Dr Ali Ahrari
Lecturer
Doctor of Philosophy in Mechanical Engineering (December 2016), Michigan State University, East Lansing, MI, USA (GPA: 4.00/4)
Master of Science in Mechanical Engineering-Applied Design (September 2009),University of Tehran, Tehran, Iran
Bachelor of Science in Mechanical Engineering-Solid Mechanics (September 2006), University of Tehran, Tehran, Iran
UNSW Canberra
School of Systems & Computing
Dr. Ali Ahrari is a Lecturer at the School of Systems and Computing, University of New South Wales, Canberra, Australia. He received his Ph.D. in mechanical engineering from Michigan State University (MSU) in 2016 and subsequently worked as a professional aide at MSU until June 2018. He has won some international competitions on optimization such as "Competition on niching methods for multimodal optimization" in 2016 and 2020, which was held at CEC and GECCO conferences, as well as an international student competition on structural optimization (ISCSO) in 2017 and 2018. From July 2018 to May 2022, he worked at UNSW-Canberra as a research associate/fellow in the Canberra Evolutionary Optimization group. After 15 months working as a research fellow at the University of Sydney, he returned to UNSW-Canberra in August 2023, working as a lecturer at the School of Systems and Computing.
Dr Ahrari is the recipient of the Australian Research Council Discovery Early Career Researcher Award (ARC-DECRA'2023) for the project "An Efficient Computational Solver for Complex Engineering Problems." His current research focuses on evolutionary algorithms to solve multimodal and multiobjective problems. Dr Ahrari has 28 peer-reviewed publications (25 papers as the first author) in scientific journals including 4 papers in lEEE Transactions on Evolutionary Computation. He is a member of the editorial board of “Applied Soft Computing.”
E-mail
Location
Building 15, Room 1113
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
2023-2016: ARC Discovery Early Career Research Award (DECRA) (Lead Investigator, 329,278 AUD)
2023: NCI adapter scheme (Lead Investigator, 2,200 AUD)
2022:NCI adapter scheme (Chief Investigator, $5,600)
2019-2021: UNSW high-performance computing (HPC) resource allocation scheme (Lead Investigator, $3,718)
2022Winner of the competition on seeking multiple optima in dynamic environments at IEEE CEC’2022
2022 Winner of the competition on dynamic optimization problems generated by generalized moving peaks benchmark at IEEE CEC’2022
2021 Associate Fellow of the Higher Education Academy (AFHEA)
2020Winner of competition on niching methods for multimodal optimisation at (500 USD cash prize from IEEE) and
2018 Winner of competition on structural optimisation (1000 € prize)
2017 Winner of GECCO'2017 competition on multi-modal optimisation
2017 Winner of the competition on structural optimisation among 60+ participants (1000 € prize)
2016 Winner of , competitions on multimodal optimisation
2013-2016 Graduate Office Fellowship (This fellowship was awarded multiple times)
2012 Richard H. Brown – ME Endowment Award
My research focuses on the foundations and applications of computational optimisation, evolutionary computation, and swarm intelligence. I am particularly interested in multi-objective and multi-modal optimisation.
I can supervise enthusiastic HDR students (PhD or Master’s by research) whose research plans overlap with my expertise and background. The University often offers scholarships for highly competitive applicants. Interested applicants are encouraged to contact me with the following information:
- CV + publication list
- Transcripts
- English test score. You can find about the scores here: /english-requirements-policy
- Your research proposal (1-2 pages). Depending on your research interest, it is suggested that you visit EvOpt group website () or MDO lab ().
- Chair of IEEE CIS Task force on Multi-modal Optimization
- Member of the editorial board of Applied Soft Computing (Q1)
- Lead Organiser of the competition on “Benchmarking niching methods for multimodal optimization” at GECCO’2024
- Lead Organiser of the “Competition on dynamic multimodal optimization” at IEEE CEC’2022
- Chair of two special sessions at IEEE CEC’2022 Conference
- Invited member of the IEEE CIS Task Force on multi-modal optimisation (2019-2024)
- Member of the scientific committee of ISCSO student competitions on structural optimisation (2019-now)
My Research Supervision
1 PhD student at SEIT, UNSW-Canberra
My Teaching
Introduction to Programming (tutor and lab demonstrator) (2018, 2019, 2021)
Computational Problem Solving (lab demonstrator) (2024)