Dr. Eda Nur Saruhan: Researcher at Koç University, Turkey
Eda Nur Saruhan is a dedicated researcher with a strong interdisciplinary background, combining mechatronic engineering principles with artificial intelligence to innovate in the fields of environmental science and health. She is currently a PhD candidate at Koç University’s Computer Science and Engineering department, where her work focuses on the application of machine learning and data science techniques to solve complex biomechanical and environmental challenges. Eda is passionate about leveraging AI to create sustainable and impactful solutions, bridging engineering and public health domains.
Online Profiles
As of now, Eda Nur Saruhan has received a total of 24 citations, reflecting the growing impact of her research in the scientific community. She holds an h-index of 2, indicating that at least two of her publications have been cited at least twice, and an i10-index of 2, representing two papers that have received ten or more citations. These metrics demonstrate her contributions to interdisciplinary research at the intersection of artificial intelligence, health, and environmental science.
Education
Eda completed her Bachelor’s degree in Mechatronic Engineering at Yıldız Technical University, graduating in June 2021 with a solid foundation in robotics, control systems, and automation. Currently, she is pursuing her PhD in Computer Science and Engineering at Koç University, where she focuses on integrating AI with environmental and biomedical applications. Additionally, she has enhanced her expertise through the prestigious UNDP SDG AI Lab Data Science Fellowship, which emphasizes data-driven solutions aligned with sustainable development goals.
Research Focus
Her research explores the intersection of artificial intelligence, environmental science, and health, aiming to develop novel AI-based models for forecasting environmental phenomena and analyzing complex biomechanical systems. She investigates scalable AI approaches for air quality prediction, 3D fiber orientation mapping in cardiac tissues, and optical flow methods for fluid dynamics, with an overarching goal of contributing to public health and sustainable environmental monitoring.
Experience
Eda has been a researcher at Koç University for three years, where she has been involved in multiple interdisciplinary projects. Her experience spans AI-driven air quality modeling, microrobot motion analysis, and advanced imaging techniques. Throughout her career, she has collaborated with experts across engineering and biomedical fields, authored several high-impact publications, and presented findings at international conferences, demonstrating strong project leadership and scientific communication skills.
Research Timeline & Activities
Since 2019, Eda’s research trajectory has included working on cutting-edge projects at Koç University involving fluid dynamics measurement using optical flow methods, microrobot control under laminar flow, and AI-based cell classification techniques. She has actively contributed to conferences such as the International Symposium on Flow Visualization and the Manipulation, Automation, and Robotics at Small Scales conference. Her work has progressively advanced from foundational experimental studies to the application of machine learning models in environmental health contexts.
Awards & Honors
Eda’s contributions to research have been recognized with the UNDP SDG AI Lab Data Science Fellowship, highlighting her commitment to sustainable and impactful AI solutions. She has also co-authored influential papers published in reputed journals like IEEE/ASME Transactions on Mechatronics and Cardiovascular Engineering and Technology, reflecting the quality and relevance of her research output.
Recent Publication
One of her notable recent publications is “Scalable AI-Driven Air Quality Forecasting and Classification for Public Health Applications,” published in Discover Atmosphere. This work presents innovative machine learning frameworks designed to provide accurate and scalable air quality forecasts, which are critical for public health decision-making and environmental policy planning. The paper exemplifies her commitment to applying AI for real-world societal benefits.
-
S. Donmazov, E.N. Saruhan, K. Pekkan, S. Piskin
Review of Machine Learning Techniques in Soft Tissue Biomechanics and Biomaterials
Cardiovascular Engineering and Technology, 15(5), pp. 522–549, 2024.
Citations: 12 -
A.A. Demircali, R. Varol, G. Aydemir, E.N. Saruhan, K. Erkan, H. Uvet
Longitudinal Motion Modeling and Experimental Verification of a Microrobot Subject to Liquid Laminar Flow
IEEE/ASME Transactions on Mechatronics, 26(6), pp. 2956–2966, 2021.
Citations: 12 -
E.N. Saruhan, H. Ozturk, D. Kul, B. Sevgin, M.N. Coban, K. Pekkan
Learning-Enhanced 3D Fiber Orientation Mapping in Thick Cardiac Tissues
Biomedical Optics Express, 16(8), pp. 3315–3336, 2025. -
M. Serdar, E.N. Saruhan, K. Pekkan
Enhancing Particle Image Velocimetry with RAFT and Optical Flow for High-Fidelity Cardiovascular Flow Measurements
Proceedings of the 21st International Symposium on Flow Visualization (ISFV21), 2025. -
E.N. Saruhan, M. Serdar, K. Pekkan
Optical Flow Methods for High-Resolution OCT Analysis of Complex Hemodynamics
21st International Symposium on Flow Visualization (ISFV21), 2025. -
T. Duruöz, A. Madayen, E.N. Saruhan, R.H. Zarnaghi, H.H. Gezer, I. Aktas, et al.
ABS0156 AI-Based Classification of Spondyloarthritides Using the Turkish Patients of ASAS perSpA Dataset: Insights on Clinical Features and Patient Outcomes
Annals of the Rheumatic Diseases, 84, pp. 2108–2109, 2025.