I am a research scientist in the Computer Science and Mathematics Division at Oak Ridge National Laboratory . I received Ph.D. and M.S. degrees in Informatics from the School of Informatics, Computing, and Engineering at Indiana University Bloomington . Previously, I received M.S. and B.S. degrees in Electrical Engineering at Pontificia Universidad Javeriana in Colombia. I am the recipient of best paper awards at the 9th International Workshop on Managing Insider Security Threats (MIST) 2017 in conjuntion w
My research lies at the intersection of data science, network science, and cybersecurity. In particular, I use data-driven and computational methods to discover and understand anomalous behavior in large-scale networked systems. I rely on this approach to design and develop innovative solutions to address these. Applications of my research range across multiple disciplines, including, the detection of exceptional events in social media, Internet route hijacking, insider threat behavior in version control sy
By leveraging these contribution graphs, our research shows the potential of using graph-based ML to improve Just-In-Time (JIT) defect prediction. We hypothesize that features extracted from the contribution graphs may be better predictors of defect-prone changes than intrinsic features derived from software characteristics. We corroborate our hypothesis using graph-based ML for classifying edges that represent defect-prone changes. This new framing of the JIT defect prediction problem leads to remarkably b