IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics topics, including modeling, rendering, animation, (data) visualization, HCI/user interfaces, novel applications, hardware architectures, haptics, and virtual- and augmented-reality systems.

From specific algorithms to full system implementations, CG&A offers a unique combination of peer-reviewed feature articles and informal departments. Theme issues guest edited by leading researchers in their fields track the latest developments and trends in computer-generated graphical content, while tutorials and surveys provide a broad overview of interesting and timely topics. Regular departments further explore the core areas of graphics as well as extend into topics such as usability, education, history, and opinion. Each issue, the story of our cover focuses on creative applications of the technology by an artist or designer. Published six times a year, CG&A is indispensable reading for people working at the leading edge of computer-generated graphics technology and its applications in everything from business to the arts.

CG&A is the oldest and still the only publication with such a breath of topics and its mix of opinion pieces and peer-reviewed research articles. We pride ourselves on both our high impact factor and fast turnaround time for submitted content.

Special Issue on Breakthroughs, Challenges, and Opportunities in Biological Data Visualization
Submission Date: 2025-03-24

The rapidly expanding data generated by advanced methods in biology is creating enormous  challenges at the interface between humans and biological data that can be represented and  analyzed visually. To meet these challenges, a blend of methodology from the visualization,  bioinformatics and biology domains is required. This methodology encompasses perception and  design knowledge, algorithm design, techniques for analyzing and visualizing big data,  statistics, and specific domain knowledge for different application problems. Powerful and  integrative visualization methods are necessary, as well as methods for visually communicating  the outcome of computational analytical methods and findings. 

This special issue aims to highlight new challenges in biological data visualization (BioVis), and  state-of-the-art solutions created by the vibrant BioVis community. We invite contributions on all  aspects of data visualization in biology, from molecular to cell, tissue, organism and population  biology. Topics of interest include, but are not limited to: 

    Genome and sequence data visualization, including genomic variation data, 3D and 4D genome visualization, and chromosome interaction maps
    Multivariate omics data visualization (transcriptomics, proteomics, metabolomics, etc.)
    Phylogenetic data visualization, as well as biological networks and pathways
    Neurobiology and developmental biology visualization, biological atlases and metadata 
    Macromolecular structures (e.g., protein or RNA structures) visualization
    Biological image data, such as microscopy data visualization 
    Visualization for the modeling and simulation of biological systems 
    Biovis systems and software frameworks, and integrating visualization and machine learning for biological analysis 
    Biological workflows or collaborative processes, processes for interdisciplinary collaboration between biology and visualization, and usability of visualization by biologists, including communicating uncertainty 
    New challenges, breakthroughs, and opportunities in biological data visualization

Special Issue on Human-AI Interaction for Graphics and Visualization
Submission Date: 2025-04-24

Artificial intelligence (AI) has made significant strides across various fields. However, its end-to-end automation often overlooks the nuances of human needs and expectations, particularly in creative domains like graphics and visualization design. These fields demand human expertise, creativity, and iterative development  – qualities that AI alone cannot replicate. 

To bridge this gap, human-AI interaction (HAI) emerges as a promising paradigm. HAI explores how humans and AI systems communicate and collaborate, leveraging the unique strengths of both to achieve more innovative and impactful outcomes. By combining human ingenuity with AI’s computational power, HAI introduces workflows that enable new possibilities for creative designs.

This special issue explores the transformative potential of collaborative HAI in graphics and visualization.  Submissions are encouraged that deepen our understanding of human-AI collaboration and its application in these fields, whether through theoretical frameworks, empirical research, or the development of innovative systems and tools that push the boundaries of HAI.

Topics of interest include, but are not limited to:

    Frameworks for HAI in Graphics and Visualization
    Human-Centric AI Tools for Graphics and Visualization
    Design and Evaluation of HAI in Visual Media
    Data-Driven Dynamic Design Approaches for Visual Media
    Graphical Interfaces and Visualizations for Explainable and Interpretable HAI
    Empirical Studies on HAI in Graphics and Visualization
    Ethical Issues in Collaborative HAI Design for Graphics 
    Integrating AI in Tools for Creative Design and Visualization
    HAI Framework, System, and Tool for VR/AR/XR
    Adaptive AI Techniques for Personalized Graphics and Visualizations
    Modeling User Interaction Behavior in HAI Systems
    Designing HAI Systems for Graphics and Visualization Based on User Behavior Models
    Applications of HAI in Design, Communication, Storytelling, 3D Modeling, Visual Media, Animation, and more