Bilkent Üniversitesi
Makine Mühendisliği Bölümü
ORÇUN KORAY ÇELEBİ
Dr. Öğretim Üyesi
Adres
Department of Mechanical Engineering Bilkent University 06800 Bilkent, Ankara
Ofis
EA112
Telefon
+90 (312) 290-3427
E-Posta
ÖZ GEÇMİŞ
Orcun Koray Celebi joined BilMech as an Assistant Professor in September 2024. He received his B.S. degree in Mechanical Engineering from Bogazici University in 2018. Afterward, he entered the direct Ph.D. program in the Mechanical Science and Engineering Department at the University of Illinois Urbana-Champaign (UIUC). Dr. Celebi obtained his Ph.D. degree in Mechanical Engineering in 2024 and continued as a Postdoctoral Research Associate at UIUC until joining BilMech.
His research focuses on computational & theoretical modeling of plastic deformation mechanics in metallic materials (including pure metals, alloys, and high entropy alloys) utilizing quantum mechanics-based simulation methods (e.g. Density Functional Theory), atomistic simulation tools (e.g. Molecular Dynamics), and Machine Learning approaches.
AKADEMİK TECRÜBE
For more information, visit Dr. Celebi's Google Scholar Profile.
EĞİTİM
Ph.D., Mechanical Engineering, University of Illinois Urbana-Champaign (2024)
B.S., Mechanical Engineering, Boğaziçi University (2018)
ARAŞTIRMA
Dr. Celebi leads the Atomistic Mechanics & Materials Modeling Laboratory (A3ML). A3ML is dedicated to advancing the understanding of the structure, mechanics, and deformation physics of materials across scales, from the quantum level to the mesoscale. In pursuit of this objective, the research efforts are directed towards:
Development of predictive models that will guide the design of high-performance materials,
Multiscale modeling of plastic deformation mechanics in metallic materials (including metals, alloys, and high entropy alloys),
First-principles modeling of crystal defects, including point, line, and interface defects (e.g., vacancies, dislocations, twins, grain boundaries).
A3ML employs a range of computational techniques, including quantum mechanics-based simulations (e.g., Density Functional Theory), atomistic methods (e.g., Molecular Dynamics), and Machine Learning approaches to tackle these research efforts.