3/11/2026

Articles

• Aslan Yıldız, Ö., Sarıçiçek, İ., & Yazıcı, A. (2025a). A Reinforcement Learning-Based Solution for the Capacitated Electric Vehicle Routing Problem from the Last-Mile Delivery Perspective. Applied Sciences, 15(3), 1068. https://doi.org/10.3390/app15031068
• Aslan Yıldız, Ö., Sarıçiçek, İ., & Yazıcı, A. (2025b). A transformer-based deep reinforcement learning for the Dial-a-Ride problem. Knowledge and Information Systems, 67(10), 9085-9109. https://doi.org/10.1007/s10115-025-02493-4
• Yılmaz, M., Çinar, E., & Yazıcı, A. (2025). Federated Learning-Based State of Charge Estimation in Electric Vehicles Using Federated Adaptive Client Momentum. IEEE Access, 13, 72128-72141. https://doi.org/10.1109/ACCESS.2025.3563188
• Taş, M. B. H., Özkan, K., Sarıçiçek, İ., & Yazici, A. (2025). Transportation Mode Selection Using Reinforcement Learning in Simulation of Urban Mobility. Applied Sciences, 15(2), 806. https://doi.org/10.3390/app15020806
• Yılmaz, M., Çinar, E., & Yazıcı, A. (2025). A Transformer-Based Model for State of Charge Estimation of Electric Vehicle Batteries. IEEE Access, 13, 33035-33048. https://doi.org/10.1109/ACCESS.2025.3542961
• Caferler, B., Ünal, A., Bozkurt Keser, S., & Yazıcı, A. (2025). A Review for Remaining Driving Range Prediction of Electric Vehicles Using Machine Learning Algorithms. Journal of Data Science and Intelligent Systems. https://doi.org/10.47852/bonviewJDSIS52025131
• Douaidi, L., Senouci, S.-M., El Korbi, I., Harrou, F., & Yazıcı, A. (2025). Federated deep learning for enhanced prediction of electric vehicle charging station availability. Cluster Computing, 28(6), 364. https://doi.org/10.1007/s10586-025-05152-z
• Keser, S. B., Sarıçiçek, İ., & Yazıcı, A. (2025). Electric Vehicle Routing With Recharging Stations: Trade‐Offs in Last‐Mile Delivery. IET Intelligent Transport Systems, 19(1), e70052. https://doi.org/10.1049/itr2.70052
• Polat, A. A., Bozkurt Keser, S., Sarıçiçek, İ., Erdoğmuş, A. K., Kafalı, A., & Yazıcı, A. (2025). A dataset for state of charge and range estimation of an L5 type electric vehicle that is used for Urban Logistic. Data in Brief, 62, 111933. https://doi.org/10.1016/j.dib.2025.111933
• Polat, A. A., Bozkurt Keser, S., Sarıçiçek, İ., & Yazıcı, A. (2025). Analysis of Factors Affecting Electric Vehicle Range Estimation: A Case Study of the Eskisehir Osmangazi University Campus. Sustainability, 17(8), 3488. https://doi.org/10.3390/su17083488
• Ünal, Y., Sarıçiçek, İ., Bozkurt Keser, S., & Yazıcı, A. (2025). Electric Vehicle Routing with Time Windows and Charging Stations from the Perspective of Customer Satisfaction. Applied Sciences, 15(9), 4703. https://doi.org/10.3390/app15094703
• Caglar, O., Baglum, C., & Yayan, U. (2025). CleanAI: Deep neural network model quality evaluation tool. SoftwareX, 29, 102015. https://doi.org/10.1016/j.softx.2024.102015
• Esen, Y. E., Çeti̇Ncan, B. K., Yayan, K., Burnak, Ö., & Yayan, U. (2025). XR4MCR: Multiplayer collaborative robotics maintenance training platform in extended reality. SoftwareX, 31, 102348. https://doi.org/10.1016/j.softx.2025.102348
• Esen, Y. E., Kaan Çetincan, B., Yayan, K., Güray Gürlek, H., & Yayan, U. (2025). XR-Driven Robotic System Training for Occupational Health, Safety, and Maintenance. IEEE Access, 13, 61708-61727. https://doi.org/10.1109/ACCESS.2025.3556699
• Örnek, Ö., Değirmenci, E., & Yazıcı, A. (2025). Online learning-based anomaly detection for positioning system. Expert Systems with Applications, 267, 126221. https://doi.org/10.1016/j.eswa.2024.126221
• Tuğrul, K. M., Kaya, R., Özkan, K., Ceyhan, M., Gürel, U., & Fidantemiz, F. Y. (2025). Early detection of Cercospora beticola and powdery mildew diseases in sugar beet using uncrewed aerial vehicle-based remote sensing and machine learning. PeerJ, 13, e19530. https://doi.org/10.7717/peerj.19530
• Yıldız, Ö. A., Yazıcı, A., & Sarıçiçek, İ. (2025). Conflict-Free Path Planning for Autonomous Transport Vehicles. 국제산업공학저널, 32(2). https://doi.org/10.23055/IJIETAP.2025.32.2.10445

 

Papers Presented at Peer-Reviewed Scientific Conferences

• Bağlum, C., & Yayan, U. (2025). STS: AI-Driven Smart Test Scenario Generation Tool. 2025 33rd Signal Processing and Communications Applications Conference (SIU), 1-4. https://doi.org/10.1109/SIU66497.2025.11112297
• Yılmaz, M., Kanber, B., Kırca, Y. S., Kahraman, S., Özkan, K., Yayan, U., Sarıçiçek, İ., Çinar, E., Özkan, M., & Yazıcı, A. (2025). Implementation of IoT-Based Communication System for Electric Vehicle Fleets. 2025 33rd Signal Processing and Communications Applications Conference (SIU), 1-4. https://doi.org/10.1109/SIU66497.2025.11111926
• Kanak, A., Ergün, S., Arif, İ., Atalay, A. S., İnanç, S. E., Herkiloğlu, O., Yazıcı, A., Kirca, Y. S., Ozberk, M., Erdogmus, A. K., Kafalı, A., Bayar, D., Taş, M. O., Davoli, L., Belli, L., Ferrari, G., Muneer, B., Palazzi, V., Roselli, L., & Gelati, F. (2025). Multi-Partner Project: Electric Vehicle Data Acquisition and Valorisation: A Perspective from the OPEVA Project. 2025 Design, Automation & Test in Europe Conference (DATE), 1-7. https://doi.org/10.23919/DATE64628.2025.10992740
• Kahraman, S., & Yayan, U. (2025). Development and Simulation of a Robot Arm Functional Mockup Unit (FMU) for Digital Twins. 2025 33rd Signal Processing and Communications Applications Conference (SIU), 1-4. https://doi.org/10.1109/SIU66497.2025.11112169
•  Sevim, E., Yılmaz, M., Çinar, E., & Yazıcı, A. (2025). Federated Learning Based State of Health Estimation for Lithium-Ion Batteries. 2025 20th Annual System of Systems Engineering Conference (SoSE), 1-6. https://doi.org/10.1109/SoSE66311.2025.11083856

Funded Projects

• Yayan, U., & Yayan, K. (2025). Manufacturing intelligent digital interactive assistant (MINDIA) [Project]. Horizon Europe Programme (2025–2026).

 

Books

• Yazıcı, A., Özkan, M., & Yayan, U. (2025). Tekstil ve hazır giyim endüstrisinde otomasyon (otonom robotlar). In İ. İlhan & A. Özbek (Eds.), Nesnelerin İnterneti çağında tekstil endüstrisi (pp. 81–118). İstanbul Ticaret Odası.