Steven Collicott is the principal investigator for one of nine NASA-supported research and technology payloads included through NASA's Flight Opportunities program that launched on Blue Origin's 11th New Shepard mission.

Carolin Frueh, an assistant professor in AAE, worked with NASA’s Goddard Space Flight Center to prevent accidents by learning to predict collisions in a reliable computationally fast manner.

Shaoshuai Mou and Dan DeLaurentis, professors in aeronautics and astronautics, are leading research to use artificial intelligence and learning algorithms to create a platform allowing multiple drones to communicate and adapt as mission factors change. The research received three-year funding from Northrop Grumman Corp. as part of the Real Applications of Learning Machine consortium.

The paper on the Specialized Terrestrial Rotorcraft Explorer (SPECTRE), a Mars UAV science mission concept, was co-authored by six AAE students.

Maisie Linker was selected as the Herbert F. Rogers Award winner, given annually by the School of Aeronautics and Astronautics.

A Purdue project, led by AAE Professor James Garrison, was one of 16 selected by NASA’s CubeSat Launch Initiative.

Alexis Harroun was selected to receive a National Defense Science and Engineering Graduate Fellowship, given by the Department of Defense.

Gerstenmaier, associate administrator for the Human Exploration and Operations Mission Directorate at NASA headquarters, will receive an honorary doctorate in engineering during Purdue’s Division IV commencement at 2 p.m. on May 11.

NASA's Bill Gerstenmaier (BSAAE '77) joined Mary Lynne Dittmar, president and CEO of The Coalition for Deep Space Exploration, and Jonathan Lunine, professor and director of the Cornell University Center for Astrophysics and Planetary Science, on a panel to discuss a variety of topics related to space exploration and policy.

In collaboration with six universities, Purdue was awarded a Multidisciplinary University Research Initiative (MURI) award from the Department of Defense (DoD) to build a capability to allow scientists to predict the behavior of energetic materials using advanced machine learning tools.