Xiwei
Xuan
Associate Instructor & Graduate Student Researcher at University of California, Davis
"Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact"
"Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact"
Wed May 21 - 6:00 PM EDT/New York (See in local time)
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05/21/2025 6:00 PM
05/21/2025 06:10 PM
America/New_York
#WTGC2025
"Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact"
#WTGC2025
"Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact"
https://www.womentech.net/ringcentral
https://www.womentech.net/ringcentral
"Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact"
"Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact"
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Session: Empowering AI with Human Insight: Advancing Data-Centric and Responsible AI for Real-World Impact
In the rapidly evolving AI landscape, ensuring that models are not only accurate but also aligned with human perception is essential for building trustworthy AI systems. This talk explores how data-centric approaches and human-in-the-loop strategies can enhance the reliability, responsibility, and efficiency of AI models, particularly in safety-critical applications such as autonomous driving and surveillance. Drawing from my research in open-vocabulary segmentation and foundation model optimization, I will demonstrate how refining data quality, improving model interpretability, and incorporating human feedback can mitigate biases and improve generalization. The session will highlight actionable insights for researchers and practitioners aiming to develop robust AI solutions that balance automation with human oversight.Key Takeaways
- Building Responsible AI for Safety-Critical Applications – Explore techniques to align machine intelligence with human perception in high-stakes scenarios such as autonomous driving and surveillance.
- Data-Centric Approaches for Robust AI – Learn how improving data quality through refinement and diversity can significantly enhance model performance and generalization.
- Empowering Women to Shape the Future of AI – Discover how women in tech can contribute to designing AI systems that are ethically grounded, interpretable, and capable of serving diverse communities.
Bio
Xiwei Xuan is a PhD candidate conducting research in AI, advised by Distinguished Professor Dr. Kwan-Liu Ma. Her research lies at the intersection of computer vision, machine learning, and visual analytics, with a primary goal of improving the reliability, responsibility, and efficiency of AI systems. In particular, she is interested in data-centric and human-involved strategies, seeking to foster the alignment of machine intelligence with human perception. The resulting methods contribute to the development of robust, trustworthy AI systems that can reason, interact, and generalize effectively in complex real-world scenarios.