BASE: Bridging AI, Systems, and Environment
Advancing AI frontiers through innovative research in agriculture and beyond
We're Hiring
Graduate Research Assistant (50% FTE)
AI, Machine Learning, Deep Learning, and Computer Vision. Immediate joining for Spring 2027.
BASE Lab Featured on WSIL Heartland News
Our team members Taminul Islam and Toqi Tahamid Sarker were featured on WSIL 3 Heartland News for their AI research supporting the SIU and Illinois Department of Natural Resources deer density study, which could help improve deer management in 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
Auditing Weapon Segmentation and Prompted Detection on Real CCTV at a Stated Alarm Rate: A Deployment-Oriented Evaluation
Real-World Surveillance (RWS) Workshop at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2027
Khaled R. Ahmed, Taminul Islam, Abdellah Lakhssassi, Toqi Tahamid Sarker
EfficientMTNet: An Ultra-Lightweight Multi-Task Network for Joint Brain Tumor Classification and Segmentation
CVPath-Vision4Neuro Workshop at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2027
Taminul Islam, Prapti Roy, Joseph Kalinzi, Khaled R. Ahmed
Stable Scores, Unstable Decisions: Object-Level Predictive Multiplicity in Clinical Microscopy and Computational Pathology
CVPath-Vision4Neuro Workshop at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2027
Malek Rababa, Nisrein Rababa, Khaled R. Ahmed
Latest News
Three Papers Accepted at WACV 2027 Workshops
November 2026
Three of our papers have been accepted at WACV 2027 workshops: 'Auditing Weapon Segmentation and Prompted Detection on Real CCTV' (oral, RWS workshop), 'EfficientMTNet' and 'Stable Scores, Unstable Decisions' (CVPath-Vision4Neuro workshop).
Review Paper Published in Journal of Imaging
November 2026
Our review paper 'Binding Text to Pixels: A Narrative Review of Supervision Granularity in Language-Guided Chest Radiograph Segmentation and Grounding' by Joseph Kalinzi, Taminul Islam, and Khaled R. Ahmed has been published in the Journal of Imaging (MDPI). Read the paper
KFVS12 Features BASE Lab's AI Deer-Counting Work
October 2026
KFVS12 covered SIU's effort to find better ways to track Illinois deer populations, comparing trail cameras, thermal-imaging vehicle surveys, and drones. BASE Lab PhD candidate Taminul Islam is developing AI software that detects and counts deer in thermal footage while avoiding double counts. Read the KFVS12 story
SIU News: Zoology and Computer Science Team Up for IDNR Deer Density Study
October 2026
SIU News highlighted a collaboration between the Center for Wildlife Sustainability Research and BASE Lab to help the Illinois Department of Natural Resources compare deer-density estimation methods. BASE Lab PhD students Toqi Tahamid Sarker and Taminul Islam built AI models for estimating deer distance in trail-camera images and for detecting and counting deer in thermal imagery, work accepted to an ECCV 2026 workshop. Read the SIU News story
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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