Faculties

Understanding many-body systems through data-driven corroboration is inherently intensive, and the atomic nucleus serves as one of the most compelling examples of such systems. Investigations of nuclei at the limits of stability provide crucial insights into the nature of the nuclear force, which remains one of the least well-understood fundamental interactions. Theoretical efforts in this domain primarily aim to test and validate nuclear models under extreme conditions, thereby examining the assumptions that underlie them. My research focuses on exploring the properties of atomic nuclei under extreme conditions and the associated phase transitions. These studies are of significant interest, as they offer the potential to uncover fundamental aspects of many-body physics. My research interests include nuclear structure theory, with particular emphasis on giant resonances, nuclear fission, thermal pairing, nuclear level densities, and the application of machine learning techniques to nuclear physics.

Nuclear Structure Theory, Artificial Intelligence, Machine Learning, Deep Neural Network.

Hon. Director, Centre for Particle Physics, CUSAT, since August 2025

ANRF-SERB Core Research Grant, in the year 2024

Senate Member, CUSAT, since 2023

Radiological Safety Officer (RSO), CUSAT, since 2022

Assistant Professor, Department of Physics, Cochin University of Science and Technology, Cochin, Kerala, India, since 29 June 2017

DST-INSPIRE Faculty at Department of Physics, National Institute of Technology Karnataka, Surathkal, India from May 2017 to 28 - June, 2017

DST-INSPIRE Faculty Award DST, 2016

Selected for the SERB Indo-US Postdoctoral Fellowship for the year 2016, supported by the Science and Engineering Research Board (SERB) and Indo-US Science and Technology Forum (IUSSTF) (Not availed)

Prof. C. V. K. BABA AWARD for best thesis in Nuclear Physics, Indian Physics Association, 2015

Towards the microscopic understanding of the thermodynamic properties of atomic nuclei, SERB-ANRF, Core Research Grant, 2024 -2027, Total outlay Rs. 28 Lakhs.

Solving Complex Problems Using High Performance Cluster, RUSA 2.0 T3A, CUSAT, Govt. of India, 2023 -2026, Total outlay Rs. 3.24 Crores.

Study of giant dipole resonance in hot and rotating nuclei, DST- INSPIRE, Govt. of India, 2027 -2023, Total outlay Rs. 35 Lakhs.

Tata Institute of Fundamental Research, Mumbai-400005, India

Indian Institute of Technology, Roorkee-247667, India

Bhabha Atomic Research Centre, Mumbai-400085, India

Variable Energy Cyclotron Centre, 1/AF Bidhannagar, Kolkata 700064, India

Inter University Accelerator Centre, New Delhi, India

RIKEN, Japan

Jyothish K., Nuclear Structure Theory, 2019, ongoing, PhD Student

Gokul A., Nuclear Structure Theory, 2020, ongoing, PhD Student

Parvathi V Nair, Nuclear Structure Theory, 2021, ongoing, PhD Student

Asmitha M. R., Nuclear Structure Theory, 2024, ongoing, PhD Student

Niranjana Rojith, 2025, Project Student

Sreelakshmi S., 2025, Project Student

A. Gokul, and A. K. Rhine Kumar; Clustering in hot 28Si; Nucl. Phys. A 1067, 123319 (2026) https://doi.org/10.1016/j.nuclphysa.2025.123319.

V. Parvathi and A. K. Rhine Kumar; Collective enhancement in nuclear level density and shape transitions in 169Tm; Nucl. Phys. A 1067, 123309 (2026). https://doi.org/10.1016/j.nuclphysa.2025.123309

K. Jyothish, Asmitha M. R. and A. K. Rhine Kumar; Nuclear shape transition of Th isotope at fission limits: a fourier shape parametrization approach; Nucl. Phys. A 1067, 123291 (2026). https://doi.org/10.1016/j.nuclphysbps.2023.07.004

K Jyothish, Govardhan Manangode and A. K. Rhine Kumar; Transfer-learning-driven machine-learning model for α-decay half-life predictions; Phys. Rev. C 112, 064309 (2025). https://doi.org/10.1103/67c1-2dvd

K Jyothish, Suryan Sivadas M. S and A. K. Rhine Kumar; Exploring the nuclear landscape using neural network techniques Submission has been accepted for publication in the International Journal of Modern Physics E (IJMPE):IJMPE-D-25-00069R2 (2025). https://doi.org/10.1142/S0218301326500011

K Jyothish, V Parvathi and A. K. Rhine Kumar; Nuclear level density studies using deep neural network techniques; Pramana – Journal of Physics, 99, 53 (2025). https://www.ias.ac.in/article/fulltext/pram/099/0053

V. Ranga, I. Mazumda, S.P. Weppner, S. Panwar, R. Sariyal, S.M. Patel, P.B. Chavan, A. K. Rhine Kumar, G. Anil Kumar; Measurement of proton induced absolute production cross-section of 6.13, 6.92 and 7.12MeV γ-rays from 16O(p,p′γ)16O reaction; J. Phys. G: Nucl. Part. Phys. 51, 045101 (2024). https://iopscience.iop.org/article/10.1088/1361-6471/ad1fd3/pdf

K. Jyothish, M. S. Suryan Sivadas, and A. K. Rhine Kumar; A study on nuclear binding energy and beta decay energy using deep neural networks; Nucl. and Part. Phys. Proce. 336, 17 (2023). https://doi.org/10.1016/j.nuclphysbps.2023.07.004

A. Gokul, C. Ameerali, and A. K. Rhine Kumar; Cluster Radioactivity in Platinum isotopes; Nucl. and Part. Phys. Proce. 336, 22 (2023). https://doi.org/10.1016/j.nuclphysbps.2023.07.006

Abhishek Sharma, P. Arumugam, and A. K. Rhine Kumar; Giant dipole resonance and its fine structures in 144-152Nd, 152Sm studied within the linear response theory; Phys. Scr. 98, 035303 (2023). https://iopscience.iop.org/article/10.1088/1402-4896/acb23f/pdf

IQAC Profile Link: Dr. RHINE KUMAR A. K.

Google Scholar Link: Dr. RHINE KUMAR A. K.