Welcome to my home page!

I have graduated from the Collaborative Software Development Laboratory, UH Manoa ICS, where I was 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 (STA) framework -- a general approach for recurrent behavior discovery from systematic measurements of software process and product artifacts. Given a contrast set of measurements (collected from two or more processes) STA leverages the SAX-VSM algorithm and outputs a set of software-process characteristic behaviors for each of the input classes.

At the moment, I am developing algorithms for high-throughput integrative biological data analyses at Los Alamos National Laboratory, where I work as a Research Associate (a postdoctoral researcher). We develop the EDGE Bioinformatics platform. In addition to that, I am extending my dissertation research on recurrent behaviors discovery towards spatio-temporal data mining: recently, we have proposed novel techniques for time series recurrent (i.e., motif) and anomalous (i.e., discord) patterns discovery, which are based on symbolic discretization, grammatical inference, and algorithmic complexity.

Previously, I worked for MIAT INRA on transcriptome annotation refinement, analysis of structure and function of microbial communities, identification of disease-related SNPs, and identification of transcripts and pathways involved in the fruit ripening process. At INRIA, I worked on the olfactory proteins identification. I also worked for DOE-JGI supporting genome finishing effort, pioneering single cell squencing process design, and database development. At RCUH I worked on the first transgenic genome assembly (papaya).

Currently, I am looking for an academic or industrial role allowing me to apply my expertise in research and development, my short resume is available here. Thank you!

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© Pavel Senin — 2005 - 2015. Except where otherwise noted, all original material on this page created by Pavel Senin is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported.