Dr. Nitesh Kumar Adichwal is a dedicated educator with a profound passion for fostering academic excellence and inspiring students. With a Ph.D. in Statistics from Banaras Hindu University, he possesses a strong academic foundation and specializes in sampling theory, survey sampling, and applied demography. Recognized for his commitment to excellence, Dr. Adichwal has been awarded prestigious fellowships, including the RET Exempted fellowship for his Ph.D. and a Government of India Fellowship for his M.Sc. Proficient in essential tools such as MS Office, SPSS, STATA, LaTeX, and R, he seamlessly integrates technology into his teaching and research, creating an engaging learning environment for his students while continually seeking opportunities for professional growth and innovation.
Dr. Adichwal’s tenure as an Associate Professor and Associate Dean (Accreditation & Ranking) at IILM University, Greater Noida, showcased his leadership prowess in academic governance and quality assurance. He led initiatives aimed at improving teaching-learning processes, curriculum design, and student assessment methodologies. His engaging persona and approachable nature made him an effective mentor for both faculty and students.
At the University of Petroleum and Energy Studies (UPES), Dehradun, Dr. Adichwal served as a Cluster Head in the School of Business. He excelled in various roles, including Criteria Champion for NAAC, Course Coordinator for BBA and MBA programs, and Program Lead in the Emergent Cluster. Dr. Adichwal’s expertise in business mathematics, research methodology, and statistics enriched the learning experience for students across bachelor’s and master’s programs.
Research Contributions and Academic Publications:
Dr. Adichwal is a prolific researcher with numerous publications in esteemed journals. His research focuses on statistical estimation methods, population studies, and survey sampling techniques. Noteworthy contributions include the development of novel estimators for population variance and mean, utilizing auxiliary variables and advanced statistical software.