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- Post-doctoral researcher

- Project manager (H2020-DIGITbrain)

- Bachelor's and Master's thesis supervisor

- Teacher tutor (Mechanical engineering program)

- Teacher and course responsible (Digital manufacturing, Additive manufacturing, Measurement Science and Engineering, and Systems Engineering) 

Fields of expertise

- Additive Manufacturing 

- Metamodeling in product-process development

- University pedagogy 

Top achievements

- Design, develop, and implement of 'additive manufacturing' course for the first time at Tampere University. 

- Collaborating in the development of the DACM framework. 

- Invited speaker to the high-level conference of ‘INFORMS Annual meeting 2019. 

- Honorable approved Ph.D. thesis of ‘Approved with distinction’.

- Invited speaker to Nordic systems engineering (NOSE) conference, Helsinki. 

- Invited speaker to Technology trade fair, Helsinki. 

- Co-organizer of the scientific workshop in the IDETC 2016 conference. 

- Patent: "Self-cooling welding torch (Welding torch using vortex tube technology)"

Main positions of trust

- Teacher tutor at Tampere University for the mechanical engineering program. 

- Reviewer (systems engineering journal, journal of ASTM smart and sustainable manufacturing systems, CIRP CMS 2019 conference, journal of advances in manufacturing) 

Research topics

Additive Manufacturing

Digital Manufacturing

Manufacturing Systems

Smart Manufacturing

Product Development

Systems Engineering


Research unit

Manufacturing Research Group

Selected publications

[1] Mokhtarian, H. (2019). Product-Process Integrated Meta-Modeling Using a Graph-Based Approach: Application to Additive Manufacturing. (Tampere University Dissertations; Vol. 36). Tampere University.

[2] Paris, H., Mokhtarian, H., Coatanéa, E., Museau, M., & Ituarte, I. F. (2016). Comparative environmental impacts of additive and subtractive manufacturing technologies. CIRP Annals, 65(1), 29-32.

[3] Mokhtarian, H., Coatanéa, E., & Paris, H. (2017). Function modeling combined with physics-based reasoning for assessing design options and supporting innovative ideation. AI EDAM, 31(4), 476-500.

[4] Coatanéa, E., Roca, R., Mokhtarian, H., Mokammel, F., & Ikkala, K. (2016). A conceptual modeling and simulation framework for system design. Computing in Science & Engineering, 18(4), 42.

[5] Mokhtarian, H., Coatanéa, E., Paris, H., Mbow, M. M., Pourroy, F., Marin, P. R., ... & Ellman, A. (2018). A conceptual design and modeling framework for integrated additive manufacturing. Journal of Mechanical Design, 140(8), 081101.

[6] Nagarajan, H. P., Mokhtarian, H., Jafarian, H., Dimassi, S., Bakrani-Balani, S., Hamedi, A., ... & Haapala, K. R. (2019). Knowledge-Based Design of Artificial Neural Network Topology for Additive Manufacturing Process Modeling: A New Approach and Case Study for Fused Deposition Modeling. Journal of Mechanical Design, 141(2).

[7] Mokhtarian, H., Hamedi, A., Nagarajan, H., Panicker, S., Coatanea, E., & Haapala, K. (2018). Probabilistic Modelling of Defects in Additive Manufacturing: A Case Study in Powder Bed Fusion Technology. In 52nd CIRP Conference on Manufacturing Systems (pp. 956-961). in 52nd CIRP Conference on Manufacturing Systems.

[8] Nagarajan, H., Panicker, S., Mokhtarian, H., Remy-Lorit, T., Coatanéa, E., Chakraborti, A., Prod’hon, R., Jafarian, H., Haapala, K. (2019). Graph-based Meta-modeling for Characterizing Cold Metal Transfer (CMT) Process Performance. ASTM Journal of Smart and Sustainable Manufacturing Systems.