The Computational Engineering and Data Science Research Laboratory (CEDS Lab) is an interdisciplinary research center established in late 2025 with the aim of generating innovative solutions to today's complex scientific and engineering problems.
Uniting the rigor of mathematical theory, the predictive power of statistical analysis, and the high-performance computing capabilities of computer engineering under one roof, CEDS Lab focuses on data-driven decision-making processes, optimization, and intelligent systems.
CEDS Lab was brought to life by three founding directors—academics from three distinct fields: Prof. Dr. Murat Alper (Statistics and Industrial Engineering), Assoc. Prof. Dr. İrem Küçükoğlu (Mathematics), and Asst. Prof. Dr. Gürkan Çelik (Computer Engineering). Born from the synergy of these departments, our laboratory is grounded in the globally recognized, modern "multidisciplinary ecosystem" approach. The aim is to build a research culture where theoretical models do not merely remain on paper but are trained using real-world data and transformed into industrial and societal benefits.
CEDS Lab is designed as a dynamic and flexible "umbrella laboratory." Specialized sub-research groups operate within the lab to allow for an in-depth focus on specific problem areas. This structure enables researchers from diverse fields of expertise to share a common infrastructure and undertake large-scale projects.
Our Vision
To become a leading center of excellence recognized as a benchmark at both national and international levels that shapes the future of industry, smart cities, and complex systems through algorithms and computational models developed at the intersection of mathematics, statistics, and computer engineering.
Our Mission
As CEDS Lab, our core mission is to produce publications that advance the national and international scientific literature; to conduct funded projects supported by organizations such as TÜBİTAK, Horizon Europe, and EIT; and to train the next generation of experts in data science and computational engineering all by utilizing big data analytics, artificial intelligence, and computational modeling techniques.