Our Team

Prof. Juan J. Alonso is an internationally recognized expert in computational aerospace design and serves as a distinguished faculty member at The Standard School of Machine Learning (TheSSML). As the founder and director of the Aerospace Design Laboratory (ADL), he brings deep expertise in high-fidelity simulation, multi-disciplinary optimization, and high-performance computing—skills central to TheSSML’s mission of integrating advanced engineering with cutting-edge computational intelligence.

Prof. Alonso’s research spans a wide spectrum of aerospace applications, including transonic, supersonic, and hypersonic aircraft; helicopters; turbomachinery; and launch and re-entry vehicles. With over 200 technical publications, his contributions in computational aircraft and spacecraft design are globally influential, shaping innovation in both manned and unmanned flight systems. His work demonstrates how computational models, intelligent algorithms, and real-world engineering can combine to create efficient, sustainable, and highly optimized aerospace systems.

A passionate educator, Prof. Alonso has played a key role in designing advanced engineering curricula at Stanford University, including courses in aircraft design, sustainable aviation, UAS design, and computational engineering. At TheSSML, he continues this commitment by helping students develop the computational thinking, engineering intuition, and analytical depth required to innovate in aerospace and AI-driven industries.

His teams have set multiple world records, including the global speed record for human-powered water vehicles and the altitude record for an unmanned electric aircraft weighing under 5 lbs. These achievements reflect his commitment to pushing the boundaries of engineering performance while mentoring the next generation of scientists and engineers.

Prof. Alonso brings exceptional technical expertise, educational leadership, and research excellence to TheSSML, contributing to its vision of shaping future innovators through computational mastery and interdisciplinary learning.