Academic Journey: Between 2015 and 2024, I worked at Karatay University in Turkey, where I held the position of Assistant Professor in the Mechatronics Engineering Department for nearly a decade. Throughout this period, I served as a lecturer for undergraduate and postgraduate courses covering a range of subjects, including AI-related courses, signal processing, computer programming, and embedded systems. Additionally, I conducted research on various industrial and academic projects, with a specific focus on machine learning and artificial intelligence. During this period, I supervised numerous undergraduate and postgraduate students.

Research and Collaborations: My research portfolio includes a diverse array of projects aimed at leveraging AI technologies to address real-world challenges. Collaborating with universities and companies, I am developing solutions for various domains. With Konya Technical University’s civil engineering and architecture departments, we are pioneering the development of an AI-based system to extract geometric parameters from building planes and façade images, enhancing rapid seismic evaluation methods. Partnering with Turk Telekom Turkey, our research focuses on developing AI algorithms for network-related data, particularly anomaly detection, automating root cause analysis, and KPI tuning. In collaboration with Neurocom in Australia, we are spearheading the development of a SaaS solution using machine learning techniques to intelligently monitor money transactions in streaming data. Additionally, my partnership with Meliora Academy involves creating interactive games utilizing computer vision methods to enhance mathematics education for fourth-grade students. With AutoDidactic Technologies, we have developed a reinforcement learning-based simulation solution for pilot training, facilitating adaptive learning in various scenarios. Moreover, my research extends to remote sensing and medical image analysis, encompassing MRI, Transvaginal Ultrasound (TVUS) images, and whole slide images for breast cancer grading.

Patents and Publications:

Patents 

1. Yavariabdi 2021. Toplu taşıma araçlarında kullanmak üzere termal sisli dezenfeksiyon sistemi. Turkey Patent, 2020/08604, filed June 03, 2020, and issued August 23, 2021.
2. Yavariabdi, M. H. Arslan, G. Doğan, Y. Ekici, F. M. Asik, Konut türü binalarin deprem risk önceliklerinin tespitinde kullanilan geometrik parametrelerin evrişimli sinir ağlari ile belirlenmesi yöntemi, Turkey Patent, 2021/021293, filed December 27, 2021, and accepted August 04, 2023.

SCI/SCI-E Journal Papers

1. Tekin, H. Kusetogullari, A. Yavariabdi, C. Yazici, F. Tokat, B. Darbaz, L. O. Iheme, , E. Bozaba, S. Cayir, G. Solmaz, G. Ozsoy, S. Ayaltı, C. K. Kayhan, U. Ince, and B. Uzel, “Improving Computer-Aided Breast Cancer Diagnosis with Generative Adversarial-based Stain Normalization: A Comparative Analysis of Conventional and Unsupervised GAN Techniques”, NPJ Breast Cancer, Submitted 2023.
2. Yavariabdi, H. Kusetogullari, H. Ertan, E. Aksoy, A. Emre Tiryaki, and İ. Berk Özalp, “A Multi-Head CNN-LSTM Model to Detect Performance Anomalies in Home Subscriber Servers”, IEEE Signal Processing Letters, Submitted 2023.
3. Yavariabdi, H. Kusetogullari, O. Orhan, E. Uray, V. Demir, and T. Celik, “SinkholeNet: A Novel RGB-Slope Sinkhole Dataset and Deep Weakly-Supervised Learning Framework for Sinkhole Classification and Localization”, Egyptian journal of remote sensing and space sciences, 2023.
4. Tekin, C. Yazici, H. Kusetogullari, F. Tokat, B. Darbaz, L. O. Iheme, A. Yavariabdi, E. Bozaba, S. Cayir, G. Solmaz, G. Ozsoy, S. Ayaltı, C. K. Kayhan, U. Ince, and B. Uzel, “Tubule-U-Net: A Novel Dataset and Deep Learning Patch-Based Model for Incomplete and Irregular Tubule of Breast Tissue Segmentation”, Nature: Scientific Reports, 2023.
5. Yavariabdi, H. Kusetogullari, T. Celik, “CARDIS: A Swedish Historical Handwritten Character and Word Dataset”, IEEE Access, 2022.
6. Cheddad, H. Kusetogullari, A. Hilmkil, L. Sundin, A. Yavariabdi, M.  Aouache, J. Hall, “SHIBR-The Swedish Historical Birth Records: A Semi-Annotated Dataset”, Neural Computing and Applications, 2021.
7. Yavariabdi, H. Kusetogullari, T. Celik, H. Cicek, ”FastUAV-NET: A Multi-UAV Detection Algorithm for Embedded Platforms” Electronics, vol. 10, no. 6, 2021.
8. Kusetogullari, A. Yavariabdi, J. Hall, N. Lavesson, “DIGITNET: A Deep Handwritten Digit Detection and Recognition Method Using a New Historical Handwritten Digit Dataset”, Big Data Research, vol. 23, 2021.
9. Kusetogullari, A. Yavariabdi, A. Cheddad, H. Grahn, and J. Hall, ”ARDIS: a Swedish historical handwritten digit dataset”, Neural Computing and Applications, vol. 32, pp. 16505–16518, 2020.
10. Kusetogullari and A. Yavariabdi, ”Evolutionary Multiobjective Multiple Description Wavelet Based Image Coding in the Presence of Mixed Noise in Images”, Applied Soft Computing, vol. 73, pp. 1039-1052, Dec. 2018.
11. Kusetogullari and A. Yavariabdi, ”Unsupervised Change Detection in Landsat Images with Atmospheric Artifacts: A Fuzzy Multiobjective Approach”, Journal of Mathematical Problems in Engineering, may 2018.
12. Yavariabdi, H. Kusetogullari, ”Change Detection in Multispectral Landsat Images Using Multi-Objective Evolutionary Algorithms”, IEEE Geoscience and Remote Sensing Letters, December 2016.
13. Yavariabdi, A. Bartoli, C. Samir, M. Artigues, D. Da Ines, and M. Canis, “Mapping and Characterizing Endometrial Implants by Registering 2D Transvaginal Ultrasound to 3D Pelvic Magnetic Resonance Images”, Journal of Computerized Medical Imaging and Graphics (CMIG), Elsevier, June 2015.
14. Kusetogullari, A. Yavariabdi, and Turgay Celik, “Unsupervised Change detection in Multi-temporal Multi-spectral Satellite Images using Parallel Particle Swarm Optimization”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), May 2015.

Other Journals (Scopus)

1. Demir, E. Uray, O. Orhan, A. Yavariabdi, H. Kusetogullari, “Trend Analysis of Ground-Water Levels and The Effect of Effective Soil Stress Change: The Case Study of Konya Closed Basin”, European Journal of Science and Technology, vol. 24, pp. 515-522, 2021.
2. Yavariabdi, H. Kusetogullari, and H. Cicek, “UAV detection in airborne optic videos using dilated convolutions”, Journal of Optics, 2021.

International Conference Papers

1. A. Kusetogullari, H. Kusetogullari, A. Yavariabdi, J. Eklund, and M. Andersson, “Genetic Algorithm-based Variable Selection Approach for High-Growth Firm Prediction”, IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering, 2022.
2. Ertan, A. Yavariabdi, S. Ezgi Küçükbay, E. Aksoy, A. Emre Tiryaki, and İ. Berk Özalp, “Lead-Acid Battery Lifetime Estimation using Limited Labeled Data for Cellular Base Stations”, IEEE Wireless Telecommunications Symposium, 2022.
3. Ertan, S. Ezgi Küçükbay, A. Yavariabdi, N. Kangöz, A. Emre Tiryaki and İ. Berk Özalp, “Anomaly Detection on Broadband Network Gateway”, IEEE International Black Sea Conference on Communications and Networking, pp. 1-6, 2020.
4. Yavariabdi, H. Kusetogullari, E. Mendi, and B. Karabatak, ”Unsupervised Change Detection using Thin Cloud-Contaminated Landsat Images”, IEEE International Conference on Intelligent Systems, Madeira Island, Portugal, September 2018.
5. F. Demir, A. Cankirli, B. Karabatak, A. Yavariabdi, E. Mendi, and H. Kusetogullari, ” Real-Time Resistor Color Code Recognition using Image Processing in Mobile Devices”, IEEE International Conference on Intelligent Systems, Madeira Island, Portugal, September 2018.
6. Kusetogullari, A. Yavariabdi, ”Self-Adaptive Hybrid PSO-GA Method for Change Detection Under Varying Contrast Conditions on Satellite Images”, IEEE Int. Science and Information Conf. on Computing, pp. 361-368, London, UK, 2016.
7. Yavariabdi, H. Kusetogullari, A. B. Usakli, ”Unsupervised Satellite Change Detection Using Particle Swarm Optimization in Spherical Coordinates”, International Symposium on Engineering, Artificial Intelligence and Applications (ISEAIA), Kyrenia, Cyprus, 2015.
8. Yavariabdi, C. Samir, and C. Hordonneau, “Curves-Driven Smooth Deformation Field for Multimodal TVUS-MR Image Registration”, Proceedings of the Medical Image Understanding and Analysis Conference (MIUA), Lincoln, UK, July 2015.
9. A. Yavariabdi, C. Samir, A. Bartoli, D. Da Ines, and N. Bourdel, “Contour-Based TVUS-MR Image Registration for Mapping Small Endometrial Implants”, Proceedings of the Computational and Clinical Applications in Abdominal Imaging at MICCAI (ABD-MICCAI), Nagoya, Japan, September 2013.
10. Yavariabdi, C. Samir, A. Bartoli, D. Da Ines, and N. Bourdel, “Mapping Endometrial Implants by 2D/2D Registration of TVUS to MR Images from Point Correspondences”, Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), San Francisco, CA, USA, April 2013.
11. Yavariabdi, C. Samir, and A. Bartoli, “3D Medical Image Enhancement based on Wavelet Transforms”, Proceedings of the Medical Image Understanding and Analysis Conference (MIUA), London, UK, July 2011.
12. Kusetogullari, A. Yavariabdi, M. S. Leeson, and E. L. Hines, “Genetic Algorithm Based Rainbow Network Flow Optimization for Multiple Description Coding in Lossy Networks”, Proceedings of the IEEE International Conference on Internet Technology and Secured Transactions (ICITST), London, UK, pp. 1–6, November 2010.