Base Lab
Advancing cutting-edge research in Distributed Computing, Deep Learning, and Computer Vision at Southern Illinois University Carbondale.
Research Focus
Our lab specializes in cutting-edge research across these interconnected domains
Distributed Computing
- Autonomous decentralized systems
- Service-oriented architecture
- Scalable communication technologies
- Trust frameworks for volunteer computing
Deep Learning
- Advanced CNN architectures
- Dilated convolution techniques
- Parallel computing for neural networks
- Real-time system optimization
Computer Vision
- Material defect detection
- Pothole detection systems
- Real-time visual sensing
- Medical image analysis
Our Journey
2002-2004
Pioneered research in autonomous decentralized community systems and service-oriented communication technologies.
2011-2012
Published influential work on GPS-based safety systems and intelligent computing approaches.
2020-2021
Published groundbreaking research on Smart Pothole Detection using Deep Learning, receiving over 120 citations.
2022-2023
Developed DSTEELNet, a real-time parallel system for detecting and classifying defects in steel surfaces.
Lab Director
Dr. Khaled R. Ahmed
Associate Professor of Computer Science at Southern Illinois University with expertise in Distributed Computing, Big Data, and Deep Learning.
Featured Publications
Breakthrough research that has advanced the field and made real-world impact
Smart Pothole Detection Using Deep Learning Based on Dilated Convolution
A groundbreaking approach to road condition monitoring using advanced computer vision techniques.
DSTEELNet: A Real-time Parallel Dilated CNN with Atrous Spatial Pyramid Pooling
Novel system for detecting and classifying defects in surface steel strips with high accuracy.
ProTrust: A Probabilistic Trust Framework for Volunteer Cloud Computing
Innovative framework addressing trust issues in volunteer computing environments.
Autonomous Decentralized Community Communication for Information Dissemination
Foundational work on decentralized community systems and communication technologies.
Our Core Values
Collaboration
We foster interdisciplinary teamwork across universities and industry partners to solve complex research challenges.
Innovation
We develop novel algorithms and systems that push boundaries in AI, distributed computing, and real-world applications.
Impact
We focus on research with practical applications that address significant technological and societal challenges.
Join Our Team
We're looking for talented researchers, graduate students, and collaborators interested in distributed computing, deep learning, and computer vision.
View Open Positions