
Angkur J. D. Shaikeea
استادیار · Solid Mechanics
California Institute of Technology (Caltech)معرفی
Angkur J. D. Shaikeea is an Assistant Professor of Aerospace at the California Institute of Technology and a Bren Scholar, starting in 2025. He holds a B.Tech from the National Institute of Technology Calicut (2015) and a Ph.D. from the University of Cambridge (2022). His research lies at the intersection of solid mechanics, materials science, and advanced experimental techniques.
His research focuses on developing cutting-edge experimental tools using X-rays to study material behavior in three dimensions. He aims to integrate techniques such as tomography, ptychography, EDXRD, and 3DXRD for in-situ mechanical testing across diverse materials including metals and biological samples. By extracting detailed 3D stress and strain data, his group is building a large-scale database for data-driven mechanics, enabling machine learning and AI-based analysis in solid mechanics. He emphasizes interdisciplinary collaboration among designers, material scientists, and mechanicians to innovate in material design and promote sustainability.
The publications listed represent emerging work in advanced materials characterization and mechanics, with a strong emphasis on in-situ imaging, high-resolution 3D analysis, and AI integration. These works reflect a growing trend toward combining experimental precision with computational modeling for next-generation materials discovery.
- Bren Scholar (2025–)
Angkur mentors students in aerospace and mechanical systems, fostering innovation through interdisciplinary research. Although specific grants are not listed, his Bren Scholar designation suggests significant institutional support for his research program. He collaborates across disciplines to advance experimental methods and data-centric approaches in mechanics.
Dr. Shaikeea is establishing a unique laboratory at Caltech dedicated to integrating multiple X-ray-based techniques for real-time, 3D mechanical analysis under load. This lab will serve as a hub for data generation and methodological innovation in experimental mechanics.



