About the Lab
At Dig Connectivity Research Laboratory (DCRLab), we strive to engage in cutting-edge research to design and develop secure, reliable, and sustainable end-to-end solutions and systems. We are pioneering a data-driven future through research and solutions developed with trending technologies to solve and address real-world problems using deep learning techniques. You should be very motivated to catch up on the latest Tech advances in those areas. Students from all STEM disciplines (CS, ME, ECE, etc.) are welcome. You are supposed to be a proactive, creative, and self-motivated character in the workplace. Strong background in mathematics, computer science, deep learning techniques, and technical trends. Background knowledge in Networking, Security, Optimization, Artificial Intelligence, Cyber-physical system modelling, and Computer Vision. Strong programming experience with at least one tool (of your choice) in Matlab, Python, R, or Java. Background in logic, detection, and estimation theory would be a plus. For details, consider checking this Link.
Area of Concentration
The main focus of our group is threefold:
Food Security Monitoring (we use satellite data and develop artificial intelligence models to provide real-time crop monitoring and yield predictions for improved food security early warning systems),
Disaster Early Warning (we develop early warning systems for droughts, floods, and other climate-related disasters to help communities prepare and respond effectively),
Artificial Intelligence for Sustainable Computing (we create AI solutions that work in Africa's diverse agricultural contexts, plant stress detection, identification, and classififocusing on practical applications for smallholder farmers).
Our approaches range from several domains, multimodal learning, network analysis, and model mining, to Bayesian modeling, deep learning, representation learning, explainable AI, security, and privacy through human-computer interaction, targeting top venues of research publication. Join us! We are looking for talented and self-motivated research assistants to work on groundbreaking, real-world problems in the context of high-impact applications like agriculture, healthcare, and environmental change.