About Me
Hello! I'm Egemen Erbayat, Ph.D. student in Electrical and Computer Engineering at The George Washington University. My academic journey began at Bogazici University in Istanbul, where I earned my Bachelor's degree in Electrical & Electronics Engineering. I am passionate about leveraging technology to solve complex problems and am experienced in finding, analyzing, and discovering insights, as well as formulating and implementing solutions for research problems.
My skill set encompasses a range of programming languages and tools, including Python and C++. Throughout my career, I have gained diverse experience as both a software and machine learning engineer, working across a range of industries, from healthcare to market operations. This includes achievements such as enhancing landmark localization for autonomous robots and optimizing image processing techniques for retail operations. My roles have included positions at Siemens Healthineers, Delivers.ai, Vispera, DASAL, and Baykar Technologies, where I contributed to projects involving computer vision, deep learning, and UAV swarm algorithms.
Currently, my research focuses on AI applications and optimizations in communication systems, where I apply advanced machine learning techniques, computer vision, and optimization algorithms. My work has consistently demonstrated improvements in system accuracy and efficiency.
Publications
- Age of Information Optimization and State Error Analysis for Correlated Multi-Process Multi-Sensor Systems - MobiHoc '24
- PRODIGY+ : a robust progressive upgrade approach for elastic optical networks - J. Opt. Commun. Netw., 2024
- A Trade-off Analysis of Latency, Accuracy, and Energy in Task Offloading Strategies for UAVs - IEEE Cloud Summit, 2024
- Fronthaul Network Architecture and Design For Optically Powered Passive Optical Networks - IEEE ICC, 2024
- ULTRA: Machine Learning Optimized TRA For Enhanced Resource Allocation in MCF-based SDM-EONs - IEEE ANTS, 2023