Welcome to my home page!
I was a PhD student at CSDL of ICS UH Manoa advised by Professor Philip M Johnson. The focus of my dissertation research was on empirical software process discovery. Working on this, I have proposed, designed, and developed the Software Trajectory Analysis framework -- a general approach for recurrent behavior discovery and ranking from systematic measurements of software artifacts. I defended my dissertation in early 2015, and currently looking for a postdoctoral position; my short resume is available here.
Extending my dissertation research on recurrent behaviors discovery, I am increasingly involved in the development of spatio-temporal data mining techniques. Recently, we have proposed novel techniques for time series recurrent pattern (i.e., motif) discovery and for spatio-temporal anomaly (i.e., discord) discovery, both based on the symbolic discretization and grammatical inference. My next research project combines my work on recurrent behaviors discovery and spatio-temporal data ming aiming at activity classification.
Currently, I am working as a bioinformatics software engineer at MIAT INRA on genomics data mining. Previously, I have worked in a number of research projects. In FUNHYMAT I performed bioinformatics analysis of structure and function of microbial communities, in 3SR I was responsible for the identification and annotation of SNPs in sheep genome; at ENSAT, I was involved in the identification of genes involved in the fruit ripening; at INRIA Rennes I have designed and implemented a high-throughput sequence classification pipeline for G protein-coupled receptors (GPRs) based on the finite state machines. I also worked for LANL, DOE-JGI on NGS sequencing data analysis and genome finishing, and for RCUH, Hawaii on the transgenic papaya genome assembly.
senin [at] hawaii.edu