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Ms. R. Indrakumari

Assistant Professor

Ms. R. Indrakumari is an Assistant Professor of Computer Science and Engineering at Galgotias University since 2018. She has been teaching for over 14 years and 4 years of Software Industry experience and has a passion for Computer Programming and Data Analysis. She is an expert in programming languages such as Java, C++, and C, and data analysis tools like Excel, Tableau, and Power BI, and has edited several books on the Subject. She is an active researcher in the field, having published numerous papers and chapters in leading journals and conferences. She is an active member of several professional organizations. She is committed to inspiring students to pursue their dreams and reach their full potential.


She has been teaching for 14 years and have a wealth of experience and expertise in a multitude of areas. She has taught in a variety of settings, including University and Engineering Colleges. She has worked in the industry for over 4 years. She has been responsible for developing and executing strategies, as well as delivering results. She is highly organized and have a proven track record of success. She is well-versed in both the educational and corporate environments.


She is having a Master degree in Computer Science & Information Technology from the Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India. She has also completed additional courses in Data Analysis tools.

Awards & Recognition

Awarded the "The Best Faculty of the Year" by Dr. Pauls Engineering College for the academic 2008 – 2009.

Named "Top Performer" by Tecksphere Company in 2016

Received the "Most Valuable Employee" recognition from Tecksphere Company for the year 2017 and 2018.

Awarded the "Best Researcher" for the years 2019 and 2020 by Galgotias University.


She has published several studies that have advanced the field of research in Data analysis and Heart Disease Prediction. Her research has been published in leading journals, Edited books and conferences, including Elsevier, Springer, Taylor & Francis and IEEE. Her research has focused on topics such as artificial intelligence, machine learning, Data Analysis and Disease Prediction. Her work has made a significant impact in terms of both academic and practical applications. She is striving to continue to push the boundaries of her research with the ultimate goal of making a real-world impact and improving the lives of people.

Area of Interest

She possesses a strong interest in Data Analysis and the application of analytical techniques to make data-driven decisions. Her experience with data-driven decision-making has been demonstrated through her coursework, research papers, and professional experience. She is expertise in Excel, Tableau, and R programming to manipulate and analyse data. She has also worked with data analytics software such as SAS, SPSS, and STATA.