Vina (Mina) Rahimian

Vina (Mina) Rahimian, holds a Ph.D. in Architecture from the Penn State where her research efforts lie in the intersection of computational design and sustainability. She’s a design technologist interested in technological and data-driven responses for solving wider sustainability-related issues in the built environment.

Rahimian earned her M.S. in Architecture and a graduate certification in applied statistics from Penn State. She holds a B.Arch. from the University of Tehran (Iran).

Rahimian previously served as a visiting researcher at the University of Lisbon in Portugal. She also worked as a generative design researcher at Autodesk in San Francisco and as the director of generative design at iBUILT in New York City.

Rahimian is currently working full time as a senior product manager at Outer Labs where she manages the development of several design automation and database management applications.

• B.Arch., University of Tehran (2008-2013)
• Master of Science in Architecture, Penn State (2013-2015)
• PhD in Architecture, Penn State (2015-2021)
• Graduate Certification in Applied Statistics, Penn State (2017-2018)

• Programming for Artists and Designers
• Intro to Sustainability

• Erasmus+ Scholarship for Studying Abroad

• Link Energy Foundation, Honorable Mention

• Alma Heinz & August Pohland Graduate Fellowship, Awarded for Ph.D. Academic Excellence

• Alma Heinz & August Pohland Graduate Fellowship, Awarded for Master's Academic Excellence

• Generative Design Workflows with Dynamo and Project Refinery, Tutor. Workshop by Autodesk at eCAADe SIGraDI 2019 - University of Porto, Portugal 2019.
• Generative Design Workflows with Dynamo and Project Refinery, Tutor. Workshop by Autodesk at ACADIA 2019 - University of Texas at Austin.

• (In Press as of September 2021) Rahimian, M., Duarte, J. P., Iulo, L. D. (2021). A Realtime Predictive Software Prototype for Simulating Urban Scale Energy Consumption Based on Surrogate Models, Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM).
• Rahimian, M., Cervone, G., Duarte, J.P., Iulo, L.D., (2020), A Machine Learning Approach for Mining the Multidimensional Impact of Urban Form on Community Scale Energy Consumption in Cities. in Design Computing and Cognition 2020 (DCC'20), (pp. 627-646).
• Rahimian, M., J. Beirao., J.P. Duarte., L.D. Iulo. (2019) A Generative Urban Design Tool Considering Topographic Constraints: The Case of American Urban Planning. Proceedings of eCAADe+SIGraDi’19.
• Rahimian, M., Iulo, L.D., Duarte, J.P.,(2018). A Review of Predictive Software for the Design of Community Microgrids. (pp. 1-13). Hindawi Journal of Engineering.
• Rahimian, M., Iulo, L.D., (2017). A Feedback Delivery System for Communal Energy Consumption Practices, Springer Lecture Notes in Computer Science and Artificial Intelligence (Invited paper submission).
• Rahimian, M., Cardoso Llach, D., & Iulo, L. D. (2015). Participatory Energy Management in Building Networks. Sustainable Human-Building Ecosystems (pp. 27-35). Pittsburgh: American Society of Civil Engineers.
• Rahimian, M., Iulo, L. D., & Cardoso Llach, D. (2015). The Case for Collaborative Energy Sharing Network for Small-Scale Community Microgrids. Architecture and Resilience on the Human Scale (pp. 200 - 193). Sheffield: The University of Sheffield.
• Iulo, L. D., Kimel, A., Fadaei, S., Macht, K., Rahimian, M., & Riley, D. (2014). Innovate, Evaluate, Learn: The Importance of Iterative Research in Housing Design-Build. 2014 ACSA Fall Conference: Working out - Thinking while Building. Halifax: ACSA Press.

• Research Gate
• www.vinarahimian.xyz