Projects

Smartphone-Based Chlorophyll Monitoring System Using AI Models for Precision Stress Management in Soybeans

Award: Soybean Center, Southern Illinois University Carbondale, $15,000

Smartphone-based AI for precision stress management in soybean fields

Developing a smartphone-based chlorophyll monitoring system powered by AI models to detect early nutrient and stress indicators in soybean fields, enabling low-cost, in-field precision stress management.

AI-Driven Discovery of Sustainable Ionic Liquids: A Multimodal Deep Learning Approach for Enhanced Lignin and Plastic Deconstruction

Award: IIN Sustaining Illinois

Multimodal deep learning for accelerated discovery of sustainable solvent systems for biopolymer and plastic valorization

Vision-centric deep learning frameworks that fuse 3D imaging cues with cross-modal signals to forecast solvent–substrate interactions, enabling faster screening of sustainable solvent candidates.

Detecting Subacute Ruminal Acidosis Using Real-Time Deep Learning

Award: USDA-NIFA 2023-70001-40997

Non-invasive detection of subacute ruminal acidosis via optical gas and thermal imaging

A multi-paper effort segmenting CO₂, methane, and multi-gas plumes from optical gas imaging — combining lightweight ViT backbones, attention-based fusion, and thermal recognition for non-invasive livestock health monitoring.

Computer Vision for Wildlife Monitoring

Automated wildlife census and habitat analysis across camera-trap, thermal, and aerial imagery

Perception pipelines spanning ground-level RGB, thermal infrared, and drone-based orthoimagery to support large-scale ecological surveys and wildlife population studies.