BASE: Bridging AI, Systems, and Environment
Advancing AI frontiers through innovative research in agriculture and beyond
Awarded at Illinois Young Innovator of the Year
PhD Student Taminul Islam has been awarded 3rd place in the 2025 Illinois Young Innovator of the Year, among 16 selective talks by Falling Walls Lab Illinois.
Research Focus
Computer Vision
Developing advanced techniques for visual data interpretation, including object detection, recognition, and image processing, to enhance automated visual understanding in diverse applications.
Deep Learning
Designing and optimizing state-of-the-art neural network architectures and algorithms to address complex problems across various domains, with a focus on improving performance and scalability.
AI for Agriculture
Applying artificial intelligence to agricultural challenges such as precision livestock management, crop health monitoring, and yield prediction, aiming to improve efficiency and sustainability in agriculture.
Federated Learning
Creating robust federated learning frameworks to handle non-iid data and resource constraints, ensuring effective and secure distributed learning across heterogeneous environments.
Recent Publications
Quantum Parallel Processing Framework for Image Processing Applications
IEEE 16th International Symposium on Autonomous Decentralized Systems (ISADS), 2025
Juan Carlos Salcedo, Khaled R. Ahmed
WeedSense: Multi-Task Learning for Weed Segmentation, Height Estimation, and Growth Stage Classification
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2025
Toqi Tahamid Sarker, Khaled R. Ahmed, Taminul Islam, Cristiana Bernardi Rankrape, Karla Gage
GasTwinFormer: A Hybrid Vision Transformer for Livestock Methane Emission Segmentation and Dietary Classification in Optical Gas Imaging
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2025
Toqi Tahamid Sarker, Mohamed Embaby, Taminul Islam, Amer AbuGhazaleh, Khaled R. Ahmed
Latest News
Awarded at Illinois Young Innovator of the Year
September 2025
PhD Student Taminul Islam has been awarded 3rd place in the 2025 Illinois Young Innovator of the Year, among 16 selective talks by Falling Walls Lab Illinois.
Two Papers Accepted at ICCV 2025
September 2025
Two papers have been accepted at ICCV 2025. WeedSense, a multi-task architecture that simultaneously performs weed segmentation, height estimation, and growth stage classification, was accepted at the 10th Computer Vision in Plant Phenotyping and Agriculture workshop. The second paper, GasTwinFormer, introduces a hybrid vision transformer for real-time livestock methane monitoring and has been selected for oral presentation and as a best paper nominee at the SEA: Sustainability with Earth Observation & AI workshop.
Doctoral Research Fellowship awarded
August 2025
PhD student Toqi Tahamid Sarker has been awarded the Doctoral Research Fellowship.
Journal Article Published: WeedSwin
July 2025
We are thrilled to announce that our journal article, 'WeedSwin Hierarchical Vision Transformer with SAM-2 for Multi-Stage Weed Detection and Classification' has been published in Scientific Reports (Nature). This comprehensive research introduces extensive datasets documenting prevalent weed species across multiple growth stages, and proposes a novel WeedSwin Transformer architecture that demonstrates exceptional performance in weed detection and classification for precision agriculture. Congratulations to the team!
Join Our Lab
Interested in pushing the boundaries of AI? We are always looking for talented individuals to join our team.
PhD Students
Conduct cutting-edge research in AI and Computer Vision.
Masters Students
Gain hands-on experience in advanced AI projects.
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