My name is Pavel Senin, welcome to my home page!
I was a PhD student at Collaborative Software Development Laboratory (CSDL) of University of Hawaii at 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 behaviors discovery and ranking from systematic measurement of software process artifacts. I defended my dissertation in January, 2015, and currently looking for a postdoctoral appointment or an industrial R&D position; my short resume is available here.
While finishing the school, I am increasingly involved in the development of spatio-temporal data mining techniques. Recently, we have proposed a novel techniques for time series recurrent patterns discovery and for spatio-temporal anomaly discovery, which are based on symbolic discretization and grammatical inference. My next research project combines my work on recurrent behaviors discovery and spatio-temporal data ming aiming at the recurrent behaviors-based spatio-temporal activity mining.
Currently, I am working as a bioinformatics software engineer at INRA MIA in Toulouse. During my studies I was involved in a number of research projects. In FUNHYMAT, I was responsible for bioinformatics analyses aiming at understanding of structure and function of microbial communities, in 3SR project, I worked on the identification and annotation of SNPs in sheep genome; at ENSAT, I was involved in the identification of genes responsible for fruit ripening; at INRIA Rennes I have designed and implemented a high-throughput sequence classification pipeline for G protein-coupled receptors (GPRs) based on finite state machines. I also worked for LANL, DOE-JGI as a research technologist on NGS sequencing data analysis and genome finishing, and for RCUH, Hawaii on the transgenic papaya genome assembly.