Dr Hirad Assimi
Grant Funded Researcher A
School of Electrical and Mechanical Engineering
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
I believe "if we want to make progress fast, we can do it alone; If we want to go far, we have to do it together". I am a multidisciplinary design engineer with the goal of increasing value and productivity while lowering operational costs and saving the planet. I have a diverse technical background and a passion for blending academic knowledge into real-world complex optimisation problems to conduct research with impact and facilitate collaboration between academic research and industrial applications.
My PhD was part of the Integrated Mining Consortium, in which we dealt with real-world problems to improve mining technologies and solve a common problem in stockpile management. I am currently a researcher at the Mine Operational Vehicles Electrification (MOVE) project funded by the Future Battery Industries Cooperative Research Centre (FBICRC) and led by the University of Adelaide. Our project provides the Australian mining industry with a suite of decision-making tools and guidelines that will aid their transition towards battery-supported vehicles and associated stationary machinery in their mining operations.
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Appointments
Date Position Institution name 2021 - ongoing Grant Funded Researcher University of Adelaide -
Language Competencies
Language Competency English Can read, write, speak, understand spoken and peer review Persian Can read, write, speak, understand spoken and peer review -
Research Interests
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Journals
Year Citation 2024 Assimi, H., Hashemian Ataabadi, S. N., Islam, S. M. M., Soong, W. L., & Pourmousavi, S. A. (2024). Toward Underground Mobile Fleet Electrification: Three essential steps to make a real change. IEEE Electrification Magazine, 12(1), 16-26.
Scopus12021 Mallipeddi, R., Gholaminezhad, I., Saeedi, M. S., Assimi, H., & Jamali, A. (2021). Robust controller design for systems with probabilistic uncertain parameters using multi-objective genetic programming. Soft Computing, 25(1), 233-249.
Scopus2 WoS22019 Assimi, H., Jamali, A., & Nariman-zadeh, N. (2019). Multi-objective sizing and topology optimization of truss structures using genetic programming based on a new adaptive mutant operator. Neural Computing and Applications, 31(10), 5729-5749.
Scopus20 WoS122018 Assimi, H., & Jamali, A. (2018). A hybrid algorithm coupling genetic programming and Nelder–Mead for topology and size optimization of trusses with static and dynamic constraints. Expert Systems with Applications, 95, 127-141.
Scopus41 WoS262017 Assimi, H., Jamali, A., & Nariman-zadeh, N. (2017). Sizing and topology optimization of truss structures using genetic programming. Swarm and Evolutionary Computation, 37, 90-103.
Scopus56 WoS362017 Gholaminezhad, I., Jamali, A., & Assimi, H. (2017). Multi-objective reliability-based robust design optimization of robot gripper mechanism with probabilistically uncertain parameters. Neural Computing and Applications, 28(S1), 659-670.
Scopus19 WoS152016 Gholaminezhad, I., Assimi, H., Jamali, A., & Vajari, D. A. (2016). Uncertainty quantification and robust modeling of selective laser melting process using stochastic multi-objective approach. International Journal of Advanced Manufacturing Technology, 86(5-8), 1425-1441.
Scopus23 WoS11 -
Book Chapters
Year Citation 2020 Khayyam, H., Jamali, A., Assimi, H., & Jazar, R. N. (2020). Genetic Programming Approaches in Design and Optimization of Mechanical Engineering Applications. In R. N. Jazar, & L. Dai (Eds.), Nonlinear Approaches in Engineering Applications: Automotive Applications of Engineering Problems (pp. 367-402). Cham, Switzerland: Springer International Publishing.
DOI Scopus10
Hans-Jürgen and Marianne Ohff Research Grant at University of Adelaide (2019)
Teaching assistant for Grand Challenges (2020, Semester 2)
Teaching assistant for Grand Challenges (2019, Semester 2)
Teaching assistant for Evolutionary Computation (2018, Semester 2)
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2024 Co-Supervisor Explainable, Transparent and Trustworthy Data-Driven, Modelling of Underground Electric Mining Trucks Doctor of Philosophy Doctorate Full Time Miss Tamsa . 2023 Co-Supervisor Optimal Energy Storage and Infrastructure Design and Operation for Mining's Electrified Mobile Fleet Doctor of Philosophy Doctorate Full Time Mr Behnam Hashemian Ataabadi
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External Profiles