Tutorial Presenters
Meet the presenters who will guide you through neural network reprogrammability
Expertise
This tutorial brings together complementary expertise spanning theoretical foundations, practical implementation, and trustworthy AI considerations.
🎯 Theory
Mathematical foundations and formal framework development
⚙️ Practice
Implementation techniques and practical applications
🛡️ Trust
Security, robustness, and ethical considerations
Research Impact
Our speakers have collectively contributed to:
- Foundational survey papers on neural network reprogrammability
- New model reprogramming and prompt tuning techniques
- Adversarial robustness and trustworthy AI frameworks
- Cross-domain applications in vision, NLP, and multimodal learning
- Open-source implementations and educational resources
Tutorial Philosophy
This tutorial emphasizes:
- Unified Framework: Connecting disparate techniques under one methodology umbrella
- Practical Focus: Hands-on implementation with real code examples
- Broader Impact: Considering societal implications and responsible AI
- Interactive Learning: Encouraging questions and collaborative exploration
- Resource Sharing: Providing comprehensive materials for continued learning
Questions and Collaboration
Interested in learning more or exploring potential collaborations? We welcome questions before, during, and after the tutorial.