Objective: To achieve professional satisfaction, career progression and personal development by working in a learning environment that encourages growth and enriches my experience. Research Interests: Data Mining, Machine Learning, Pattern Recognition, Evolutionary Algorithms and Multi-objective Optimization

Graduate Teaching Assistant @ Spatio-temporal Data Mining, Advisor Dr. Ramez Elmasri From June 2012 to Present (3 years 7 months) Research Intern @ From 2015 to 2015 (less than a year) Data Science Intern (Summer 2014) @ Worked on the project titled "Optimal Session Strategy". In this project the metrics for optimal user session on StumbleUpon were proposed and evaluated. Further, ranking based methods (i.e., (AdaRank)) were also tried and evaluated on user session data to find out the relevance of the users sessions to their interests. From June 2014 to August 2014 (3 months) Graduate Teaching Assistant @ I was working in SMILE (Sensory Motor Intelligence Lab). From August 2011 to May 2012 (10 months) Research Associate @ Data Mining Tasks in Visualization From January 2011 to July 2011 (7 months) Senior Lecturer @ I am working as a Senior Lecturer in JUIT for almost one year. My subjects of interest are Data Mining, Pattern Recognition, Machine Learning and Evolutionary Computation. I am presently teaching Information Retrieval and Data Mining. From January 2009 to December 2010 (2 years) System Analyst @ Have worked in the following areas / projects: Algorithmic Trading: Algorithmic trading tries to identify possible "windows of opportunities" automatically, using algorithms, for performing stock trading. These windows of opportunities are determined by predictions from the historical data. In this vast domain, the problem of identifying the similarities between the companies stock was pursued. The results of the project were communicated for publication in the form of the following articles. Practical Inter-stock Dependency Indicator using Time Series and Derivatives. Identifying Stock Similarity Based on Episode Distances. Identifying Stock Similarity Based on Multi-event Episodes. Multi-objective optimization in Cognitive Radio: Cognitive radio (CR) has recently emerged as an efficient spectrum utilizing techniques in wireless communication. The intelligence of CR lies in learning the environment and selecting the best resources to support the user needs. In order to support the best possible combination of the resources to the user, an optimization algorithm is needed for selection. In this work we studied the optimization procedure based on genetic algorithms (GA) to make an intelligent CR system. GA is an evolutionary algorithm that mimics the biological evolutionary phenomena. The optimization problem of CR was encoded as chromosomes in GA and was solved using a multi-objective GA. Collaboration with IISc: In this collaboration with Dr. Chiranjeeb Bhattacharya, the feasibility of Ordinal regression concept, in the applications involving survival data is being carried out. The survival data involves the statistical analysis of the time to even data. The prediction in the survival data is a challenging task due to the presence of censored data samples. An SVM based ordinal regression concept is being used with the novel approach to address censorship. From July 2007 to October 2008 (1 year 4 months) Senior Research Fellow @ The work involved design and analysis of the evolutionary algorithms for multi-objective optimization. I worked on the genetic algorithms and swarm optimization techniques. The results were published in the internal conferences and journals. From September 2005 to July 2007 (1 year 11 months) Machine Intelligence Unit @ Design and Application of Multi-objective Evolutionary algorithms for Pattern From September 2003 to July 2007 (3 years 11 months)

Bachelor of Technology (B.Tech; B, Computer Engineering @ Institution From 2011 to 2016 Doctor of Philosophy (Ph.D.), Computer Science @ The University of Texas at Arlington From 2011 to 2016 Master of Science (M.S, Computer Science and Technology @ Jawaharlal Nehru University New From 2000 to 2002 B. Tech, Computer Engineering @ Govind Ballabh Pant University of Agriculture and Technology From 1975 to 1999 M. Tech, 2002; Computer Science and Technology @ Jawaharlal Nehru University, Delhi Praveen Tripathi is skilled in: Machine Learning, C, Data Mining, Wireless, Pattern Recognition, Algorithms, HTML, Matlab, Statistics, C++, Programming, Linux, Information Retrieval, Optimizations, Research