Saeed Mouloodi
Mechanical Engineer - High Pressurized Electrochemical Cell & Stack Design and Simulation @Jupiter Ionics
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WORK HISTORY
Mechanical Engineer - High Pressurized Electrochemical Cell & Stack Design and Simulation @Jupiter Ionics
Design and manufacture electrochemical cells and stacks working at elevated pressures (>15bar).* Detailed engineering design and optimization of critical components affecting cell/staskperformance, cost and durability.*Create and maintain top-level assembly models, individual part drawings, assemblydrawings and bills of materials.* Innovation in using artificial intelligence and machine learning in green ammonia production, renewable energies, and mechanical design & manufacturing.* FEA, CFD, DFMEA, PFMEA, 3D printing* Mentoring junior engineers and PhD students.
EDUCATION
University of Melbourne
Doctor of Philosophy (PhD), Mechanical & Biomedical Engineering
University of Tabriz
Bachelor of Science - BS, Mechanical Engineering | Fluid Mechanics
Amirkabir University of Technology - Tehran Polytechnic
Master of Science (M.Sc.), Mechanical Engineering | Solid Mechanics
ABOUT SAEED MOULOODI
Dr. Saeed Mouloodi completed his PhD at The University of Melbourne (20••••20), followed by M.Eng.(2013) and B.Eng.(2011) in Mechanical Engineering. He is currently a research assistant and mechanical and biomedical design support at Department of Mechanical Engineering, The University of Melbourne. His PhD thesis includes six published scholarly journals and seven international refereed conference presentations. Saeed\'s PhD thesis was nominated to receive the Chancellor’s Prize for Excellence in 2021. He published a textbook on \"Engineering Mechanics, Statics\" in 2019. Saeed is a passionate mechanical design engineer, author and researcher highly motivated in employing innovative techniques (machine learning and artificial neural networks, CAD & FEA) to find solutions to engineering problems concerning materials modeling, design, and structural optimization. His research is mainly focused on assessing and comprehending mechanical responses of complicated engineering structures that exhibit peculiar nonlinear properties, covering disciplines such as BioMechanics, Biomedical Engineering, Metamaterials, NanoMechanics, and Solid Mechanics of Structures and Composites. To enrich our comprehension of such complex structures belonging to interdisciplinary domains, proper employment of novel techniques is required: optimization algorithms, artificial neural networks (ANN), machine learning algorithms, finite element analysis (FEA), computer-aided design (CAD), and intelligent FEA besides deep understanding of constitutive models.
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