My decision to pursue a PhD stems from my passion for science and engineering, coupled with my abilities in the field of machine learning and applied statistics. I consider myself fortunate to be a part of the Department of Computer Science at the University of Florida for my master's studies. Most importantly, I am happy to have two excellent professors in this field, Dr. Pader and Dr. Jilson, as my advisors, who are guiding me throughout my graduate studies. They helped me choose and pursue courses and topics that interested me. During my first semester, I took the Mathematical Methods for Intelligent Systems course which gave me a solid foundation in applied mathematics in the field of intelligent systems. Likewise, the Computational Neuroscience research course gave me insight into the applications of statistics, neural networks, and linear dynamic systems from a biological perspective. My keen interest in the field of applied statistics inspired me to take courses such as machine learning and neural networks. the following semester. In this context, I would like to give a brief overview of my master's research projects, which I find very exciting. The first project was to design a handwriting recognition system capable of classifying 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 (SVM) and Relevance Vector Machines (RVM), using handwritten character data from the postal system. In the first phase, we analyzed the ability to map the features calculated on the input character images to the membership values ​​of different classes using BLR. In the second phase, the c...... middle of paper queries ......ilar which belong to a particular domain. Representing user queries in a machine-readable format will help us create probabilistic models for queries. Additionally, combining queries to solve complex queries will be the next step in question-answering systems. Works cited1. DM Blei, AY Ng and MI Jordan. Latent Dirichlet Allocation, JMLR, 20032. 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. FM Suchanek. Automated construction and growth of a large ontology. Doctoral dissertation, Saarland University, 2009.4. T. Hofmann, SIGIR '99: Proceedings of the 22nd Annual ACM SIGIR International Conference on Research and Development in Information Retrieval (ACM, New York, NY, USA, 1999)