Trustworthy AI & Sensing Informatics (TASI) Lab

Principal Investigator: Dr. Sambandh Dhal
Assistant Professor, Data Science in Agricultural & Ecosystem Sustainability
Department of Bioproducts and Biosystems Engineering
University of Minnesota Twin Cities

The Trustworthy AI & Sensing Informatics (TASI) Lab develops reliable, data-driven methods that connect sensing → artificial intelligence → real-world decision making.

Our research integrates machine learning, spectroscopy, hyperspectral imaging, computer vision, IoT sensing, and uncertainty quantification to address challenges in:

• Precision and digital agriculture
• Food quality, food safety, and processing
• Spectroscopy and hyperspectral imaging
• Biomass and bioenergy systems
• Agricultural and environmental sensing
• Circular bioeconomy and waste-stream informatics
• Automated material identification and sorting
• Materials informatics
• Multimodal sensor fusion
• Trustworthy and uncertainty-aware AI
• Data-driven process monitoring and optimization

A central goal of the lab is to develop AI systems that remain useful when real-world data are small, noisy, incomplete, heterogeneous, or high-dimensional and to translate those models into practical sensing and decision-support tools.