Australian Institute for Machine Learning - Projects
Faculty of Sciences, Engineering and Technology
I am a PhD researcher at the Australian Institute for Machine Learning (AIML). I work at the intersection of Reinforcement Learning (RL) and robotics. Please see my personal page for more information: https://mahdi-kazemi-m.github.io/
My research is at the intersection of computer vision and machine learning. I'm, particularly, interested in reinforcement learning and the ways it can be utilised to perform goal-oriented decision making tasks.
Awards and Achievements
Date Type Title Institution Name Country Amount 2019 Award Valedictorian of class 2019 The University of Adelaide Australia 2019 Award Govehack 2019 Award Govhack Australia 2019 Award Golden Prize at SAIC VW Logistics Innovation Day Volkswagen China 2019 Scholarship Adelaide Graduate Research Scholarship The University of Adelaide Australia 2018 Scholarship Adelaide Summer Research Scholarship The University of Adelaide Australia 2018 Scholarship Higher Education Scholarship (Honours degree) The University of Adelaide Australia
Language Competency English Can read, write, speak, understand spoken and peer review Persian Can read, write, speak, understand spoken and peer review
Date Institution name Country Title 2018 - 2019 The University of Adelaide Australia Honours Degree of Computer Science (First Class Honours) 2015 Amirkabir University of Technology Iran, Islamic Republic of Bachelor of Electrical Engineering, Electronics
Year Citation 2022 Ghiasi, A., Moghaddam, M. K., Ng, C. T., Sheikh, A. H., & Shi, J. Q. (2022). Damage classification of in-service steel railway bridges using a novel vibration-based convolutional neural network. Engineering Structures, 264, 114474-1-114474-16.
DOI Scopus1 WoS1
Moghaddam, M. K., Abbasnejad, E., Wu, Q., Shi, J., & Hengel, A. V. D. (n.d.). Learning for Visual Navigation by Imagining the Success.
Year Citation 2022 Kazemi Moghaddam, M., Abbasnejad, E., Wu, Q., Qinfeng Shi, J., & Van Den Hengel, A. (2022). ForeSI: Success-Aware Visual Navigation Agent. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2022) (pp. 3401-3410). Waikoloa, Hawaii: IEEE.
2021 Kazemi Moghaddam, M., Wu, Q., Abbasnejad, E., & Shi, J. (2021). Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2021) (pp. 3732-3741). online: IEEE.
DOI Scopus4 WoS3
Moghaddam, M. M. K., Abbasnejad, E., & Shi, J. (n.d.). Follow the Attention: Combining Partial Pose and Object Motion for
Fine-Grained Action Detection.
Master of Data Science Research Project, Semester 1, 2021
Mining Big Data, Semester 1, 2021
Master of Data Science Research Project, Semester 2, 2020
Deep Learning Fundamentals, Semester 2, 2020
Applied Machine Learning, Semester 2, 2020
Date Role Membership Country 2018 - 2019 Member Australian Computer Society Australia
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