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Mollie Johnson is a graduate researcher in the Engineering Systems Laboratory at the Massachusetts Institute of Technology. She recently graduated from the Georgia Institute of Technology with a BS in aerospace engineering and is furthering her education as a masters’ student in the AeroAstro department at MIT.

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Rea Lavi earned his doctoral degree in science & engineering education from the Technion – Israel Institute of Technology, Haifa, Israel, in 2019, his master’s in curriculum management with a thesis and with honors from Bar-Ilan University, Ramat Gan, Israel, in 2013, and both his B.Sc. degrees in biology and in psychology as part of the Neuroscience track from Tel-Aviv University, Tel Aviv-Jaffa, Israel, in 2009.
In 2019, he joined the New Engineering Education Transformation program at the School of Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA. As of 2023, he is also Digital Education Lecturer with the Department of Aeronautics and Astronautics in the same school, and Expert-in-residence with the MIT Abdul Latif Jameel World Education Lab. His work has been published in IEEE Transactions on Education, Journal of Science Education and Technology, and Studies in Educational Evaluation, among other peer-reviewed journals. His research interests include problem structuring, systems thinking, and creative ideation, with specific focus on undergraduate engineering education.
Dr. Lavi is a member of IEEE and of the American Society for Engineering Education. During his time at MIT, he has obtained educational project grants from the Alumni Class Funds and from the d’Arbeloff Fund for Excellence in Education. He has also received several awards for his doctoral research, including but not limited to the Zeff Fellowship for Excelling First-year Doctoral Students and the Miriam and Aaron Gutwirth Fellowship for Excelling Doctoral students.

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Olivier de Weck is the Apollo Program Professor of Astronautics and Engineering Systems at MIT. His research focuses on the technological evolution of complex systems over time, both on Earth and in Space . He is a Fellow of INCOSE and AIAA and served as Faculty Co-Director of the MIT Gordon Engineering Leadership Program

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Prabhat Hajela is the Edward P. Hamilton Professor of Aerospace Engineering at Rensselaer Polytechnic Institute. He earned a Ph.D. in Aeronautics and Astronautics from Stanford University, and his research interests are at the intersection of multidisciplinary system design optimization and emergent computing approaches including evolutionary computing and machine learning. He has authored over 300 papers and articles and co-authored/edited 4 books on structural and multidisciplinary optimization. A recipient of the AIAA’s Biennial Multidisciplinary Design Optimization Award in 2004, Hajela is a Fellow of AIAA, ASME, and Aeronautical Society of India.

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Luca Carlone is the Boeing Career Development Associate Professor in the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology, and a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS). He received his PhD from the Polytechnic University of Turin in 2012. He joined LIDS as a postdoctoral associate (2015) and later as a Research Scientist (2016), after spending two years as a postdoctoral fellow at the Georgia Institute of Technology (2013-2015). His research interests include nonlinear estimation, numerical and distributed optimization, and probabilistic inference, applied to sensing, perception, and decision-making in single and multi-robot systems. His work includes seminal results on certifiably correct algorithms for localization and mapping, as well as approaches for visual-inertial navigation and distributed mapping. He is a recipient of the 2022 and the 2017 Transactions on Robotics King-Sun Fu Memorial Best Paper Award, the Best Student Paper Award at IROS 2021, the Best Paper Award in Robot Vision at ICRA 2020, a 2020 Honorable Mention from the IEEE Robotics and Automation Letters, a Track Best Paper award at the 2021 IEEE Aerospace Conference, the Best Paper Award at WAFR 2016, the Best Student Paper Award at the 2018 Symposium on VLSI Circuits, and he was best paper finalist at RSS 2015, RSS 2021, and WACV 2023. He is also a recipient of the AIAA Aeronautics and Astronautics Advising Award (2022), the NSF CAREER Award (2021), the RSS Early Career Award (2020), the Sloan Research Fellowship (2023), the Google Daydream Award (2019), the Amazon Research Award (2020, 2022), and the MIT AeroAstro Vickie Kerrebrock Faculty Award (2020). He is an IEEE senior member and an AIAA associate fellow. At MIT, he teaches “Robotics: Science and Systems,” the introduction to robotics for MIT undergraduates, and he created the graduate-level course “Visual Navigation for Autonomous Vehicles”, which covers mathematical foundations and fast C++ implementations of spatial perception algorithms for drones and autonomous vehicles.

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Yun Chang received the B.S. degree in aerospace engineering and the M.S. degree in aeronautics and astronautics in 2019 and 2021, respectively, from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, where he is currently working toward the Ph.D. degree with the Department of Aeronautics and Astronautics and the Laboratory for Information and Decision Systems.
He is a member of the SPARK Lab, led by Prof. Luca Carlone. His research interests include robust localization and mapping with applications to multi-robot systems.
Mr. Chang is a recipient of the 2022 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award, the 2019 MIT AeroAstro Andrew G. Morsa Memorial Award for demonstration of ingenuity and initiative in the application of computers to the field of Aeronautics, and the 2019 MIT AeroAstro Henry Webb Salisbury Award for academic performance.

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