Dr. Atangana Likéné André Aimé | High Energy Physics | Best Researcher Award

Dr. Atangana Likéné André Aimé | High Energy Physics | Best Researcher Award

Post-Doctoral Researcher | University of Geneva | Switzerland

Dr. Atangana Likéné André Aimé is a distinguished researcher in High Energy Physics with expertise spanning Nuclear Physics, Particle Physics, and Radiation Protection. His academic background, marked by advanced degrees in Physics, reflects a strong foundation in theoretical and applied High Energy Physics. Professionally, he has served as a Research Officer at the Research Center of Nuclear Science and Technology, a Lecturer at the University of Yaoundé I, and a Post-Doctoral Researcher affiliated with the ATLAS Experiment at CERN, contributing to global advancements in High Energy Physics. His research interests include Quantum Chromodynamics, quark confinement, nuclear decay, and the application of machine learning to High Energy Physics phenomena. Dr. Atangana’s excellence in research has earned him notable honors, including the Best Researcher Award in High Energy Physics, academic scholarships, and leadership roles in scientific collaborations. His skills encompass symbolic computation, scientific programming, and Monte Carlo simulations, all pivotal in modern High Energy Physics modeling and analysis. With an active presence in international conferences and publications across prestigious journals like Nuclear Physics A, European Physical Journal C, and Modern Physics Letters A, he continues to advance High Energy Physics through innovative theoretical frameworks and computational methods. His dedication to advancing knowledge and mentoring the next generation of scientists underscores his professional integrity and global recognition. Scopus profile of 37 Citations, 24 Documents, 3 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Ahmadou, K., Atangana Likéné, A., Mbida Mbembe, S., Ema’a Ema’a, J. M., Ele Abiama, P., & Ben-Bolie, G. H. (2025). Unveiling nuclear energy excitations and staggering effect in the γ-band of the isotope chain 180−196Pt. International Journal of Modern Physics E.

2. Atangana Likéné, A. A., Ndjana Nkoulou, J. E. II, Oumar Bobbo, M., & Saidou. (2025). Analytical solutions of the 222Rn radon diffusion-advection equation through soil using Atangana–Baleanu time fractional derivative. Indian Journal of Physics.

3. Nga Ongodo, D., Atangana Likéné, A. A., Ema’a Ema’a, J. M., Ele Abiama, P., & Ben-Bolie, G. H. (2025). Effect of spin-spin interaction and fractional order on heavy pentaquark masses under topological defect space-times. The European Physical Journal C.

4. Nga Ongodo, D., Atangana Likéné, A. A., Zarma, A., Ema’a Ema’a, J. M., Ele Abiama, P., & Ben-Bolie, G. H. (2025). Hyperbolic tangent form of sextic potential in Bohr Hamiltonian: Analytical approach via extended Nikiforov–Uvarov and Heun equations. International Journal of Modern Physics E.

5. Atangana Likéné, A. A., Ndjana Nkoulou, J. E. II, & Saidou. (2025). Angular momentum dependence of nuclear decay of radon isotopes by emission of 14C nuclei and branching ratio relative to α-decay. The European Physical Journal Plus.

Dr. Abouzar Bahari | Nuclear Physics | Best Researcher Award

Dr. Abouzar Bahari | Nuclear Physics | Best Researcher Award

CEO | Bahari Research and Development | Oman

Dr. Abouzar Bahari is a distinguished scholar and researcher whose academic and professional journey reflects a deep commitment to Nuclear Physics, with a Ph.D. in Nuclear Physics from Payame-Noor University, alongside advanced studies in Genetics, Petroleum Engineering, and Mining Engineering, enabling him to bridge multidisciplinary fields through innovative research. His career includes leadership as CEO and Founder of Bahari Research and Development in Muscat, Oman, invited lectureships at Ferdowsi University of Mashhad, and extensive engineering experience in oil and gas production, all while advancing Nuclear Physics research through Monte Carlo simulations, particle radiation modeling, relativity, zero-point field analysis, and electromagnetic field applications in health sciences. His Nuclear Physics dissertation on predicting rock and fault failure has been recognized with prestigious awards, including a Best Researcher Award, and his consistent ranking among top graduates further validates his expertise. As a prolific contributor to scientific journals, reviewer, and editorial board member, Dr. Bahari has authored impactful works on earthquake precursors, neutron interactions, and Nuclear Physics-based simulations. His research interests span physics, cancer therapy with ultra-low frequency fields, and interdisciplinary applications of Nuclear Physics in geology, health, and energy systems. With advanced computational and simulation skills in MCNPX, MATLAB, Python, and visualization software, he combines technical mastery with scientific creativity. Overall, Dr. Bahari exemplifies how Nuclear Physics can integrate with diverse domains to generate solutions with global impact, and his career stands as a model of excellence in research, innovation, and education.

Profiles: Google Scholar | ORCID

Featured Publications

1. Bahari, A., & Seyed, A. B. (2007, April). Trust-region approach to find constants of Bourgoyne and Young penetration rate model in Khangiran Iranian gas field (SPE-107520-MS). SPE Latin America and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina. Society of Petroleum Engineers.

2. Bahari, A., & Baradaran Seyed, A. (2009). Drilling cost optimization in a hydrocarbon field by combination of comparative and mathematical methods. Petroleum Science, 6(4), 451–463.

3. Moradi, H., Bahari, M. H., Sistani, M. B. N., & Bahari, A. (2010). Drilling rate prediction using an innovative soft computing approach. Scientific Research and Essays, 5(13), 1583–1588.

4. Bahari, M. H., Bahari, A., Moharrami, F. N., & Sistani, M. B. (2008). Determining Bourgoyne and Young model coefficients using genetic algorithm to predict drilling rate. Journal of Applied Sciences, 8(17), 3050–3054.

5. Hassan, B. M., Aboozar, B., & Hamidreza, M. (2011). Intelligent drilling rate predictor. International Journal of Innovative Computing, Information and Control, 7(4), 1425–1436.