Shima Hajimirza

Assistant Professor

School: School of Engineering and Science

Department: Mechanical Engineering

Building: Carnegie Laboratory

Room: 203

Phone: (201) 216-5358

Email: shajimi1@stevens.edu

Website

Education
  • PhD (2013) The University of Texas at Austin (Mechanical Engineering)
  • MS (2010) California Institute of Technology (Bioengineering)
  • MS (2009) Southern Illinois University Edwardsville (Mechanical Engineering)
Research

Thermal Fluid Sciences
Artificial Intelligence for Design & Manufacturing
Data-Driven Modeling
Topology Optimization
Micro-Nano Materials Modeling
Energy Conversion at Nano-scale

General Information



Experience




Appointments

Assistant Professor, Sept.2020-PresentStevens Institute of Technology
Department of Mechanical Engineering

Assistant Professor, Jan.2016-August 2020 Texas A&M University
Department of Mechanical Engineering

Assistant Professor, Sep.2014-Sep.2015 California State Polytechnic University, Pomona
Department of Engineering Technology

Professional Societies
  • ASME – American Society of Mechanical Engineers (ASME) Member
Patents and Inventions

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Selected Publications

Selected Publications:

1. Kim Hansol, Mine Kaya, and Shima Hajimirza,” Braodband Solar Distributted Bragg Reflector Design Using Numerical Optimization”, Journal of Solar Energy 221 (2021): 384-392
2. Kaya, Mine, and Shima Hajimirza,” Nonparametric design of nanoparticles with maximum scattering using evolutionary topology optimization”, International Journal of Heat and mass transfer 166(2021): 120738
3. Sharadga, Hussein, Shima Hajimirza, and Robert S. Balog,” Time series forecasting of solar power generation for large-scale photovoltaic plants”, Renewable Energy 150 (2020): 797-807
4. Sharadga, Hussein, Shima Hajimirza, and Elmer PT Cari. "A Fast and Accurate Single-Diode Model for Photovoltaic Design." IEEE Journal of Emerging and Selected Topics in Power Electronics (2020).
5. Kang, Hyun Hee, Mine Kaya, and Shima Hajimirza, “A Data Driven Artificial Neural
Network Model for Predicting Radiative Properties of Metallic Packed Beds”, Journal of Quantitative Spectroscopy and Radiative Transfer 226(2019):66-72