The Michigan Engineer News Center

Necmiye Ozay receives ONR Young Investigator Award to advance research in autonomous systems

Research will focus on how autonomous vehicles adapt to wide-ranging changes.| Short Read
EnlargeNecmiye Ozay. Photo: Joseph Xu, Michigan Engineering.
IMAGE:  Necmiye Ozay

Necmiye Ozay received a 2018 Young Investigator Award from the Office of Naval Research (ONR) for her research project “Correct-by-construction Control with Non-asymptotic Learning, Estimation and Detection in-the-Loop.” The award comes from the Science of Autonomy Program, which emphasizes a multi-disciplinary approach to the development of future autonomous systems.

Her research will incorporate the latest advances in learning and estimation by developing new theory and algorithms that seamlessly blend adaptability, safety and correctness.

EnlargeNecmiye Ozay's scaled car
IMAGE:  An autonomous scaled car platform in Ozay’s laboratory.

Specific problems Ozay is investigating in her research include autonomous vehicles that encounter temporary or permanent surface changes that impact the vehicle, adapting to system failures or malfunctions, and even the problem of maintaining proper temperature of alternative fuel sources such as fuel cells.

According to Ozay, correct-by-construction control involves constructing “a model of the system and a formal high-level specification describing the desired behavior, and leveraging ideas from control theory (hybrid systems) and computer science (temporal logics, automata and game theory) to automatically construct a controller that guarantees that the closed loop system satisfies the specification regarding safety and mission objectives given assumptions on the environment and on the system model.”

Her research will focus on the problems of handling both abrupt and gradual changes on a system, as well as scalable control synthesis for adaptation.

This research has the goal of improving how learning-enabled autonomous systems are designed and operated with respect to design time and adaptability, while allowing for modular upgrades to the system.

She is actively applying her research in correct-by-construction control synthesis to autonomous cars in Mcity.

Ozay focuses on control systems, dynamical systems, cyber-physical systems, identification, verification, and validation of systems and information extraction from sensory data, along with autonomy and perception. She has already made major contributions to correct-by-construction control synthesis for cyber-physical systems.

Prof. Ozay teaches the graduate course Linear Systems Theory and the undergraduate/graduate course Control Systems Analysis and Design. She also developed the graduate course Hybrid Systems: Specification, Verification and Control.

Prof. Ozay has received an NSF CAREER Award, a NASA Early Career Faculty Award, a DARPA Young Faculty Award, and a Director’s Fellowship from DARPA. In addition, she earned the Non-Linear Analysis: Hybrid Systems Paper Prize from the International Federation of Automatic Control, and the 1938E Award from the College of Engineering for excellence as an educator.

Prof. Ozay serves as Vice Chair on the IEEE Technical Committee on Computational Aspects of Control System Design, and is a member of the IEEE Technical Committee on Hybrid Systems. She is an Associate Editor for Journal of Discrete Event Dynamic Systems. She also serves as an organizer for the International Conference on Cyber-Physical Systems, and helped organize the 6th Midwest Workshop on Control and Game Theory, held in Ann Arbor, MI.

Necmiye Ozay. Photo: Joseph Xu, Michigan Engineering.
Necmiye Ozay's scaled car
Portrait of Catharine June

Contact

Catharine June
ECE Communications and Marketing Manager

Electrical Engineering and Computer Science

(734) 936-2965

3301 EECS

Researchers
  • Necmiye Ozay

    Necmiye Ozay

    Assistant Professor in Electrical and Computer Engineering

Sound wave visualization. Getty Images.

Mining soundwaves: Researchers unlock new data in sonar signals

“Acoustic fields are unexpectedly richer in information than is typically thought.” | Medium Read