I have completed my M.Tech - Information Technology (with specialization in Bioinformatics)at IIIT-Allahabad. During my course work, I have studied various topics including data mining, database managements System, pattern recognition, cloud computing, parallel computing etc. The course work was highly interdisciplinary and intensive.

Currently, I am working on parallel computing and pattern recognition in my project work. It deals with parallelization of Open Reading Frames (ORFs) that provides protein translation regions.Besides that, I am also focusing on optimizing the code in order to get improve specificity and sensitivity with minimum error rate.In future, I would like to explore the areas related to Big-data in Bio-text Mining, Machine Learning and Pattern Recognition in Biological Systems, Database and Information systems, HPC, Biometrics.

Other than that I have also worked on developing and deploying the cloud computing application. My exposure on cloud computing technology includes SAAS, PAAS, LAAS, Private and public clouds, Google Cloud webpage using PHP on Codenvy.

I have worked on various programming languages and scripts which includes C, Java, Perl, and OpenCL (for parallelization), HTML. I am comfortable on platforms as Linux and Windows for developing the applications. I worked on different variants of Linux as Fedora (17,18,19), Ubuntu (10.10,11.10),CentOS( 6.5), Mageia 3. Currently, I am using Fedora 19 for my project work. Computer science and information technology streams facilitate interdisciplinary work in various domains. I am doing my specialisation in bioinformatics, which happens to be an important and emerging field with high potential of interdisciplinary research potential. Complexity of the problems and size of data in biological domain carves a challenging research field for computer scientists. In the past, algorithms have been developed to solve the problems in bioinformatics and became the generic algorithms to be used in various applications. Genetic algorithm and neural networks are pioneer examples of such algorithms. The problems of bioinformatics can be solved by developing new algorithms or by utilizing the existing algorithms or methods (with some modifications) as Evolutionary (Genetic) Algorithms, Game Theory, RungeKutta Method, Dynamic Programming. Computer science and information technology have potential to enable this field by solving its complex problems which includes gene & protein sequence analysis, drug interaction analysis that are very useful for human kind.

Considering my programming exposure & skills, understanding of bioinformatics domain, I am suitable for doing quality research in this field. I will be fortunate to get a chance for doing the research work in this esteem organization, which will further enhance my capabilities and provide a platform to do quality research in this field.

(Rajkamal Mishra)