The Dig Connectivity Research Laboratory (DCRLab) is an independent, dynamic, and quickly growing expert systems research striving to engage in cutting-edge research to design and develop end-to-end secure and reliable sustainable solutions and systems. We aim to impact high-stake, real-world problem settings at the intersection of healthcare, ecological change, and human-computer behavior and sustainability through artificial intelligence and machine learning. For this, we focus on developing novel approaches and methodologies in close collaboration with practitioners and domain experts that enable unprecedented insights into complex systems. This allows us to directly impact real-world scenarios like local patient populations or ecosystems, maximizing the translational and synergetic effects of our work. In this context, the main focus of our group is threefold: (1) Understanding complex systems by extracting novel insights into their underlying processes, (2) Lightweight modeling of complex systems by integrating existing domain knowledge into machine learning methods, and (3) Developing methods for knowledge management, representation, and interaction.
Our approaches range from multimodal learning, network analysis, and exceptional model mining to Bayesian modeling, deep learning, representation learning, explainable AI, and human-computer interaction. With a vision to support sustainable livelihoods, and appreciate technological application in marginal environments and mission to advance sustainable solutions by integrating digital technology and circular economy principles
Strategic objectives
(1) Advance Digital Innovation for Sustainability
(2) Promote Sustainable Resource Management
(3) Foster Resilient Healthcare and Urban Systems
(4) Support Cross-Sector Collaboration and Knowledge Sharing