Visual AI Hackathon at ASU

Event sponsored by Voxel51.

Participants will have the opportunity to earn ASU micro-credentials in AI Model Development in three categories: Beginner, Intermediate and Expert!!! 

Description:
Dive into the world of machine learning at the School of Arts, Media and Engineering’s upcoming hackathon! This one-day event invites students, researchers, and ML enthusiasts to collaborate on solving real-world challenges using cutting-edge techniques in Computer Vision and AI.

With tracks designed for all skill levels, from beginners to experts, there’s something for everyone:

• Level 0 – Beginner: New to machine learning? Start your journey here!
• Level 1 – Intermediate: Build on your existing knowledge and tackle practical challenges.
• Level 2 – Expert: Push boundaries and make an impact with advanced solutions.

What to Expect:

• 🚀 Tech Talks: Explore deep-dive discussions on Computer Vision and Data-Centric AI.
• 🔧 Hands-on Workshops: Learn to build AI applications through real-world coding exercises.
• 🏅 Engaging Challenges: Solve real-world problems and compete for exciting prizes.
• 🤝 Networking Opportunities: Connect with peers, faculty, and industry professionals.
• 🎁 Swag & Prizes: Win cash prizes and take home exclusive event merchandise.

Workshops and Judging:
Throughout the day, attend workshops on best practices in Computer Vision and ML, and showcase your skills during the judging sessions led by industry experts. Prizes will be awarded for the most innovative solutions across skill levels.

What to Bring:
Your laptop and enthusiasm! Snacks and refreshments will be provided to keep you fueled.

Daniel Gural is a seasoned Machine Learning Evangelist with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data. Currently serving as a valuable member of Voxel51, he takes a leading role in efforts to bridge the gap between practitioners and the necessary tools, enabling them to achieve exceptional outcomes. Daniel’s extensive experience in teaching and developing within the ML field has fueled his commitment to democratizing high-quality AI workflows for a wider audience.

Pavan Turaga is director of the School of Arts, Media and Engineering, and a professor with a joint appointment in Electrical Engineering (ECEE) at Arizona State University.

Turaga's research is housed at the Geometric Media Lab (GML) at ASU, where they host many students from computer science, media arts, electrical engineering and more. The work at GML is interdisciplinary, with motivating applications in autonomous systems, health systems, and scientific applications, with theoretical roots in machine learning, geometry, and topology. Data representing 3D spatial, 2D imaging, 1D time-series are all of interest to them.

Don’t miss this chance to collaborate, learn and contribute to ASU’s vibrant AI and ML community, powered by the School of Arts, Media and Engineering!

Register now to secure your spot and join us in shaping the future of machine learning!