Higher Degree by Research Candidate
School of Computer Science
Faculty of Engineering, Computer and Mathematical Sciences
My PhD is part of the Integrated Mining Consortium, which we deal with real-world problems to improve mining technologies. Currently, humans determine the reclaiming/stacking planning sequence in a mining stockyard by rules of thumb which brings up limited decision support and lower ability to predict unforeseen events.
Therefore, I hope to automate stockpile recovery optimisation in my PhD to improve the quality of output for the end-users and their customers. It will lead to rapid decision making, maximising value and productivity, minimising the operational and capital costs and reducing environmental impacts of the sector.
Year Citation 2020 Mallipeddi, R., Gholaminezhad, I., Saeedi, M., Assimi, H., & Jamali, A. (2020). Robust controller design for systems with probabilistic uncertain parameters using multi-objective genetic programming. Soft Computing.
2019 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.
DOI Scopus4 WoS1
2018 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.
DOI Scopus10 WoS7
2017 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.
DOI Scopus16 WoS11
2017 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.
DOI Scopus8 WoS5
2016 Gholaminezhad, I., Assimi, H., Jamali, A., & Vajari, D. (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.
DOI Scopus11 WoS5
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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