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NIIT UNIVERSITY

Dr Raju Bhakta

  • Assistant Professor
  • Mathematics and Basic Sciences
Prof Raju Bhakta for web

Dr Raju Bhakta is with the Mathematics and Basic Sciences Area at NIIT University. Born and raised in West Bengal, Dr Raju Bhakta has steadily cultivated a distinguished trajectory in the mathematical sciences. His academic journey commenced with a Bachelor’s degree in Mathematics from Prabhat Kumar College, Contai, where he first displayed a flair for rigorous problem-solving. He advanced to Vidyasagar University, Paschim Medinipur, earning an MSc in Applied Mathematics while honing a particular interest in the interface between pure theory and real-world application.

Recognising the importance of pedagogy, Dr Bhakta completed a two-year Bachelor of Education, equipping himself with structured instructional techniques. Parallel to his formal studies, he pursued a year-long certification in Office Automation & Internet Technologies—later extended to advanced networking, C++, Java and web-based database systems—thereby acquiring computational fluency that now undergirds his research and classroom practice.

Twice qualifying the highly competitive UGC-NET-JRF examination in Mathematical Sciences, Dr Bhakta embarked on doctoral research at the National Institute of Technology Rourkela. As a Senior Research Fellow under Prof Suchandan Kayal, he investigated order statistics and their diverse applications, culminating in the 2024 thesis – Various Ordering Results between Two Finite Mixtures Arising from Some Families of Distributions. His scholarship has yielded ten peer-reviewed articles in UGC-CARE-listed international journals of repute, alongside five additional manuscripts at various stages of revision and review—evidence of sustained research momentum.

Complementing his scholarly output, Dr. Bhakta accrued hands-on teaching experience as an Assistant Professor of Mathematics at Midnapore City College, West Bengal, where he was lauded for lucid exposition and empathetic mentorship during a one-year tenure. His instruction bridges abstract theory with illustrative, technology-assisted examples, fostering both conceptual clarity and analytical agility among learners. He has had the privilege of gaining valuable postdoctoral research experience at the Indian Institute of Technology Roorkee, where he was involved in meaningful and impactful mathematical research.

Known for punctuality, self-motivation and a resolutely positive outlook, Dr Bhakta approaches challenges with equanimity, viewing both success and setback as catalysts for growth. He values collaboration yet retains an independent intellectual spirit—qualities that align with NIIT University’s ethos of innovation, interdisciplinarity and societal relevance. At NU, Dr Bhakta seeks to amplify the university’s research footprint while inspiring the next generation of quantitative thinkers. His long-term vision is to ascend to a position of academic leadership, generating impactful scholarship and uplifting the communities he serves.

Qualification

  • PhD (Statistics)
  • MSc (Applied Mathematics)
  • BSc (Mathematics)

Experience

  • Total – 7+ years
  • Research – 5+ Years
  • Teaching – 2+ Years

Courses Taught

  • Probability and Statistics
  • Stochastic Processes
  • Linear Algebra
  • Data Science
  • Graph Theory
  • Mathematical Modelling & Simulation
  • Machine Learning
  • AI & Deep Learning
  • Data Structure
  • Algorithmic Game Theory

Research Area(s)

  • Mathematical Statistics, Applied Probability, Order Statistics, Reliability Theory, Stochastic Orders, Stochastic Processes

Consulting Area

  • Order Statistics and Reliability Theory: Expertise in stochastic ordering, statistical inference, and reliability modelling, applicable to risk assessment, quality control, and system reliability analysis.
  • Applied Probability and Statistical Modelling: Development and analysis of probabilistic models for real-world systems, including data-driven decision-making, uncertainty quantification, and statistical quality assurance.
  • Mathematical Computing and Algorithm Development: Proficient in using computational tools (C++, MATLAB, Python) for solving complex mathematical problems, simulations, and algorithmic implementation.

Selected Publications

  • Kayal, S., Bhakta, R. and Balakrishnan, N. (2023). Some results on stochastic comparisons of two finite mixture models with general components, Stochastic Models, 39(2), 363-382.
    DOI: https://doi.org/10.1080/15326349.2022.2107666
  • Bhakta, R., Majumder, P., Kayal, S. and Balakrishnan, N. (2024). Stochastic comparisons of two finite mixtures of general family of distributions, Metrika, 87, 681-712.
    DOI: https://doi.org/10.1007/s00184-023-00930-4
  • Bhakta, R., Balakrishnan, N., Kayal, S. and Pradhan, S. (2024). Stochastic comparison results between two finite mixture models with generalized Weibull distributed components, Statistics, 58(3), 552-575.
    DOI: https://doi.org/10.1080/02331888.2024.2347343
  • Bhakta, R., Kayal, S. and Balakrishnan, N. (2024). Ordering results between two multiple-outlier finite δ-mixtures, Statistics and Probability Letters, 213, 110193.
    DOI: https://doi.org/10.1016/j.spl.2024.110193
  • Bhakta, R., Kayal, S. and Finkelstein, M. (2024). Stochastic comparisons for finite mixtures from location-scale family of distributions, Methodology and Computing in Applied Probability, 26(4), 1-33.
    DOI: https://doi.org/10.1007/s11009-024-10121-x

Publications

Research Papers
  • Bhakta, R. and Kayal, S. (2025). Stochastic comparisons between two finite α-mixture models with general distributed components, Metrika, 1-17.
    DOI: https://doi.org/10.1007/s00184-025-00996-2
  • Bhakta, R., Balakrishnan, N., Kayal, S. and Pradhan, S. (2024). Stochastic comparison results between two finite mixture models with generalized Weibull distributed components, Statistics, 58(3), 552-575.
    DOI: https://doi.org/10.1080/02331888.2024.2347343
  • Bhakta, R., Kayal, S. and Finkelstein, M. (2024). Stochastic comparisons for finite mixtures from location-scale family of distributions, Methodology and Computing in Applied Probability, 26(4), 1-33.
    DOI: https://doi.org/10.1007/s11009-024-10121-x
  • Bhakta, R., Kayal, S. and Balakrishnan, N. (2024). Ordering results between two multiple-outlier finite δ-mixtures, Statistics and Probability Letters, 213, 110193.
    DOI: https://doi.org/10.1016/j.spl.2024.110193
  • Bhakta, R., Majumder, P., Kayal, S. and Balakrishnan, N. (2024). Stochastic comparisons of two finite mixtures of general family of distributions, Metrika, 87, 681-712.
    DOI: https://doi.org/10.1007/s00184-023-00930-4
  • Kayal, S., Bhakta, R. and Balakrishnan, N. (2023). Some results on stochastic comparisons of two finite mixture models with general components, Stochastic Models, 39(2), 363-382.
    DOI: https://doi.org/10.1080/15326349.2022.2107666
  • Kayal, S., Patra, L. K., Bhakta, R. and Nadarajah, S. (2023). Ordering results for order statistics from heterogeneous log-logistic distributions, American Journal of Mathematical and Management Sciences, 42(1), 51-68.
    DOI: https://doi.org/10.1080/01966324.2021.2019148
  • Bhakta, R., Kundu, P., Kayal, S. and Alizadeh, M. (2024). Stochastic orderings between two finite mixtures with inverted-Kumaraswamy distributed components, Mathematics, 12(6), 852.
    DOI: https://doi.org/10.3390/math12060852
  • Bhakta, R. and Kayal, S. (2024). Stochastic comparisons for series and parallel systems with heterogeneous power-Lomax component lifetimes, Mathematical Methods of Statistics, 33(4), 409-419.
    DOI: https://doi.org/10.3103/S1066530724700212

Awards & Recognition

  • UGC-NET JRF

Professional Activities & Achievements

  • Poster Presentation - R. Bhakta, Stochastic comparisons between two finite mixture models with exponentiated location-scale components (Poster), IISA-2022, Dept. of Mathematics, IISc Bengaluru, Dec 26–30, 2022.
  • Paper Presentation - R. Bhakta, Stochastic comparisons of series and parallel systems with heterogeneous power-Lomax components (Paper), AMSE-2022, Centre for Data Science (ITER), SOA University, Bhubaneswar, Mar 24–26, 2022.
  • Paper Presentation - R. Bhakta, Stochastic comparisons between two finite mixture models with exponentiated location-scale components, National Conference on “Statistics and its Applications”, Dept. of Statistics & IQAC, Dr. G. D. Mahavidyalaya, Sangola (MS), July 6, 2023.
  • Conference Attended - 1st International Conference on Applied Analysis, Computation and Mathematical Modelling in Engineering (AACMME-2021), Dept. of Mathematics, NIT Rourkela, Feb 24–26, 2021.
  • Workshop Attended - Advanced Statistics and Applied Sciences (ASAS-2022), Dept. of Statistics & Ramanujan Centre, Ramanujan College, University of Delhi, UGC-sponsored, Mar 30–31, 2022.
  • Short Term Training Program (STTP) - Emerging Applications of Mathematics and Statistics in Engineering Science and Technology (EAMSEST-2022), Dept. of Mathematics, NIT Rourkela, May 9–15, 2022.
  • AICTE-sponsored one-week STTP - MATLAB – Statistics and Data Science, Dept. of Applied Science, Sagar Institute of Research and Technology, Bhopal, July 27 – Aug 1, 2020.
  • Six-day Faculty Development Programme - Applications of Mathematics in Engineering, Dept. of Mathematics, KPR Institute of Engineering and Technology, Coimbatore, July 20–25, 2020.
  • Offline Short-Term Course - Current Topics in Cyber Security, sponsored by MeitY, Govt. of India, organized by Dept. of CSE & Continuing Education Centre, IIT Roorkee, Dec 13–17, 2024.
  • Two-day National Workshop - An Enrichment Workshop on Algebra & Analysis, Dept. of Mathematics, Pingla Thana Mahavidyalaya, funded by NBHM, DAE, Govt. of India, Oct 30–31, 2018.

Other Interests

  • Singing, Reading, Playing cricket & badminton, Travelling, Listening to Music

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