Niluka Bentara Vitanage | Physics | Best Researcher Award

Published on 23/09/202524/09/2025 by Academic Awards

Mrs. Niluka Bentara Vitanage | Physics | Best Researcher Award

National Institute of Fundamental Studies | Sri Lanka

Mrs. Niluka Bentara Vitanage, a dedicated Research Assistant from Sri Lanka, is an emerging scholar with six years of research experience specializing in carbon nanomaterials, molecular dynamics, and sustainable environmental applications. She holds a BSc in Physics, an MPhil in Physical Science, and is currently pursuing her PhD at the University of Sri Jayewardenepura. Her expertise spans advanced synthesis and characterization techniques, including CVD, SEM, XRD, TEM, and XPS, leading to innovations such as a novel single-stage floating catalyst CVD method for high-quality VACNTs. With 27 publications, including journal papers, abstracts, patents, and a book chapter, she has made notable contributions in areas like water desalination, pollutant removal, energy storage, and nanocomposite membranes.

Profile: Google Scholar | ResearchGate

Featured Publications

Wu, Z., Sewwandi, B. V. N., Chen, X., Perera, G., Jayarathna, L., … (2025). Forward osmosis membrane with lightweight functionalised multiwall carbon nanotube nanofillers. Environmental Technology, 46(9), 1507–1518.

Sewwandi, B. V. N., Kumarasinghe, A. R., Wu, Z., Bandara, P., Jayarathne, L., … (2023). Size-tunable graphitized carbon spheres for water defluoridation. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 670, 131582.

Sewwandi, B. V. N., Kumarasinghe, A. R., Tushara, D., Wijesingha, H., … (2021). Fabrication of size-tunable graphitized carbon spheres with hierarchical surface morphology on p-Si (100) by chemical vapour deposition. Sri Lankan Journal of Physics, 22(1), 80–90.

Sewwandi, B. V. N., Kumarasinghe, A. R., Chen, X., Bandara, P., Jayarathna, L., … (2025). A novel fabrication method of vertically aligned carbon nanotubes by single-stage floating catalyst CVD. BMC Chemistry, 19(1), 89.

Wu, Z., Sewwandi, B. V. N., Deegala, H., Kuruppu, K., Chandrasekara, E., … (2025). An integrated centrifugal microfluidic chip for in situ chemical oxygen demand by improving the conventional dichromate method. Chemical Engineering Research and Design. Advance online publication.

Jayasinghe, D. M., Weerathunga, D. T. D., Kumarasinghe, A. R., Manathunga, K. S., Sewwandi, B. V. N., … (2024). Investigation of electrical properties of composite dipped films developed with electrically conductive carbon nanotube (CNT)-natural rubber latex (NRL). Faculty of Science, University of Ruhuna, Matara, Sri Lanka.

Bhishma Karki | Physics | Best Researcher Award

Published on 18/09/202518/09/2025 by Academic Awards

Dr. Bhishma Karki | Physics | Best Researcher Award

Tri-Chandra Multiple Campus | Nepal

Dr. Bhishma Karki is a distinguished physicist and academic leader from Nepal, currently serving as the Executive Chairman of the National Research Council Nepal. He also holds positions as Visiting Professor at the Department of Physics and Research Centre, Tuljaram Chaturchand College, Pune, India, and Visiting Faculty at the Department of Physics, Tri-Chandra Multiple Campus, Tribhuvan University, Kathmandu. Dr. Bhishma Karki earned his B.Sc. in Physics from National Multiple College, M.Sc. in Material Science from the University of Pune, and a Ph.D. in Material Science from Tribhuvan University with a thesis on “Photoelectrocatalytic Purification of Water Using Spray-Deposited Zinc Oxide Thin Films.” With over 57 publications in SCI and Scopus-indexed journals, his research focuses on surface plasmon resonance sensors, photocatalysis, and material science applications in water purification and cancer detection. He has actively participated in numerous international workshops and conferences across Russia, the UK, France, Germany, Italy, and Australia, including UNFCCC and UNCBD conferences. Dr. Bhishma Karki serves as Academic Editor or Editorial Board member for journals like PLOS ONE, Frontiers in Oncology, Scientific Reports, and Wiley’s Journal of Sensors. Recognized with Nepal Vidyabhushan “A” award in 2023, he is a life member of multiple technical societies and actively contributes to community development while promoting scientific research and education in Nepal.

Profile: Google Scholar

Featured Publications

Karki, B., Vasudevan, B., Uniyal, A., Pal, A., & Srivastava, V. (2022). Hemoglobin detection in blood samples using a graphene-based surface plasmon resonance biosensor. Optik, 270, 169947.
Karki, B., Uniyal, A., Pal, A., & Srivastava, V. (2022). Advances in surface plasmon resonance–based biosensor technologies for cancer cell detection. International Journal of Optics, 2022(1), 1476254.
Karki, B., Pal, A., Singh, Y., & Sharma, S. (2022). Sensitivity enhancement of surface plasmon resonance sensor using 2D material barium titanate and black phosphorus over the bimetallic layer of Au, Ag, and Cu. Optics Communications, 508, 127616.
Karki, B., Uniyal, A., Chauhan, B., & Pal, A. (2022). Sensitivity enhancement of a graphene, zinc sulfide-based surface plasmon resonance biosensor with an Ag metal configuration in the visible region. Journal of Computational Electronics, 21(2), 445–452.
Karki, B., Sarkar, P., Dhiman, G., Srivastava, G., & Kumar, M. (2024). Platinum diselenide and graphene-based refractive index sensor for cancer detection. Plasmonics, 19(2), 953–962.

Lorena Aguirre Salazar | Quantum Physics | Best Researcher Award

Published on 06/06/202506/06/2025 by Academic Awards

Dr. Lorena Aguirre Salazar | Quantum Physics | Best Researcher Award

Dr. Lorena Aguirre Salazar, Texas A&M University-Corpus Christi, United States

Dr. Lorena Aguirre Salazar is a passionate mathematician specializing in pattern formation, variational models, and PDEs. She earned her Ph.D. in Mathematics from McMaster University 🇨🇦, with prior studies at Technion 🇮🇱 and Universidad Nacional de Colombia 🇨🇴. Dr. Aguirre has taught at institutions across North and South America, including Texas A&M–Corpus Christi 🇺🇸, and has presented her research globally. She actively promotes equity, inclusion, and belonging in mathematics education 🎓. Her work is published in top journals such as SIAM J. Math. Anal. and BLMS

Publication Profile

Google Scholar

🎓 Educational Background

Dr. Lorena Aguirre Salazar holds a Ph.D. in Mathematics (2016–2021) from McMaster University 🇨🇦, where she researched energy models under the guidance of Drs. Stan Alama and Lia Bronsard. She earned her M.Sc. in Applied Mathematics (2012–2014) at Technion – Israel Institute of Technology 🇮🇱, focusing on semi-linear elliptic systems. She completed her B.Sc. in Mathematics (2009–2011) at Universidad Nacional de Colombia 🇨🇴. In 2010, she attended exchange and summer programs in Chile 🇨🇱 and Brazil 🇧🇷, gaining additional training in Fourier analysis, PDEs, measure theory, and functional analysis.

🔬 Research Interests

Dr. Lorena Aguirre Salazar’s research focuses on pattern formation within the framework of the Calculus of Variations and Partial Differential Equations (PDEs) 🧮. Her work explores the mathematical structures that govern complex physical and biological phenomena. Beyond theoretical mathematics, she is deeply engaged in higher education research, emphasizing community building and a sense of belonging among students in mathematics classrooms 👩‍🏫🤝. She advocates for inclusive teaching practices that foster emotional and social well-being alongside academic growth 🎓💬. Her interdisciplinary approach bridges rigorous analysis with impactful educational methodologies.

🎓 Professional Development

Dr. Lorena Aguirre Salazar has actively pursued diverse professional development initiatives to enhance both her mathematical and educational expertise 🌟. She completed a directed study in 2025 on social and emotional learning in mathematics education 🧠❤️. She was part of the TPSE Leadership Institute (2022–2023), focusing on building community in post-secondary math education 🏫🤝. Dr. Aguirre also earned multiple online specializations and certificates from leading universities on topics such as virtual teaching, diversity, inclusion, accessibility, and mental health support 💻🌍. At McMaster University, she completed several teaching-focused certifications, including Instructional Skills and Learning Foundations

👩‍🏫 Professional Experience

Dr. Lorena Aguirre Salazar has amassed a dynamic teaching and research portfolio across North and South America 🌎. She currently serves as a faculty member at Texas A&M University–Corpus Christi, teaching courses in statistical modeling, calculus, and fundamental mathematics 📊🧮. She has held roles as a part-time instructor at Niagara College (Canada) and Assistant Professor at Lakehead University and Valdosta State University, covering diverse mathematical topics from numerical analysis to vector analysis 🔢📐. Her academic journey includes instructor and teaching assistant roles at McMaster University, as well as prior experience in Colombia at Universidad Nacional and Universidad de Caldas 🇨🇴🎓

🔬 Research Focus

Dr. Lorena Aguirre Salazar’s research lies at the intersection of applied mathematics, particularly in partial differential equations (PDEs) and the calculus of variations 🧮🌀. Her work addresses complex models like the Thomas-Fermi-Dirac-von Weizsäcker (TFDW) theory and Ohta–Kawasaki models, with applications in quantum mechanics and materials science ⚛️🧊. She explores pattern formation, mass splitting phenomena, and energy convergence in physical systems. Her mathematical modeling extends to theoretical physics and functional analysis 🔍📈. Additionally, Dr. Aguirre Salazar is passionate about mathematics education, focusing on community building and inclusion in academic settings

Publication Top Notes

📄 A remark on weakly contractive mappings – Journal of Nonlinear and Convex Analysis, 2015 | Cited by: 33 🔁
📄 Mass splitting in the Thomas–Fermi–Dirac–von Weizsäcker model with background potential – Journal of Mathematical Physics, 2020 | Cited by: 4 🔬
📄 Convergence of the TFDW Energy to the Liquid Drop Model – SIAM Journal on Mathematical Analysis, 2021 | Cited by: 1 📘
📄 An Ohta–Kawasaki model set on the space – Bulletin of the London Mathematical Society, 2024 | Cited by: — 🧩
📄 Solutions and limits of the Thomas-Fermi-Dirac-Von Weizsäcker energy with background potential – Dissertation, 2021 | Cited by: — 🎓

Muhammad Jamshaid Shabbir | Physics | Young Scientist Award

Published on 01/04/202501/04/2025 by Academic Awards

Mr. Muhammad Jamshaid Shabbir | Physics | Young Scientist Award

Mr. Muhammad Jamshaid Shabbir, University of Silesia, Poland

Muhammad Jamshaid Shabbir is a dedicated researcher in physics from Pakistan, with expertise in nanomaterials, energy storage, and condensed matter physics. He completed his MPhil in Physics from the University of the Punjab, Lahore, specializing in structural and magnetic properties of Ca₂Fe₈O₁₄/GO composites. He has worked as a Research Assistant at the University of the Punjab, gaining hands-on experience in spectroscopy, electronics, and experimental physics. His research contributions include publications on graphene-based supercapacitors, MOF advancements, and nano-sized hexagonal ferrites. He has attended multiple international conferences, presenting his findings on advanced materials.

Publication Profile

Scopus

Education 🎓

Muhammad Jamshaid Shabbir holds an MPhil in Physics from the University of the Punjab, Lahore (2021-2023) with a CGPA of 3.43/4.00. His thesis focused on the structural and magnetic properties of Ca₂Fe₈O₁₄/GO composites. Prior to this, he completed an MSc in Physics from Bahauddin Zakariya University, Multan (2019-2021) with a CGPA of 3.25/4.00. During his studies, he developed expertise in spectroscopy, experimental physics, and nanomaterials. His academic journey was marked by exceptional performance, earning him a college merit scholarship. His educational background has provided him with a strong foundation in research methodologies, statistical analysis, and advanced laboratory techniques.

Experience 🏛️

Muhammad Jamshaid Shabbir served as a Research Assistant at the University of the Punjab, where he conducted statistical research in spectroscopy and modern physics. He gained practical experience in digital and analog electronics, chromatography techniques, and thin-film applications. Additionally, he worked as a Physics Lecturer at Unique Academy Lahore (2022-2023), focusing on fundamental physics concepts, scientific attitudes, and career development in science. His laboratory experience includes working with Raman Spectroscopy, XRD, SEM, and AFM, contributing to advanced research in materials science. His dedication to research and education has made a significant impact in the field of physics.

Awards and Honors 🏆

Muhammad Jamshaid Shabbir has been recognized for his academic excellence through multiple awards. He received a Prime Minister’s Laptop under the PM Laptop Scheme for achieving an A grade in MSc Physics. Additionally, he was awarded a College Merit Scholarship for outstanding performance in his intermediate studies. His dedication to academic and research excellence has been consistently acknowledged through institutional and governmental recognitions. His contributions to physics research, particularly in nanomaterials and energy storage, have positioned him as a promising scientist in his field.

Research Focus 🔬

Muhammad Jamshaid Shabbir’s research interests span multiple domains in materials science and energy storage. His primary focus areas include biomass, composite materials, magnetic materials, graphene oxide, supercapacitors, and lithium-ion batteries. His work on graphene-based electrode materials has contributed to the advancement of high-performance supercapacitors. He has also explored MOF advancements for energy applications and the synergetic effects of hexaferrite and reduced graphene oxide (rGO) in photothermal therapy. His research integrates cutting-edge spectroscopic techniques to enhance material efficiency for renewable energy applications. His contributions to condensed matter physics are paving the way for future innovations in energy storage and materials science.

Publication Top Notes

Advances in graphene-based electrode materials for high-performance supercapacitors: A review
Journal of Energy Storage, 2023. Cited by 108.
Exploring new frontiers in supercapacitor electrodes through MOF advancements
Journal of Energy Storage, 2024. Cited by 57.Google Scholar
Sustainable catalysis: Navigating challenges and embracing opportunities for a greener future
Journal of Chemical and Environmental, 2023. Cited by 21.
Evolution of nano-sized hexagonal ferrites suitable as permanent magnets and for high frequency applications
Physica B: Condensed Matter, 2023. Cited by 6.
Synergetic effect of hexaferrite and rGO in photothermal therapy and hyperthermia application
Synthetic Metals, 2024.

Conclusion

Muhammad Jamshaid Shabbir is a strong candidate for the Research for Young Scientist Award. His contributions to materials science, nanotechnology, and energy storage systems align well with the objectives of the award. His research publications, conference participation, and technical expertise demonstrate his potential to make impactful contributions to scientific advancements. Given his achievements and commitment to research, he is highly suitable for this recognition.

Alexander B Konovalov | Physics and Astronomy | Best Researcher Award

Published on 08/08/202408/08/2024 by Academic Awards

Alexander B Konovalov | Physics and Astronomy | Best Researcher Award

Dr Alexander B Konovalov, Russian Federal Nuclear Center – Zababakhin All-Russia Research Institute of Technical Physics, Russia

Based on Dr. Alexander B. Konovalov’s impressive background and achievements, he seems to be a strong candidate for the Research for Best Researcher Award.

Publication profile

Orcid

Education and Qualifications

PhD in Biophysics (2012) from Chernyshevsky Saratov State University, focusing on spatial distributions of breast optical parameters. MSc in Electrical Engineering (1987) from St. Petersburg State University of Aerospace Instrumentation. BSc in Physics (1984) from National Research Nuclear University “MEPhI”. Advanced training in Electrical Engineering and Programming.

Employment History

Leading Scientist (2015-present) at RFNC-VNIITF, Snezhinsk, Russia, focusing on developing models and algorithms for tomography and optical imaging. Senior Researcher (2000-2015) at RFNC-VNIITF, involved in various high-impact projects including proton therapy systems and diffuse optical tomography.

Honors and Grants

Received notable grants and awards, including those from the Russian Federation Ministry of Education and Science, and “Rosatom” State Corporation. Awarded the “Rosatom” Medal “Veteran of Nuclear Power and Industry”.

Professional Activities

Member of prestigious societies such as the Optical Society of America (OSA). Contributed as an editorial board member and reviewer for multiple respected journals.

Research Experience

Developed and led projects in X-ray and diffuse optical tomography, including high-impact research on few-view tomography and molecular imaging.

Selected Publications

Authored numerous influential publications in high-impact journals and books, covering areas such as diffuse optical tomography and image reconstruction algorithms.

Invited Lectures and Conferences

Delivered invited lectures and presented research at numerous international conferences, demonstrating a high level of expertise and recognition in his field.

Conclusion

Dr. Alexander B. Konovalov’s extensive research experience, notable awards, and contributions to the field of biophysics and optical imaging make him a highly suitable candidate for the Best Researcher Award. His work in developing advanced imaging techniques and his impact on both scientific research and practical applications highlight his exceptional qualifications for this honor.

Research focus

Alexander B. Konovalov’s research focuses on advanced imaging techniques, particularly in the context of Monte Carlo simulations and fluorescence molecular tomography. His work includes the development and refinement of image reconstruction algorithms for computed tomography, as well as optimizing sensitivity functions and minimizing view numbers in tomography through deep learning approaches. Konovalov’s studies contribute to improving imaging accuracy and efficiency in medical and scientific applications, such as time-resolved fluorescence molecular tomography. His research integrates computational methods with practical imaging solutions, aiming to enhance diagnostic capabilities and visualization techniques. 📉🔬🧪

Publication top notes

Monte Carlo modeling of temporal point spread functions and sensitivity functions for mesoscopic time-resolved fluorescence molecular tomography

ASYMPTOTIC SOURCE FUNCTION APPROXIMATION BASED FLUORESCENCE MOLECULAR TOMOGRAPHY: CURRENT STATUS AND PROSPECTS

Reconstruction of fluorophore absorption and fluorescence lifetime using early photon mesoscopic fluorescence molecular tomography: a phantom study

Monte Carlo simulation of sensitivity functions for few-view computed tomography of strongly absorbing media

Development of Image Reconstruction Algorithms for Few-View Computed Tomography at RFNC–VNIITF: History, State of the Art, and Prospects

Minimizing the Number of Views in Few-View Computed Tomography: a Deep Learning Approach

Duo Xu | Physics and Astronomy | Best Researcher Award

Published on 08/06/202411/06/2024 by Academic Awards

Duo Xu | Physics and Astronomy | Best Researcher Award

Dr Duo Xu,Department of Astronomy, University of Virginia,United States

Dr. Duo Xu, an Origins Postdoctoral Fellow at the University of Virginia, specializes in star formation, molecular clouds, and machine learning in astrophysics 🌌. With a Ph.D. from the University of Texas at Austin and M.A. from the National Astronomical Observatories, Chinese Academy of Sciences, Dr. Xu’s research focuses on magnetohydrodynamic simulations and synthetic observations to understand stellar feedback and magnetic fields. Their pioneering work combines AI and astronomy, contributing extensively to conferences and prestigious publications. Dr. Xu’s multidisciplinary approach sheds light on the complex dynamics of the universe. 🚀

Publication profile

scopus

Education

Duo Xu holds a Ph.D. from the University of Texas at Austin, where they were advised by Professor Stella Offner. Prior to this, they earned a Master of Arts in Astrophysics from the National Astronomical Observatories, Chinese Academy of Sciences, under the guidance of Professor Di Li. Their academic journey began with a Bachelor of Science in Astronomy from Nanjing University.

Research Experience

Duo Xu’s research experience is extensive and diverse. Their postdoctoral work at the University of Virginia involves applying machine learning techniques to infer physical properties related to molecular clouds, particularly magnetic fields. During their graduate studies, they conducted magnetohydrodynamic simulations, synthesized observations, and applied machine learning algorithms to identify stellar feedback mechanisms. Prior research at Nanjing University and the National Astronomical Observatories, Chinese Academy of Sciences, focused on identifying stellar feedback in observations, analyzing molecular and atomic spectra, and studying the physical and chemical evolution of the interstellar medium.

Awards & Honors

Xu has received numerous awards and honors throughout their academic and professional career, including prestigious fellowships and scholarships such as The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship and the David Alan Benfield Memorial Scholarship in Astronomy.

Professional Experience

Xu has presented their research at various conferences and colloquia worldwide, showcasing their expertise in topics ranging from machine learning applications in astronomy to the physical properties of molecular clouds.

Research focus

Duo Xu’s research focus lies at the captivating intersection of 🌌 astrophysics and 🧠 machine learning. With a keen eye on star formation processes and the dynamics of molecular clouds, Xu employs cutting-edge techniques like magnetohydrodynamic simulations and synthetic observations. Their work delves into unraveling the mysteries of stellar feedback, turbulence, and magnetic fields within these cosmic nurseries. By integrating machine learning into the analysis of astronomical data, Xu pioneers innovative methods to infer physical properties, enhancing our understanding of the intricate mechanisms shaping the cosmos.