About
Dr
Mehran Bahramyan
Postdoctoral Researcher
DCU
Mehran Bahramyan, a Postdoctoral Researcher at I-Form, is at the forefront of advancing additive manufacturing through his expertise in modelling and simulation. With a recent PhD completion with I-Form at Dublin City University in 2023, Mehran's research focused on nano scale simulation, particularly directional solidification and deformation mechanisms in metallic alloys. His academic journey, from an undergraduate degree in information and communication technology engineering to an MSc in materials science and engineering, equipped him with programming and machine learning skills for computational materials science area. At I-Form since 2019, Mehran has delved into high-performance alloys, employing molecular dynamics simulations and machine learning for innovative alloy design. He also spearheads research in 3D printing and selective laser melting, utilizing multi-scale modelling to optimize part properties.
Research Interests (Lay Summary)
Mehran is passionate about the intersection of cutting-edge technology and industrial innovation, particularly in the realm of Industry 4.0. His research and professional endeavours are driven by a keen interest in leveraging advanced computational modelling and simulation techniques and artificial intelligence to propel the manufacturing industry into the era of smart factories and digital transformation.
Technical Summary
His research aims to focus on materials design and selection by integrating machine learning techniques to guide the choice and development of materials, enhancing the quality of the end product while considering sustainability metrics. Moreover, He plans to focus on quality control measures in additively manufactured metallic systems by employing a different approach utilizing machine learning methodologies. His scope encompasses diverse areas, including defect detection and classification using advanced ML models for predictive modelling and quality assurance, aiming to address and mitigate potential flaws in the manufacturing process. Additionally, he plans to delve into process monitoring and optimization, harnessing ML algorithms to ensure real-time adjustments for optimal printing parameters, thereby enhancing the consistency and quality of the final product.