Title: Advancing air mobility via optimization and AI

 

Abstract: The widespread adoption of uncrewed aerial vehicles (UAVs), or drones, across transportation, logistics, and other sectors presents both unprecedented challenges and exciting opportunities for innovation. Key areas affected include air traffic management, infrastructure development, and business model evolution. Effectively coordinating the dynamic allocation of shared resources - such as airspace, UAVs, and vertiports - demands precise mathematical modeling and large-scale optimization. In this talk, I will explore several operations research questions addressed through optimization and AI techniques. Topics include determining optimal locations for vertiports, managing high-density air traffic, dispatching air fleets for rapid package delivery, and achieving autonomous UAV landings.

 

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The CAD Seminar Series is a dedicated platform for advancing knowledge, fostering innovation, and promoting collaboration across the fields of Computation, Artificial Intelligence, and Data Science. This series brings together leading experts, researchers, and professionals to explore the latest developments, tackle emerging challenges, and drive forward-thinking solutions at the convergence of these critical disciplines.

 

Objectives:

 

• Advance Knowledge: Share cutting-edge research and insights that push the boundaries of what is known in CAD.

• Foster Innovation: Encourage the development of novel ideas and solutions through interdisciplinary dialogue and creative thinking.

• Promote Collaboration: Unite expertise across disciplines and build bridges between academia, industry, and government to address complex problems and create opportunities for joint ventures.

Schedule: The seminars will be held on a weekly basis (unless otherwise noted) throughout the academic year. For Fall 2024, the seminars are tentatively scheduled for Wednesdays from 2:30 PM to 3:30 PM, and will be available both in-person at 1146 FAB and online. Each seminar will spotlight a particular topic, providing an in-depth exploration and fostering lively discussions. 

 

Target Audience: The CAD Seminar Series is designed for a diverse audience, including faculty, researchers, students, and professionals in Computation, AI, Data Science, and related fields. It serves as a forum for exchanging ideas, networking, and contributing to the growth of these rapidly evolving areas. We highly recommend in-person attendance to enhance engagement and networking opportunities with speakers and fellow participants.

 

Call for Participation: We welcome contributions from researchers, practitioners, and students. Whether presenting your work, participating in discussions, or attending as a learner, your involvement is crucial to the success of this collaborative initiative.