Mihaela Vlasea

Assistant Professor, Mechanical and Mechatronics Engineering, Associate Director and Board Member

Contact Information

Phone: 519-888-4567 x48329
Location: EC4 1011

Assistant Professor | Mechanical and Mechatronics Engineering, Faculty of Engineering

Research Co-Director | Multi-Scale Additive Manufacturing Lab

Dr. Vlasea is an Assistant Professor and the Research Co-Director of the Multi-Scale Additive Manufacturing Lab. Her research focuses on innovative design, process optimization and adoption of new materials for powder bed fusion and binder jetting additive manufacturing processes. Dr. Vlasea collaborates closely with industry partners in the additive manufacturing supply chain and applications, including aerospace. In recognition of her scholarly work, student mentorship, and industry outreach, she was recognised as the Society of Manufacturing Engineers (SME) 20 Most Influential Academics 2021 and as the SME Outstanding Young Manufacturing Engineer 2020.

Dr. Vlasea aims to facilitate the training of graduate students by linking advanced interdisciplinary academic research with targeted industry project exposure. Interdisciplinary academic training enables HQP to gain deep competencies spanning foundational theory behind additive manufacturing processes, modeling, simulation, material science, statistical and data science, sensors and instrumentation, mechatronics, automation, and machine learning approaches. Direct industry involvement/exposure enables student leadership growth, nurtures professional communication, new career and technology transfer opportunities in the biomedical, aerospace, aviation, automotive, transportation and mining sectors.

Selected Publications:

  • Ertay DS*, Naiel AM**, Vlasea M, Fieguth P. (2021) Process performance evaluation and classification via in-situ melt pool monitoring in directed energy deposition. CIRP Journal of Manufacturing Science and Technology. 35: 298-31
  • Ertay DS*, Kamyab S*, Vlasea M, Azimifar Z, Ma T**, Rogalsky AD**, Fieguth P. (2021) Towards Sub-Surface Pore Prediction Capabilities for Laser Powder Bed Fusion Using Data Science. ASME Journal of Manufacturing Science and Engineering.
  • Patel S*, Rogalsky A**, Vlasea M. (2020) Towards Understanding Side-Skin Surface Characteristics in Laser Powder Bed Fusion. Journal of Materials Research.