معرفی
O. Burak Ozdoganlar is a Professor in the Departments of Mechanical Engineering and Biomedical Engineering at Carnegie Mellon University. His research focuses on multiscale (meso/micro/nano) manufacturing science, combining theoretical, numerical, and experimental analyses to advance three-dimensional device fabrication. He leads the Multiscale Manufacturing and Dynamics Laboratory (MMDL), with applications spanning medical, biomedical, energy, robotics, and aerospace fields.
- B.S., Istanbul Technical University, Turkey
- M.S., Ohio State University, Columbus
- Ph.D., University of Michigan, Ann Arbor
- Post-doc, University of Illinois at Urbana-Champaign
- Senior Member of Technical Staff, Sandia National Labs
His work addresses mechanics of micro-scale material removal, dynamics of micro-scale structures, novel micro/nano-manufacturing techniques, and application-driven research. Key contributions include scalable fabrication of microneedle arrays, freeform 3D ice printing for vascular networks, and high-density soft-matter electronics. His research emphasizes predictability and precision in manufacturing processes.
Recent publications highlight advancements in dissolvable microneedle arrays for transdermal delivery, freeform 3D printing of ice structures for biomimetic vascularization, and scalable methods for porous and soft-matter electronics. His work bridges fundamental mechanics with medical device innovation.
- Blackall Machine Tool and Gage Award, ASME, 2011
- Russell V. Trader Career Faculty Fellow, CMU, 2009-2011
- NSF CAREER award, 2006
- Kuo K. Wang Outstanding Young Engineer, SME, 2007
- Organizer, 'Manufacturing...The Future' symposium, NAE EU-American Frontiers Conference, 2011
- Best paper award, NAMRI SME, 2007-2008
- Struminger Teaching Fellow, CMU, 2007-2008
Ozdoganlar's Multiscale Manufacturing and Dynamics Laboratory (MMDL) develops cutting-edge manufacturing solutions for biomedical applications, including neural probes, cartilage implants, and biosensors. His research integrates mechanics, materials science, and process engineering to address challenges in device predictability and scalability.
