Kaustubh Patil: Post Doc

I am mainly interested in data analysis and predictive modeling with an emphasis on data driven techniques.

I have moved various fields starting with a bachelors’ degree in Electronics Engineering, a masters’ in Artificial Intelligence and Intelligent Systems and a PhD in Bioinformatics. In this postdoctoral work I am investigating neurological aspects of human behavior and cognition with the help of fMRI. I am working at the crossroads between psychology and computational analysis where I hope to add some value using my previous experience.

Contact: k.patil (at) ucl.ac.uk (email)

Google scholar profile: available here

Publications

Patil, K.R. & McHardy, A.C. (2013) Alignment-free genome tree inference by learning group-specific distance metrics, Genome biology and evolution, 5 (8), 1470-1484.

Patil, K.R., Roune, L. & McHardy, A.C. (2012) The PhyloPythiaS web server for taxonomic assignment of metagenome sequences, PLOSone, 7 (6), e38581.

Patil, K.R., Haider, P., Pope, P.B., Turnbaugh, P.J., Morrison, M., Scheffer, T. & McHardy, A.C. (2011) Taxonomic metagenome sequence assignment with structured output models, Nature Methods, 8 (3), 191-192.

Patil, K.R. & Kulkarni, A., (2008) Kernel-enabled methods for subspace regression and efficient control, International Journal of Modelling, Identification and Control, 5 (2), 136-145.

Vieira, J., Cardoso, C.S., Pinto, J., Patil, K.R., Brazdil, P. Cruz, E., Mascarenhas, C. et al. (2007) A putative gene located at the MHC class I region around the D6S105 marker contributes to the setting of CD8+ T‐lymphocyte numbers in humans, International Journal of Immunogenetics, 34 (5), 359-367.

Patil, K.R. & Brazdil, P. (2007) Text Summarization: using Centrality in the Pathfinder Network, IADIS Int. conference on Applied Computing.

Campos, P., Brazdil, P. & Patil, K.R. (2007) A Multi-Agent dynamic perspective of knowledge transmission in collaboration networks, EAEPE, Porto, Portugal.

Patil, K.R. & Kulkarni, A.J. (2007) A simple visualization technique to understand the system dynamics in bioreactors, Biotechnology Progress, 23 (5), 1101-1105.