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I apply machine learning, operations
research, information theory, probabilistic graphical models and other techniques to
solve various problems in the cybersecurity area.
I hold a Ph.D. degree in Computer Science Department from LSU. My advisors were
Prof. Costas
Busch and
Prof. S.S. Iyengar. My work was theoretical in nature, focusing on network design
algorithms and approximation schemes.
My area of research was on buy-at-bulk network design problems. I explored
network design problems applicable to smart-grids, load-balancing in networks, cloud
computing/data center, VLSI design and transportation & logistics. My other areas
of interest are wireless sensor networks, large-scale & reliable distributed
systems/computing, high-availability, game theory and optimization.
These days, I dwell mostly on machine learning using Python for (mostly) cybersecurity related problems.
Occasionally, I venture into relevance and IR. I gravitate naturally to
well-motivated problems where
theoretical challenges abound and those that have immediate practical applications. I
enjoy building proof-of-concepts or working prototypes to most of the problems I work on.
Here is my Ph.D. dissertation presentation
and here is my Ph.D. dissertation itself.
I have written an extended abstract
where I have attempted to explain my research from a practical standpoint. Here is my resume (as of 14-Sep-2023): resume.
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