Ali is a third-year PhD student in Computer Science, funded by the EPSRC under supervision of prof. Peter Triantafillou. He started his PhD research on examining the machine learning techniques on data systems, especially in big data environment.
Ali tries to improve machine learning techniques for data systems and vice versa. Currently, he is working on random sampling over extra large joins which is of interest because the join over huge tables are expensive in terms of running time, space and money.
Teaching Assistant in modules:
- CS258: Databases (Term 1, 2019)
- CS909: Data Mining (Term 2, 2020)
- CS258: Databases (Term1, 2020)
- CS909 Data Mining (Term 2, 2021)
- A.M. Shanghooshabad, M.S. Shekelyan, M. Kurmanji, Q. Ma, M. Almasi and P. Triantafillou. “PGMJoins: Random Join Sampling with Graphical Models”. To appear in ACM SIGMOD 2021.
- A.M. Shanghooshabad, "XLJoins". To appear in ACM SRC SIGMOD 2021.
- Q. Ma, A.M. Shanghooshabad, M. Kurmanji, M. Almasi, and P. Triantafillou. “Learned Approximate Query Processing: Make it Light, Accurate and Fast”. In Proceedings of CIDR 2021
- Ali Mohammadi, Mohammad Saniee Abadeh, and Hamidreza Keshavarz. "Breast cancer detection using a multi-objective binary krill herd algorithm". In 2014 21th Iranian Conference on Biomedical Engineering (ICBME), pages 128–133. IEEE, 2014.
- Ali Mohammadi Shanghooshabad and Mohammad Saniee Abadeh. "Sifter: an approach for robust fuzzy rule set discovery". Soft Computing, 20(8):3303– 3319, 2016
- Ali Mohammadi Shanghooshabad and Mohammad Saniee Abadeh. "Robust medical data mining using a clustering and swarm-based framework". International Journal of Data Mining and Bioinformatics, 14(1):22–39, 2016.
- Ali Mohammadi Shanghooshabad and Mohammad Saniee Abadeh. "Robust, interpretable and high quality fuzzy rule discovery using krill herd algorithm". Journal of Intelligent & Fuzzy Systems, 30(3):1601–1612, 2016.
- Mohammad Mahdi Motevali, Ali Mohammadi Shanghooshabad, Reza Zohouri Aram, and Hamidreza Keshavarz. "Who: A new evolutionary algorithm bio-inspired by wildebeests with a case study on bank customer segmentation". International Journal of Pattern Recognition and Artificial Intelligence, 33(05):1959017, 2019
- Alireza Hekmatinia, Ali Mohammadi Shanghooshabad, Mohammad Mahdi Motevali, and Mehrdad Almasi. "Tuning parameters via a new rapid, accurate and parameter-less method using meta-learning". International Journal of Data Mining, Modelling and Management, 11(4):366–390, 2019.