Minds, Optimization, Machines, and Orchestration (MOMO)

Advancing explainable AI and human–machine collaboration. The MOMO Lab explores how human intelligence, mathematical methods, and artificial intelligence can work together to solve complex problems and support better decision-making. Our research spans machine learning, optimization, explainable and interpretable AI, large language models, and intelligent and agentic systems, with particular emphasis on understanding how these technologies can be effectively integrated with human expertise.

The lab brings together four complementary perspectives: Minds, representing human knowledge, reasoning, and decision-making; Optimization, providing mathematical and computational methods for finding effective solutions; Machines, encompassing machine learning, AI, and data-driven models; and Orchestration, addressing how people, models, AI agents, and computational tools can be coordinated within larger systems and workflows.

Led by Dr. Amaury Lendasse and Dr. Peggy Lindner, the MOMO Lab develops methods and applications that make intelligent systems more transparent, trustworthy, and useful. Our work emphasizes interdisciplinary research and practical applications of AI and computational methods to engineering, science, organizations, and complex socio-technical systems.

Smart Engineering Systems Lab (SESL)

The Department established the Smart Engineering Systems Lab (SESL) to develop approaches in building complex systems that can adapt in the environments in which they operate. The term "smart" in the context indicates physical systems that can interact with their environment and adapt to changes both in space and time by their ability to manipulate the environment through self-awareness and perceived models of the world based on both quantitative and qualitative information. The emerging fields of artificial neural networks, fuzzy logic, evolutionary programming, chaos, wavelets, fractals, complex systems, and virtual reality provide essential tools for designing such systems.

The focus of the SESL is on developing smart engineering architectures that integrate and/or enhance the current and future technologies necessary for developing smart engineering systems while illustrating the real-life applications of these architectures. The smart engineering systems design and operations cut across a diversity of disciplines, namely, manufacturing, electrical, computer, and mechanical, biomedical, civil and other related fields such as applied mathematics, cognitive sciences, biology and medicine. Current research topics include data mining, artificial life, evolutionary robotics, internet-based pattern recognition, and systems architecture based on DoDAF framework. Capabilities of the developed computational intelligence models are demonstrated physically in the lab through mini autonomous research robots.

The Virtual and Augmented Reality Systems Engineering Lab (VASEL)

The Virtual and Augmented Reality Systems Engineering Lab (VASEL) provides advanced visualization and computational intelligence for decision making support to complement ongoing and future research work within the department, the S&T campus and across the UM system. The research conducted in this lab will address current and future challenges faced at the boundaries and interfaces of science, technology and engineering research that are essential for the next level of scientific advances to address societal needs. These challenges are found at the nexus of various domains and require experts from all backgrounds of science and engineering to facilitate research leading to the emergence of new disciplines and the generation of knowledge, particularly in the areas of complex systems design and development.

The focus of the VASEL is the research and development of techniques and platforms that are essential to understanding the complementary and competitive teaming of humans with natural and engineered systems. This includes design and evaluation of human response to extreme events such as earthquakes and floods which informs our understanding of developing protocols to address these natural events. Research involving human response to manufactured events such as fires, shootings and even cyber-attacks similarly will lead to engineered strategies facilitated by the virtual environments used as experimental platforms.

VASEL also leverages the massive compute power of modern graphics cards to enable cutting edge artificial intelligence techniques, supporting both the visualization mission of the lab as well as independent research.  Research in this area includes deep learning for disaster planning, resource allocation, and the creation of computer agents.