Research output per year
Research output per year
Personal profile
Curriculum vitae
Dr Younsi has strong research interest in heterogeneous parallel programming applied to genomics. His background is in Machine Learning and software engineering. His recent research area is software developement for reference free variant calling coloured de Bruijn graphs and developing fast and efficient algorithms for bioinformatics using graphs. He is investigating the software development of a heterogeneous parallel variants calling software using sequence alignment in multiple-genome graphs for both short and long reads.
Education/Academic qualification
Machine Learning, PhD, University of East Anglia
Award Date: 1 Apr 2011
Fields of Science
- 113 Computer and information sciences
- Machine Learning
- Bioinformatics, Systems biology
- Parallel and Distributed Systems
- Heterogeneous Programming in C and C++.
-
Ensembles of random sphere cover classifiers
Younsi, R. & Bagnall, A., Jan 2016, In: Pattern Recognition. 49, p. 213-225 13 p.Research output: Contribution to journal › Article › Scientific › peer-review
-
Using 2k+2 bubble searches to find single nucleotide polymorphisms in k-mer graphs
Younsi, R. & MacLean, D., 1 Mar 2015, In: Bioinformatics. 31, 5, p. 642-646 5 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access -
An efficient randomised sphere cover classifier
Younsi, R. & Bagnall, A., 1 Jan 2012, In: International Journal of Data Mining, Modelling and Management (IJDMMM). 4, 2, p. 156-171 16 p.Research output: Contribution to journal › Article › Scientific › peer-review
-
A Randomized Sphere Cover Classifier
Younsi, R. & Bagnall, A., 2010, INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2010. Fyfe, C., Tino, P., Charles, D., GarciaOsorio, C. & Yin, HJ. (eds.). Springer-Verlag, p. 234-241 8 p. (Lecture Notes in Computer Science; vol. 6283).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
-
A New Artificial Immune System Algorithm for Clustering
Younsi, R. & Wang, W., 2004, Intelligent Data Engineering and Automated Learning - IDEAL 2004: 5th International Conference Exeter, UK, August 2004, Proceedings. Yang, Z. R., Everson, R. & Yin, H. (eds.). Berlin: Springer-Verlag, p. 58-64 7 p. (Lecture Notes in Computer Science; vol. 3177).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review