Personal Statement

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My decision to pursue a PhD is derived from my passion for science and engineering paired with my abilities in the field of machine learning and applied statistics. I consider myself fortunate to be part of the Department of Computer Science, University of Florida for my master studies. More importantly, I am glad to have two excellent professors in this field as advisors, Dr. Pader and Dr. Jilson, who are guiding me throughout my graduate studies. They assisted me to decide and pursue the courses and topics that interested me. During my first semester, I took the course Mathematical methods for Intelligent Systems that gave me a strong base for applied mathematics in the field of intelligent systems. Similarly, the research course Computational Neuroscience gave me an insight into applications of statistics, neural networks, and linear dynamical systems in a biological perspective. My keen interest towards the field of applied statistics, inspired me to take courses such as Machine learning and Neural Networks in the subsequent semester. In this context, I would like to give a brief outline of my master’s research projects, which are I found to be very exciting. The first project was to design a Handwritten Recognition system capable of classifying the digits using the Multilayer Perceptron architecture. Another project was a comparative study of machine learning methodologies such as Bayesian Linear Regression (BLR), Support Vector Machines (SVMs), and Relevance Vector Machines (RVMs), using handwritten character data from postal system. In the first phase, we analyzed the capability of mapping the features calculated on the input character images to membership values in different classes using BLR. In the second phase, the c... ... middle of paper ... ...ilar queries that belong to a particular domain. Representing user queries in a machine-readable format will help us building probabilistic models for queries. Moreover, combining queries to solve complex queries will be next milestone in question answering systems. Works Cited 1. D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent Dirichlet Allocation, JMLR, 2003 2. C. Bizer, J. Lehmann, G. Kobilarov, S. Auer, C. Becker, R. Cyganiak, and S. Hellmann. Dbpedia – a crystallization point for the web of data. Web Semantics: Science, Services and Agents on the WWW, September 2009. 3. F. M. Suchanek. Automated Construction and Growth of a Large Ontology. PhD thesis, Saarland University, 2009. 4. T. Hofmann, SIGIR '99: Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval (ACM, New York, NY, USA, 1999)

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