Christin Salley

Schmidt AI in Science Fellow

Michigan Institute for Data Science

Dr. Christin Salley’s dissertation revolved around mitigating natural hazards through crisis detection and communications, enhancing accessibility to emergency management response systems. Her research aimed to ultimately assess social systems related to disasters and develop proactive measures to enhance community resilience. She earned her PhD in Civil Engineering (with a concentration in Construction and Infrastructure Systems) from the Georgia Institute of Technology, her MSE in Civil Engineering from the Johns Hopkins University, and her BS in Fire Protection Engineering from the University of Maryland.

She is also personally passionate about pathways of engineering (investigating pursuits of engineering at different educational levels) and desires to train, mentor, and teach the next generation of engineers while conducting research that benefits various communities. In her free time, she enjoys spending time with family and friends, traveling, and trying new restaurants.

During the Schmidt AI in Science Postdoctoral Fellowship, she will focus on developing equitable infrastructure systems and services within urban environments to continue studying enhancing community resilience. Specifically, her work will center on understanding societal systems and addressing ethical considerations, particularly concerning vulnerable populations, through investigations on disaster and crisis management using AI. Employing a transdisciplinary and sociotechnical approach, she will integrate data science methods for information processing and associated analyses. Her overarching goal is to make a positive impact on society through her research, fostering innovation and advancing responsible research practices. She will be working under the mentorship of Dr. Sabine Loos (Science Mentor) and Dr. Lu Wang (AI Mentor).

  • AI Mentor: Lu Wang, Computer Science and Engineering, College of Engineering
  • Science Mentor: Sabine Loos, Civil and Environmental Engineering, College of Engineering
  • Research Theme: Analysis of equitable social and infrastructure systems and services with AI applications