Summary
I hold a Bachelor's degree in Electronics Engineering from Mehran University of Engineering and Technology (MUET) and a Master's degree in Electronics Engineering from Kadir Has University, Turkey.
My academic and research background focuses on Virtual Reality (VR) and Augmented Reality (AR).
Academic Background
MSc
( )
Kadir Has University
2024
BE
( )
Mehran University of Engineering and Technology
2021
Journal Publications
Visuo-haptic exploration with relocated haptic feedback: impact of virtual and augmented reality
29-Jul-2025
Rendering haptic feedback on the wrist is an effective solution for freeing users' hands during virtual interactions while still providing haptic feedback, mostly focusing on Virtual Reality (VR) environments. Unfortunately, whether these solutions can be extended to Augmented Reality (AR) interactions has not been investigated before. In this paper, we investigate the perceptual differences between VR and AR environments with a user study experiment based on a stiffness discrimination task. Our findings revealed similar task accuracy and sensitivity in VR and AR but different exploration behaviors (i.e. higher interaction time in AR) and user experience (i.e. higher enjoyment and less mental fatigue in AR).
Conference Publications
Enhancing Eye-Hand Coordination in Volleyball Players: A Comparative Analysis of VR, AR, and 2D Display Technologies and Task Instructions
21-Oct-2024
Previous studies analyzed user motor performance with Virtual Reality (VR) and Augmented Reality (AR) Eye-Hand Coordination Training Systems (EHCTSs) while asking participants to follow specific task instructions. Although these studies suggested VR & AR EHCTSs as potential training systems for sports players, they recruited participants for their user studies among general population. In this paper, we examined the training performance of 16 professional volleyball players over 8 days using EHCTSs with three display technologies (VR, AR, and 2D touchscreen) and with four distinct task instructions (prioritizing speed, error rate, accuracy, or none). Our results indicate that volleyball players performed best with 2D touchscreen in terms of time, error rate, accuracy, precision, and throughput. Moreover, their performance was superior when using VR over AR.
Eye-hand coordination training: A systematic comparison of 2D, VR, and AR display technologies and task instructions
16-Mar-2024
evious studies on Eye-Hand Coordination Training (EHCT) focused on the comparison of user motor performance across different hardware with cross-sectional studies. In this paper, we compare user motor performance with an EHCT setup in Augmented Reality (AR), Virtual Reality (VR), and on a 2D touchscreen display in a longitudinal study. Through a ten-day user study, we thoroughly analyzed the motor performance of twenty participants with five task instructions focusing on speed, error rate, accuracy, precision, and none. As a novel evaluation criterion, we also analyzed the participants’ performance in terms of effective throughput. The results showed that each task instruction has a different effect on one or more psychomotor characteristics of the trainee, which highlights the importance of personalized training programs.
Sustainable agriculture: an IoT-based solution for early disease detection in greenhouses
09-Jun-2023
The Internet of Things (IoT) is a cutting-edge paradigm that involves the interconnection of multiple advanced sensors and peripheral devices to enable the automation and orchestration of various complex systems. In the agricultural context, smart devices are utilized to acquire and transmit data from a diverse range of sensors that monitor intricate environmental parameters crucial to ensuring optimal plant growth. These factors encompass but are not limited to humidity, temperature, soil moisture, and water pH. Continuous monitoring and control of these environmental aspects are essential for maximizing plant growth and yield. Manual disease monitoring is labor-intensive and requires specialized expertise in plant pathology. To overcome these challenges, convolutional neural network models employing deep learning techniques have been developed to detect and diagnose diseases in plants.
On the effectiveness of virtual eye-hand coordination training with head mounted displays
25-Mar-2023
Eye-hand coordination training systems are used to train participants' motor skills and visual perception. Such systems have already been tested in Virtual Reality, and the results revealed that Head Mounted Display-based systems have the potential to improve the motor training. However, this was only investigated in an hour-long study. In the longitudinal study reported here, we analyzed the motor performance of three participants in ten sessions with three different assessment criteria, where participants were instructed to focus on speed, error rate, or complete the training freely (with no instructions). We also assessed the effective throughput performance of the participants. Our results indicate that effective throughput can be potentially used as an additional assessment criterion. We hope that our results will help practitioners and developers design efficient Virtual Reality training systems.
Namal University