Web3D / Metaverse Tools Competition – Web3D 2026

Win cash prizes up to $1,000

Create, Innovate, Dominate – The 3D Challenge Awaits!

This competition aims to encourage the development of Web3D tools within the framework of X3D standards.

Facilitate seamless integration and interaction of X3D among different 3D tools & applications,
Broaden X3D adoption, and elevate the use of X3D within the 3D ecosystem.
Create opportunities for collaboration among developers, industry experts, and educators to share knowledge and resources.
Gain recognition, and visibility within the 3D industry.

Submission Deadline: August 30, 2026 – Submit here

Eligibility Criteria:

Prizes: Two categories:

1. Web3D/Metaverse Tool of the Year

2. Web3D/Metaverse Tool/Pipeline Innovation of the Year

Judging Criteria:

3-Person Judges Panel
Originality, Technical execution, Ease of use, Configurability, Performance and Extensibility.

Web3D/Metaverse tool will be judged by some or all of the following functionalities:

Submission Instructions:

Name of the X3D tool: (New or Improved existing tool)
Type of Tool: Imported, Exporter, Convertor, Editor, Viewer….
Domain Categories: Educational tools, gaming applications, simulations…
1-2 page Abstract/Summary
What problem does this tool solve?
Is it open-source?
Must submit a link to a video (max 5 minutes) in which an explanation is given as to why their entry should be considered for “Tool of the Year” or “Tool/Pipeline Innovation of the Year”.
If need be a virtual meeting/demo may be requested
You don’t have to be present in-person at the conference to enter the competition.
The winners will be announced on September 10, 2025

Submission Deadline: August 30th, 2026 Submit here

Questions about the competition should be emailed to: competition@web3d.org

To submit, please go to the submission page.

Laboratory Manager, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar

Holds a PhD in Computer Science and Engineering (HBKU, 2024), an MSc in Data Analytics (HBKU, 2021), a BS in Computer Science (AUCE, 2018), and a BS in Mathematics (LIU, 2020).
Research focuses on human–computer interaction, AI and machine learning, and computer vision for autism, including eye-tracking, pose estimation, and object detection in play-based and learning contexts.
Leads and contributes to projects on joint engagement, preference assessment, and inclusive assessment for autistic learners, often combining sensing technologies, VR, and learning analytics.
Has published in venues such as CoDesign, Frontiers in Education, International Journal of Human–Computer Interaction, JMIR, BCS HCI, and LNCS (HCII/INTERACT).
Recipient of the Mada Innovation Award (2022) for the MAAN accessibility-focused application.
Experienced educator and tutor in mathematics and computer science, and teaching assistant for courses on ICT accessibility and statistics for science and engineering.
Actively serves as a reviewer and collaborator on interdisciplinary projects spanning autism, inclusive technology, AI, and education.