multiobjective optimization problems. Through practical examples, we will examine and solve various real-world multiobjective problems, including both data-driven and simulator-based cases.

We will explore various interactive multiobjective optimization methods, including scalarization-based approaches and evolutionary algorithms. Additionally, we will examine how different methods can be combined and guide participants in developing their own approaches. The course will also cover graphical interfaces for interactive methods.. Hands-on experience with these concepts will be facilitated through the 2.0 version of the DESDEO framework [1], which provides the necessary tools for practical application.

Each day will focus on a central theme in interactive multiobjective optimization. The morning sessions will introduce key concepts related to the day's theme, while the afternoon sessions will provide hands-on experience applying these ideas using the DESDEO framework. To reinforce learning, an optional final project will be available, allowing participants to deepen their understanding and even contribute to the open-source DESDEO framework.

The final project is required for those seeking 4 ECTS credits. Participants who attend daily lectures and exercise sessions without the final project will receive 2 ECTS credits.

[1] G. Misitano, B. S. Saini, B. Afsar, B. Shavazipour and K. Miettinen, 'DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization,' IEEE Access, vol. 9, pp. 148277-148295, 2021, doi: 10.1109/ACCESS.2021.3123825.

Learning outcomes: After completing the course, participants will have a solid understanding of multiobjective optimization and the interactive methods that support decision-making. They will be familiar with both scalarization-based and evolutionary interactive methods, as well as various visualization and GUI techniques for assisting decision makers. Additionally, students will gain the necessary prerequisites to apply the DESDEO framework in modeling and solving their own data-driven optimization problems.

Participants are encouraged to bring their own laptops and optimization problems (if any) to the course!

Prerequisites: Participants are expected to have prior knowledge of the following concepts:

– Python (basic programming skills)

– Fundamentals of calculus

– Optimization and mathematical programming

– Basics of single-objective optimization

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

With best regards, Kaisa Miettinen

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

Vice-rector Kaisa Miettinen, PhD

FI-40014 University of Jyvaskyla, Finland

Professor in Industrial Optimization

Multiobjective Optimization Group: https://optgroup.it.jyu.fi/

– – –

* 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