Necdet Aybat

Necdet Aybat is an Associate Professor at the Department of Industrial and Manufacturing Engineering, Pennsylvania State University, College of Engineering. His research focuses on the design of new optimization algorithms, federated learning, distributed multi-agent optimization, and matrix decomposition for image-video processing applications.

• Research Interests: Spanning convex optimization, distributed consensus methods, and stochastic gradient techniques.
• Externally Funded Projects: Includes ONR, NSF, and ARO grants totaling over $1.3 million for work on robust optimization algorithms and decentralized power flow optimization.

His recent publications highlight advancements in primal-dual algorithms, accelerated gradient methods, and quasi-norm minimization. While no scientific awards are listed, his collaborative projects and teaching contributions (e.g., IE/EE 585 Convex Optimization and IE 597 Modern Data Analytics) underscore his academic impact.