"You never actually lose. You either win, or you learn."

In this section I have fitted some of the subjects and topics I have either studied in significant detail, or taken courses in academia, or worked in projects relating to those fields, granting me knowledge and experience about these areas.

Hydraulics and Pneumatics

Not only I studied this subject in B.Sc. and engaged in many experiments, but also I made extensive use of it for the Pipe Inspection Robot project, in which almost all the movements are actuated hydraulically. The design included cylinders, valves, pumps, hydromotors and air motors, as well as an oil tank and compressor.


I not only passed this course with an A at the graduate level but also my entire research focus throughout my time at KOC University has been human-robot interaction, which heavily involves coding and working with robots and robotics concepts. I can not only code UR5 and KUKA robots, but also I am familiar with ROS 2.0 and I have worked with Gazebo alongside it. That is me in the picture using the KUKA LBR iiwa 7 R800 to drill a hole in a marked position on a curved surface, with a custom non-perpendicular drilling angle, while wearing the Microsoft Hololens AR Goggle as an interface.

Machine Learning

Mixing with M.Sc. Mechatronics students of the ASR lab, combined with my inherent long-standing passion for Artificial Intelligence helped me get acquainted with various supervised learning and reinforcement learning techniques, and machine learning methods such as Artificial Neural Networks, K-Nearest Neighbor methods, Deep Learning, Reinforced Learning, Decision Trees and Random Forests, Support Vector Machines, and all of that introduced me to other Data Mining, Feature Selection-and-Extraction methods, and concepts. I passed the Introduction to Machine Learning course with an A in M.Sc. and I have been using ANN and LSTM models for time series regression and classification for over a year now. I am also working on a possible reinforcement learning method for optimal adaptive admittance control in pHRI together with supervised human intention recognition in the form of time-series classification.

Computer Graphics

I have taken this course in M.Sc. at KOC University. The course used Shader-based OpenGL, which may not be the most popular graphics library nowadays, but it is one of the most basic ones, and learning it would make learning other graphics libraries much easier. I have also worked with the Coin3D library of the OpenInventor library, which is also OpenGL-based. I am right now working on a Unity project for making an application that makes visualizing the movement and control of robotic manipulators much easier and more intuitive.

Image Processing

My B.Sc. project involved heavy image processing in OpenCV. My job was to use a 600-FPS camera to calculate the size and frequency of bubbles resulting from static pool boiling of water in a porous medium. I used OpenCV in both MATLAB and Python for this task, and was highly successful at it. The goal of the project was to understand how the forming of bubbles in pool boiling in porous media was affected by the porosity and permeability of the medium itself.

Surface Electromyography

At the moment, I am working on surface Electromyography signals (sEMG) obtained from the forearm muscles of humans for intention recognition of human operators in physical human-robot interaction. sEMG sensor technologies are advancing at a rapid rate. Wireless EMG products are already available on the market, and EMG equipment is more practical and cheaper than using a human force sensor in a robotic setup.

Advanced Engineering Mathematics

Due to my presence in the ASR lab, I was allowed to attend some of the courses M.Sc. students were taking. In this course I acquainted myself to matrix algebra, PDEs, equation systems, and calculus of variations.

Nonlinear Control

This course was taught in two parts: analysis of nonlinear systems in terms of stability and so forth, and design and control of nonlinear systems. I familiarized with feedback linearization, Lyapunov stability concepts, sliding-mode control, adaptive control, robust control, and so forth.

Modern Control Theory

The control engineering concepts that we studied is B.Sc., almost entirely focused on conventional classical control concepts such as transfer functions, Bode and Nyquist diagrams, root locus methods, and so forth. It was only a year after graduation that I noticed the fundamental importance of state-space analysis of dynamic and control systems, which is why I familiarized myself to it, and partook in the Ball-on-beam project in University of Tehran. I was intrigued by the topics I studied, such as designing, analyzing and controlling LTI and LTV systems using state-space methods in MATLAB and Simulink.


I had heard of Micro and Nano-Electromechanical Systems after B.Sc., but I never had any time to study the concept until last year. I found enough time to briefly study the topics of Micro and Nano-sensors, use of Electrostatic forces and Magnetic moments in actuation of these devices, Molding and Plating, Wet and Dry Etching, EDM and other Micro and Nanofabrication technologies used for making them,Vapor Deposition, Beam Lithography Methods, use of Piezoelectricity in MEMS devices, Modern Accelerometers, IMUs, MEMS Gyroscopes, Precision Resonators, Silicon Pressure Sensors, and so forth. I took the Mechanics of Microsensors class and passed it with an A+ last year where I used COMSOL for analyzing a capacitive comb-drive-actuated strain gauge acting as a force sensor. 


I have had some brief studies regarding micro and nanomanufacturing. This has coincided with my awareness of the potential use of Micro-manufacturing in micro-scale devices that have always piqued my interest. I have briefly studied the concepts of Micro-mechanical Cutting, Micro-EDM, Laser Beam Machining, Micro-casting, Micro-injection Molding, Micro-forming, Micro-milling, etc.

Fuzzy Control

The paper I have co-authored uses Fuzzy control for the adaptable part of a pipe inspection robot. I used trapezoid functions for motor current, robot velocity, and SMA voltages. The concept of Fuzzy Logic and its applications in systems and control have intrigued me greatly. Fuzzy control can be improved to be adaptive fuzzy control, or learning fuzzy control. Fuzzy logic also finds its way into machine learning and artificial intelligence. It has many advantages in comparison to other continuous-valued methods.