Ghassemi wins third place in paper competition at the AIAA Aviation Forum

Payem Ghassemi receiving an award at the conference.

Dr. Raymond Kolonay of the Air Force Research Laboratory (right), and MDO Subconference Chair in Aviation Douglas Allaire (left) of Texas A & M present the award to Payam Ghassemi (center) at the AIAA Aviation and Aeronautics Forum and Exposition.

by Nicole Capozziello

Published September 19, 2019

Payam Ghassemi, a PhD student in the Department of Mechanical and Aerospace Engineering, earned third place at the 2019 AIAA Multidisciplinary Design Optimization student paper competition.

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“Payam was recognized with this highly competitive award for his development of a machine learning augmented design approach that can compute search processes in a matter of hours, as opposed to taking weeks of simulations.”
Souma Chowdhury, assistant professor
Department of Mechanical and Aerospace Engineering
portrait of Payam Ghassemi.

Payam Ghassemi

Ghassemi received a $500 award for his paper entitled “Adaptive Model Refinement with Batch Bayesian Sampling for Optimization of Bio-inspired Flow Tailoring.” 

The competition was part of AIAA’s annual Aviation and Aeronautics Forum and Exposition, and overseen by the Multidisciplinary Design Optimization (MDO) Technical Committee of the American Institute of Aeronautics and Astronautics (AIAA). It was sponsored by the NASA Glenn Research Center.

Ghassemi’s research takes inspiration from “riblet” features on shark skins, tiny scales that help them to swim more efficiently. When this principle is applied to engineering products, it can improve the aerodynamics of products from swimsuits to airplanes. His research showed that applying these riblets on airfoils can save up to 10% aerodynamic efficiency – and ultimately be used to craft airplanes with a lower environmental footprint or civilian drones with longer ranges.

“Taking inspiration from nature in designing future engineering systems often boils down to searching for specialized configurations that have evolved over millions of years,” says Souma Chowdhury, Ghassemi’s advisor and an assistant professor in the Department of Mechanical and Aerospace Engineering. “Payam was recognized with this highly competitive award for his development of a machine learning augmented design approach that can compute such search processes in a matter of hours, as opposed to taking weeks of simulations.”

Ghassemi is a graduate research assistant in the Adaptive Design Algorithms, Models and Systems (ADAMS) Laboratory, directed by Chowdhury. His other research involves developing decentralized and efficient algorithms that can guide a large team of collaborative robots to find a source or target efficiently. Some applications are victim search in disaster response and gas leakage localization.

Chowdhury and M.S. student Sumeet Lulekar were co-authors of the paper.

The AIAA’s Aviation and Aeronautics Forum and Exposition brings together professionals from the aerospace industry and academia to discuss the most pressing issues in the field. It was held in Dallas from June 16-21, 2019.

About the American Institute of Aeronautics and Astronautics

Comprised of over 35,000 members, AIAA is the world's largest technical society dedicated to the global aerospace profession, with a mission of inspiring and advancing the future of aerospace for the benefit of humanity.