Systems Laboratory

Welcome to Systems Laboratory

About Us

We study and create intelligence. Both artificial and natural manifestations of intelligence are the focus of our research. That’s why our lab is highly interdisciplinary, drawing ideas from control theory, physics, mathematics, game theory, machine learning, and statistics. We specialize in the modeling and control of cyber-physical human systems, where the human, the physical system, and enabling cyber-technologies are interconnected through multifarious interactions to accomplish a certain goal. Our engineering applications cover aerospace, automotive and robotics fields.

Join Us!

In Systems Lab, we are developing theories and algorithms to understand and build complex intelligent systems. If you want to study and contribute to the fields of autonomy, human behavior, adaptation, and interaction between natural and artificial intelligence, come and be a part of us. If you always feel like a beginner, like to think out of the box, and don’t like conventional approaches to problems, you are welcome here. Just send a short email to Yildiray Yildiz ( and tell us why you want to be a part of us. Undergraduates, graduates, and students from all departments and all universities are welcome. (Please attach a CV to your email.)


Congratulations! Systems Lab member Cevahir Köprülü received an offer from the University of Texas at Austin to pursue his Ph.D. in the Decision, Information & Communications Engineering track of the Department of Electrical and Computer Engineering.

31 May 2021

Systems Lab members continue to study and create intelligence: Shahab Tohidi, Mert Albaba and Cevahir Koprulu will present their recent work covering control theory, machine learning and game theory at 2021 IEEE Conference on Control Technology and Applications.

Shahab will talk about designing robust and adaptive controllers for uncertain systems with redundant actuators.

Mert will present a model of 3D airspaces where unmanned and manned aircraft coexist.

Cevahir will show how to use previously trained agent policies as actions in reinforcement learning, in the context of hierarchical game theory.

We will announce the seminar schedule once we hear from the conference organizers.

25 April 2021

Berat Mert Albaba’s paper “Driver Modeling through Deep Reinforcement Learning and Behavioral Game Theory” is accepted for publication in IEEE Transactions on Control Systems Technology.

19 April 2021

Congratulations! Systems Lab members Emre Eraslan, Mert Albaba and Cem Okan Yaldız received offers from top US institutions for their PhD programs

14 April 2021

Shahab Tohidi’s paper “Discrete Adaptive Control Allocation,” is accepted for publication at 2021 American Control Conference in New Orleans.

26 January 2021