Dipankar Basak

@kokrajharuniversity.ac.in

Assistant Professor, Physics
Kokrajhar university

RESEARCH, TEACHING, or OTHER INTERESTS

Nuclear and High Energy Physics
2

Scopus Publications

8

Scholar Citations

2

Scholar h-index

RECENT SCHOLAR PUBLICATIONS

  • Harnessing data-driven methods for precise model-independent event-shape estimation in relativistic heavy-ion collisions
    D Basak, H Hushnud, K Dey
    Journal of Physics G: Nuclear and Particle Physics 53 (1), 015102 , 2026
    2026
    Citations: 1
  • Evidence of partonic collectivity in ultra-relativistic heavy-ion collisions with NCQ scaling of radial flow
    R Agarwala, D Basak, K Dey
    arXiv preprint arXiv:2512.15026 , 2025
    2025
  • Estimating centrality in heavy-ion collisions using Transfer Learning technique
    D Basak, K Dey
    Nuclear Physics A 1057, 123043 , 2025
    2025
    Citations: 2
  • Chapter-18: Leveraging Machine Learning for Accurate Determination of Npart in Heavy-Ion Collision Events
    D Basak
    Multidisciplinary Research: Innovations in Science, Arts, and Commerce 4, 123 , 2025
    2025
  • Estimation of collision centrality in terms of the number of participating nucleons in heavy-ion collisions using deep learning
    D Basak, K Dey
    The European Physical Journal A 59 (7), 174 , 2023
    2023
    Citations: 5
  • Estimation of centrality in heavy-ion collision at√ s= 200 GeV using deep learning
    D Basak, A Basumatary, S Choudhury, R Chouhan, K Dey
    Proceedings of the DAE Symp. on Nucl. Phys 66, 1028 , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • Estimation of collision centrality in terms of the number of participating nucleons in heavy-ion collisions using deep learning
    D Basak, K Dey
    The European Physical Journal A 59 (7), 174 , 2023
    2023
    Citations: 5
  • Estimating centrality in heavy-ion collisions using Transfer Learning technique
    D Basak, K Dey
    Nuclear Physics A 1057, 123043 , 2025
    2025
    Citations: 2
  • Harnessing data-driven methods for precise model-independent event-shape estimation in relativistic heavy-ion collisions
    D Basak, H Hushnud, K Dey
    Journal of Physics G: Nuclear and Particle Physics 53 (1), 015102 , 2026
    2026
    Citations: 1
  • Evidence of partonic collectivity in ultra-relativistic heavy-ion collisions with NCQ scaling of radial flow
    R Agarwala, D Basak, K Dey
    arXiv preprint arXiv:2512.15026 , 2025
    2025
  • Chapter-18: Leveraging Machine Learning for Accurate Determination of Npart in Heavy-Ion Collision Events
    D Basak
    Multidisciplinary Research: Innovations in Science, Arts, and Commerce 4, 123 , 2025
    2025
  • Estimation of centrality in heavy-ion collision at√ s= 200 GeV using deep learning
    D Basak, A Basumatary, S Choudhury, R Chouhan, K Dey
    Proceedings of the DAE Symp. on Nucl. Phys 66, 1028 , 2022
    2022