I am a Computer Science PhD student funded by the EPSRC under supervision of Prof. Peter Triantafillou. Before joining Warwick, I was working in a bank as a data scientist for three years.
We try to improve machine learning for systems, and systems for machine learning. Currently, I am working on random sampling over extreme joins which is of interest because the join over huge tables are time consuming. Our aim is to use machine learning to generate uniformly a sample of join results without doing exact join using generative models.
CS258: Databases (Term 1, 2019)
CS909: Data Mining (Term 2, 2020)
- 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.