Human cyber-physical systems where humans and computing are tightly integrated into a physical environment. Software-integrated systems often interact with humans, frequently forming a symbiotic relationship, where the result is more than the sum of its parts. Our projects research the science and engineering of such systems, where humans are assisted by computational systems.
The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by the National Science Foundation. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim.
Makerspaces are very popular because they provide a hands-on experience for young learners to experiment with technology. One drawback is that the focus of educational experiences in makerspaces are necessarily on the hardware. Computing aspects, especially more advanced concepts such as cybersecurity, take a back seat. We will team up with Martin Luther King Jr.
Building on the foundations set by the AP Computer Science (CS) Principles course, this project seeks to dramatically expand access, especially for high school girls, to the most exciting and emerging frontiers of computing, such as distributed computation, the internet of things (IoT), cybersecurity, and machine learning, as well as other 21st century skills required to productively leverage computational methods and tools in virtually every profession.
Computational Modeling for Integrating Science and Engineering Design (CMISE) will conduct a series of experiments to systematically compare different computational modeling activities on 5th and 6th grade students’ engineering design processes, their understanding of engineering, science and computational thinking concepts, as well as science teachers’ confidence and ability to implement integrated STEM and computing curricula.
With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by improving undergraduate understanding of data science. It will accomplish this goal by incorporating data science concepts and skill development in undergraduate courses in biology, computer science, engineering, and environmental science.
Automated design processes, especially using Machine Learning/AI techniques, require proposed systems to be evaluated across all relevant attributes, requirements, and concerns. Traditionally, teams create models in a set of engineering tools for design evaluation data.