Surya S.C. Congress

Biography

Dr. Surya S. C. Congress is an Assistant Professor in the Department of Civil and Environmental Engineering at the Michigan State University. He is also an FAA Certified Drone Pilot and has flown many uncrewed aerial vehicles (UAV) missions to collect infrastructure condition data. His areas of research interest include sustainable and resilient infrastructure design, ground improvement techniques, ... and smart city concepts using innovative sensors and smart monitoring technologies. He worked on Federal and State-funded research projects on designing and monitoring various infrastructure assets. As part of these projects, he focused on monitoring and evaluating the civil infrastructure health conditions by inspecting pavements, railways, airports, bridges, embankments, slopes, towers, and dam assets using unmanned aerial vehicles coupled with close-range photogrammetry techniques.

Dr. Congress uses image processing techniques to build the digital models of various infrastructure assets and leverages Artificial Intelligence and Machine Learning (AI/ML) Techniques to automate the infrastructure condition assessments. He is also a member of two national academy’s Transportation Research Board committees and also serves as TRB Committee Communications Coordinator (CCC) for one of those committees. He is part of the ASCE Committee on Innovative Technologies and Tools in Geotechnical Engineering (INNC) task force. He published his research in many peer-reviewed journals and conference publications. He delivered several invited lectures on national and international platforms including Transportation Research Board, UAV Commercial Expo, DJI Airworks, and the International Society for Soil Mechanics and Geotechnical Engineering’s (ISSMGE’s) Bright Spark Keynote Lecture at Cairo, Egypt. He likes to play outdoor sports and enjoys glacier hiking.

Research Interests:

• Stabilization of Problematic Soils

• Resilient and Sustainable Designs for Transportation Geotechnical Assets

• Climate change effects on Civil Infrastructure and Communities

• Structural Health Monitoring of Infrastructure Assets using Digital Twins

• Applications of Uncrewed Aerial Vehicles (UAVs) for Infrastructure Asset Management

• Machine Learning and Neural Network Models for Feature Extraction

• Computer Vision Applications for Solving Real-World Problems



Courses Taught:

• CE 312: Soil Mechanics (Fall 2023)