Shah Saki

Ph.D. Student

Civil & Environmental Engineering


Shah Saki is a 4th year Ph.D. student in the Department of Civil & Environmental Engineering at the University of Connecticut (UConn). With a strong focus on statistical approaches, machine learning, and geospatial analysis, his research aims to unravel the complexities of extreme events and their profound impacts on grid resilience and vulnerability.

Shah joined the Hydrometeorology and Hydrologic Remote Sensing Group and the Outage Prediction Modeling (OPM) Group in Fall 2021. His academic journey began with a bachelor’s degree in Civil Engineering from Bangladesh University of Engineering and Technology (BUET) in 2016, followed by a master’s degree in Environmental Engineering from the University of California, Los Angeles (UCLA) in 2018. Before joining UConn, he served as a lecturer in Bangladesh from 2017 to 2020, further solidifying his commitment to education and research.

Shah’s technical expertise spans hydrodynamic modeling (e.g., HEC-RAS), big data analytics (e.g., Python, RStudio), machine learning, and geospatial data analysis (e.g., ArcMap, QGIS). He gained extensive training on the impact of climate change on the power outage sector during his internship at the Electric Power Research Institute (EPRI). His skills have been instrumental in collaborative projects with utilities such as Eversource Energy, Dominion Energy, Exelon Energy, and Avangrid, Inc. His dedication to advancing the field was recognized through his participation as a summer institute fellow at the National Water Center, sponsored by NOAA and NSF.

In addition to his research, Shah is actively involved in various student organizations. He is a member of the Student Association of Graduate Engineers (SAGE), a senator at the Graduate Students Senate, and currently serves as the vice president of the John Lof Leadership Academy (JLLA) at UConn. His involvement in JLLA has provided a platform to develop his leadership skills and contribute to the community.

Shah envisions a world where sustainable practices are the norm, and his work is a testament to this vision. Through his research and active participation in the academic community, he aims to make a lasting impact, bridging the gap between climate science and practical solutions for the power sector.

Contact Information
Emailshah.saki@uconn.edu
CV_Shah_Saki CV_Shah_Saki_2024
Mailing AddressEversource Energy Center | Innovation Partnership Building: 159 Discovery Dr, Storrs, CT 06269, United States
Office LocationInnovation Partnership Building (IPB), 212
CampusStorrs
Linkhttps://www.linkedin.com/in/shahsaki
Research Interests
  • Predictive Analytics in Extreme Weather
  • Extreme Event Impact Modeling
  • Geospatial Big Data Analytics
  • Artificial Intelligence