Soroush Mahjoubi
Soroush Mahjoubi, PhD
Postdoctoral Associate
Olivetti Group & Concrete Sustainability Hub (CSHub)
Massachusetts Institute of Technology
ABOUT
Soroush is currently a Postdoctoral Associate at MIT's Olivetti Group and Concrete Sustainability Hub (CSHub). His research aims to reduce emissions from cement-based materials through data analysis, machine learning, optimization strategies, and hands-on experiments. He's worked on creating new binders for concrete, designing complex concrete mixes, and conducting detailed performance tests.
Before his postdoc at MIT, Soroush taught a course on Advanced Mechanics of Materials (CE518) as an adjunct professor at Stevens Institute of Technology. As a PhD student at Stevens' Smart Infrastructure Lab, supervised by Dr. Yi Bao, he did research on AI-guided structural health monitoring systems using fiber optic sensors and predicting and characterizing material properties using advanced AI methods, including deep learning and NLP. His research contributions also include developing AI-driven designs for sustainable, high-performance concrete.
RESEARCH THRUSTS
Leveraging AI for Revolutionary Materials and Structures, Infrastructure Health Assessment, and Beyond
ADVANCED MATERIALS
My research focuses on leveraging the power of AI to advance the understanding of engineering materials and development of materials with desirable properties. Through the application of machine learning, natural language processing, and optimization I have developed methods for predicting material properties, discovering new chemical reactions, and automating the development of various cementitious composites, including ordinary concrete, ultra-high-performance concrete, and strain-hardening cementitious composites. I have also developed a method based on computer vision and image processing to characterize and classify 2D nano graphene flakes, enabling automated development of 2D materials.
ADVANCED STRUCTURES
My research centers around two areas: optimization design of high-strength yet lightweight concrete composite modules, with a particular focus on robotic integration and accelerated construction methodologies. Concurrently, I employ and develop a blend of optimization algorithms that are inspired by natural phenomena and game theory to design resilient structures. These algorithms are aimed at significantly enhancing computational efficiency, especially vital in the optimization of complex structural designs.
STRUCTURAL HEALTH MONITORING
My research revolves around two core aspects: optimal sensor deployment and sensor data analysis. I strategically position sensors using optimization techniques to collect valuable data throughout structures, ensuring effective monitoring of structures. By analyzing data collected from distributed fiber optic sensors, I extract crucial parameters to detect potential damage and excessive loads, thus enhancing our understanding of structural health. These advancements contribute to improved maintenance strategies and the creation of safer structures.
CONTACT
Address 77 Massachusetts Ave, Cambridge, MA 0213
Email mahjoubi [at] mit.edu