Adjunct Associate Professor of Computer Science
- Doctoral Degree, Mechanical Engineering, University of Pennsylvania
- Master's Degree, Mechanical Engineering, University of Pennsylvania
- Bachelor's Degree, Mechanical Engineering, Drexel University
Nora Ayanian is Assistant Professor of Computer Science and Andrew and Erna Viterbi Early Career Chair at the University of Southern California. Her research focuses on creating end-to-end solutions for coordinating teams of robots that start from truly high-level specifications and deliver code for individual robots in the team, such as using simple multitouch inputs to control a team of UAVs. Ayanian brings a unique approach to multirobot systems, creating unified solutions that address task assignment, path planning, and control that are broadly applicable across all aspects of multirobot systems and mobile sensor networks. Her solutions provide guarantees of convergence and safety on real robotic systems. She won the Best Student Paper Award at the International Conference on Robotics and Automation 2008 for her work on constrained multirobot control, and with her collaborators, Best Paper in Robotics Track at the International Conference on Automated Planning and Scheduling. She was named one of IEEE Intelligent Systems "AI's 10 to watch" (2013), NerdScholar's "40 Under 40: Professors who Inspire" (2014), and was part of the inaugural Mic 50 (2015), Mic.com's list of 50 influential young people, and MIT Technology Review's "35 Innovators under 35" (TR35, 2016). In 2016, she was received the NSF CAREER award and the Okawa Foundation Research Grant. Ayanian is a co-founder and current co-chair of the IEEE Robotics and Automation Society Technical Committee on Multi-Robot Systems.
Ayanian's research focuses on the question: How can we enable almost anyone to use teams of robots? To that end, Ayanian studies and develops end-to-end solutions for coordinating teams of robots, combining automation and artificial intelligence to create new kinds of autonomy. These solutions take very high level specifications, such as simple multi-touch input from a tablet, and provide automated code delivery to all robots in the team. By applying AI and studying human interaction, robots work collaboratively and accomplish tasks autonomously. Her solutions are broadly applicable across all aspects of multi-robot systems and mobile sensor networks, including manufacturing, warehousing, environmental monitoring, precision agriculture, and emergency response.
Some of her work is featured on her lab's YouTube channel: https://www.youtube.com/watch?v=7KIa9FlmbRc
- 2016 MIT Technology Review 35 Innovators Under 35 (TR35)
- 2016 The Okawa Foundation for Information and Telecommunications Research Grant
- 2016 International Conference on Automated Planning and Scheduling Best Paper in Robotics Track
- 2016 National Science Foundation NSF CAREER Award
- 2015 University of Southern California Hanna Reisler Mentorship Award
- 2015 Mic.com Mic50
- 2014 NerdWallet 40 under 40 Professors who Inspire
- 2013 IEEE Intelligent Systems AI's 10 to Watch