Rong Wang | Artificial Intelligence | Best Researcher Award

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Mrs. Rong Wang | Artificial Intelligence | Best Researcher Award

Postdoc | University of Tuebingen | Germany

Mrs. Rong Wang is a postdoctoral researcher at the Eberhard Karls University of Tübingen, Germany, specializing in computational linguistics and the evaluation and optimization of large language models (LLMs). She holds an M.Sc. in Computational Linguistics (NLP) from the University of Stuttgart (Grade: 1.7, 2024) and a Ph.D. in Digital Humanities from Zhejiang University, China (2016). Her interdisciplinary academic background bridges computer science, linguistics, and AI-driven humanities research, reflecting her ability to apply quantitative and symbolic methods to linguistic and cognitive studies. Professionally, she has served as a Postdoctoral Fellow at the University of Tübingen, AI Engineer at Telus International Digital AI, AGI Engineer Intern at Deepseek AI, Data Scientist at DEKRA GmbH, and Assistant Professor of Linguistics at Hangzhou Dianzi University. Her research focuses on language model evaluation metrics, neural-symbolic reasoning, multimodal semantics, and automated linguistic assessment. She has contributed to projects on enhancing spatial reasoning in LLMs, multi-agent AI systems, and personality recognition models, alongside authoring several publications on machine learning applications in cognitive linguistics and NLP evaluation. Technically proficient in Python, R, JavaScript, and SQL, she is experienced with frameworks such as LangChain, Autogen, Hugging Face, and PyTorch, and cloud platforms including Azure ML and AWS SageMaker. Her certifications include Azure Certified Data Scientist Associate and AWS Certified AI Practitioner. Mrs. Wang is fluent in English, German, and Chinese, with working knowledge of Japanese, and is recognized for her strong teamwork, communication, and leadership abilities. Her recent works have appeared in Data Intelligence, Psychology Methods, and TMLR, demonstrating her innovative contributions to the AI and NLP research community. (0 Citations ; 2 Documents ; 0 h-index.)

Profiles: Scopus | ResearchGate

Featured Publications

Wang, R., Sun, K., & Kuhn, J. (2024, Dec). Dspy-based neural-symbolic pipeline to enhance spatial reasoning in LLMs [Preprint]. arXiv. https://arxiv.org/abs/2411.18564

Wang, R., Sun, K., & Kuhn, J. (2024, Nov). A pipeline of neural-symbolic integration to enhance spatial reasoning in large language models [Preprint]. arXiv. https://arxiv.org/abs/2411.18564

Sun, K., & Wang, R. (2024, Oct). The roles of contextual semantic relevance metrics in human visual processing [Preprint]. arXiv. https://arxiv.org/abs/2410.09921

Wang, R., & Sun, K. (2024, Jul). A novel dependency framework for enhancing discourse data analysis [Preprint]. arXiv. https://arxiv.org/abs/2407.12473

Wang, R., & Sun, K. (2024, Jun). Continuous output personality detection models via mixed strategy training [Article]. arXiv. https://arxiv.org/abs/2406.16223

Ekadashi Rajni | Biomedical Sciences | Best Researcher Award

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Dr. Ekadashi Rajni | Biomedical Sciences | Best Researcher Award

Professor | Mahatma Gandhi Medical College & Hospital | India

Dr. E. Rajni Sabharwal, MD in Microbiology, is a leading researcher in clinical microbiology, antimicrobial resistance (AMR), and infection control. Her research focuses on emerging multidrug-resistant and extensively drug-resistant organisms, epidemiology of hospital-acquired infections, and antimicrobial susceptibility patterns in critical clinical settings, including urinary tract and bloodstream infections. She actively contributes to national multicentric studies on AMR surveillance and the implementation of antimicrobial and diagnostic stewardship programs, integrating One Health approaches. Dr. Sabharwal’s work encompasses molecular characterization of pathogens, synergy testing of novel antibiotic combinations, biofilm studies, and evaluation of rapid diagnostic tools to optimize patient management. Her publications address Gram-negative resistance, carbapenem-resistant Enterobacterales, Stenotrophomonas and MRSA infections, fungal pathogens, and empirical management strategies in tertiary care hospitals. She also investigates the role of immunotherapeutic interventions, such as SPAG9-primed dendritic cell-based vaccines, in gallbladder cancer. With expertise in epidemiological research, laboratory diagnostics, and clinical trial design, she has advanced knowledge on antimicrobial stewardship and resistance mitigation. Through workshops, symposia, and mentorship, Dr. Sabharwal promotes evidence-based practices, bridging clinical microbiology with public health strategies to combat AMR and improve patient outcomes, establishing her as a prominent contributor to infectious disease research and translational microbiology. (210 citations by ; 36 Documents; h-index: 8).

Profiles: Google scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Sabharwal, E. R. (2012). Antibiotic susceptibility patterns of uropathogens in obstetric patients. North American Journal of Medical Sciences, 4(7), 316. Citations: 106

  2. Sabharwal, E. R., & Sharma, R. (2015). Fosfomycin: An alternative therapy for the treatment of UTI amidst escalating antimicrobial resistance. Journal of Clinical and Diagnostic Research, 9(12), DC06–DC09. Citations: 48

  3. Sabharwal, E. R., & Sharma, R. (2015). Estimation of microbial air contamination by settle plate method: Are we within acceptable limit? Scholars Academic Journal of Biosciences, 3(8), 703–707. Citations: 15

  4. Sabharwal, E. R. (2010). Successful management of Trichosporon asahii urinary tract infection with fluconazole in a diabetic patient. Indian Journal of Pathology and Microbiology, 53(2), 387–388. Citations: 14

  5. Jain, M., Sabharwal, E. R., & Srivastava, D. (2016). Practices of health care personnel regarding occupational exposure. Journal of Clinical and Diagnostic Research, 10(11), DC14–DC17. Citations: 12

Saika Farook | Molecular Biology | Best Researcher Award

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Assist. Prof. Dr. Saika Farook | Molecular Biology | Best Researcher Award

Assistant Professor | Ibrahim Medical College | Bangladesh

Dr. Saika Farook is a distinguished Bangladeshi microbiologist and academic, currently serving as Assistant Professor in the Department of Microbiology at Ibrahim Medical College, Dhaka, and as Adjunct Faculty at BRAC University. She earned her Doctor of Medicine (MD) in Microbiology from BIRDEM Academy, affiliated with Bangabandhu Sheikh Mujib Medical University (BSMMU) in 2020, following her MBBS from Noakhali Medical College under Chittagong University in 2014. Her foundational education includes H.S.C. from Rajuk Uttara Model College. Professionally, Dr. Farook has accumulated extensive clinical and research experience, having served as a Junior Consultant and Virologist at DMFR Molecular Lab & Diagnostics, an MD resident at BIRDEM Academy, and an intern doctor at Jananeta Nurul Haque Adhunik Hospital. Her research focuses on molecular microbiology, infectious diseases, and the epidemiology of Burkholderia pseudomallei, with ongoing projects on detection, molecular epidemiology, and clinical characterization of melioidosis in Bangladesh. Dr. Farook has led and participated in numerous workshops, including bacterial genomics, antimicrobial resistance, bioinformatics, molecular techniques, and infection prevention and control, and she has organized the 3rd South Asian Melioidosis Congress-2023. Her scholarly contributions include 18 publications in peer-reviewed journals, covering diagnostics, molecular epidemiology, and clinical case reports, with presentations at national and international conferences. She is a life member of the Bangladesh Society of Medical Microbiologists and a contributing member of the Global Outreach of the American Society for Microbiology. Dr. Farook’s work has significantly advanced microbiology research and public health awareness in Bangladesh, bridging clinical findings to laboratory investigations and global collaboration. Her academic excellence is further reflected in her research impact, with 6 citations across 4 documents and an h-index of 2.

Profiles: Scopus | ORCID | ResearchGate

 

Featured Publications

Moutusy, S. I., Farook, S., Mazumder, S., & Jilani, M. S. A. (2024, Jan). Modified MacConkey agar: A simple selective medium for isolation of Burkholderia pseudomallei from soil. [Full text]. IMC Journal of Medical Science.

Jilani, M. S. A., Farook, S., Bhattacharjee, A., & Tuanyok, A. (2023, Dec). Phylogeographic characterization of Burkholderia pseudomallei isolated from Bangladesh. PLoS Neglected Tropical Diseases. https://doi.org/10.1371/journal.pntd.0011823

Farook, S., Jilani, M. S. A., Islam, M. K., Rawal, S. K., & Mendiratta, N. (2023, Aug). IgG4-related retroperitoneal fibrosis: A case report of a challenging disease. Clinical Case Reports, 11(9), e7865.

Farook, S., Hoque, F., Anwar, S., & Jilani, M. S. A. (2022, Dec). Melioidosis: Bridging the gap from bedside to bench in Bangladesh. Z H Sikder Women’s Medical College Journal, 5(1), 53–57.

Muhib, F., Farook, S., Hossain, M. B., & Jilani, M. S. A. (2025, Sep). Septicemic melioidosis in a young adult with transfusion-dependent β-thalassemia major. Current Research in Microbial Sciences. https://doi.org/10.1016/j.crmicr.2025.100464

Yaxiong Wu | Robotics and Automation | Best Researcher Award

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Dr. Yaxiong Wu | Robotics and Automation | Best Researcher Award

Assistant Researcher |  Institute of Automation, Chinese Academy of Sciences | China

Dr. Yaxiong Wu (BRID: 00917.00.90205) is an Assistant Research Fellow at the Institute of Automation, Chinese Academy of Sciences (CAS), affiliated with the State Key Laboratory of Multimodal Artificial Intelligence Systems. He earned both his B.Eng. (2019) and Ph.D. (2024) in Mechanical Engineering from the University of Science and Technology Beijing, demonstrating a consistent academic excellence in robotics and control systems. Following his doctoral studies, he joined CAS as a Postdoctoral Fellow and later advanced to his current role as an Assistant Research Fellow. His professional experience spans across musculoskeletal robotics, biomechanical modeling, intelligent control, and human–machine interaction, with a strong interdisciplinary approach integrating mechanical design, neural control principles, and artificial intelligence. Dr. Wu’s research interests focus on bio-inspired musculoskeletal robotic systems, equilibrium-point control theory, compliant motion learning, and brain–machine fusion technologies, aiming to bridge biological mechanisms with robotic intelligence for humanoid applications. His research skills include advanced control algorithm development, multimodal data fusion, robotic system modeling, reinforcement learning, and experimental validation of human-like motion systems. As Principal Investigator of an NSFC Youth Science Fund Project and participant in several national R&D programs funded by the Ministry of Science and Technology and Ministry of Industry and Information Technology, Dr. Wu contributes to China’s major strategic initiatives in humanoid robotics and intelligent systems. His representative works, published in journals such as IEEE/ASME Transactions on Mechatronics, Neurocomputing, and Robotic Intelligence and Automation, highlight innovative methods for control robustness and morphology learning in tendon-driven robotic arms. He has also co-invented multiple patents on artificial muscle devices and musculoskeletal control systems. Dr. Wu’s excellence has earned him recognition within the robotics research community, reflecting his growing influence and scholarly impact, with 148 citations by , 14 Documents, and an h-index of 6.

Profiles: Google scholar | Scopus | ORCID | ResearchGate

Featured Publications

Qiao, H., Wu, Y., Zhong, S., Yin, P., & Chen, J. (2023). Brain-inspired intelligent robotics: Theoretical analysis and systematic application. Machine Intelligence Research, 20(1), 1–18.Citations: 81

Wu, Y., Chen, J., & Qiao, H. (2021). Anti-interference analysis of bio-inspired musculoskeletal robotic system. Neurocomputing, 436, 114–125.Citations: 31

Chen, J., Wu, Y., Yao, C., & Huang, X. (2024). Robust motion learning for musculoskeletal robots based on a recurrent neural network and muscle synergies. IEEE Transactions on Automation Science and Engineering, 22, 2405–2420.Citations: 18

Chen, J., Wu, Y., & Qiao, H. (2024). Memory, attention, and muscle synergies based reinforcement and transfer learning for musculoskeletal robots under imperfect observation. IEEE/ASME Transactions on Mechatronics.Citations: 14

Fan, Y., Yuan, J., Wu, Y., & Qiao, H. (2023). A feedforward compensation approach for cable-driven musculoskeletal systems. Robotica, 41(4), 1221–1230.Citations: 10

zihan gao | Chemical Engineering | Best Researcher Award

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Dr. zihan gao | Chemical Engineering | Best Researcher Award

Phd | China University of Petroleum (East China) | China

Dr. Zihan Gao is an emerging researcher in the field of Safety Engineering at the China University of Petroleum (East China), Qingdao, China. His academic foundation lies in industrial risk management, process safety, and occupational health, with a specialized focus on Process Safety Management (PSM) systems for accident prevention and operational reliability. Holding a Ph.D. in Safety Engineering, Dr. Gao has conducted significant research aimed at developing quantifiable Key Performance Indicators (KPIs) that bridge the gap between theoretical safety models and real-world industrial applications. His professional experience includes contributing to the Shandong Province Process Safety Management Assessment Project, and publishing influential works in reputable international journals such as the Journal of Intelligent & Fuzzy Systems and Process Safety Progress. Dr. Gao’s research interests span chemical process safety, hazard analysis, safety data analytics, and risk assessment modeling, with a commitment to integrating AI-based systems into industrial safety frameworks. His research skills encompass quantitative risk modeling, system reliability assessment, simulation analysis, and data-driven safety benchmarking, all directed toward enhancing performance metrics in high-risk industries. Recognized for his scholarly rigor and practical innovation, he has contributed to national efforts to improve China’s chemical safety framework through the 2024 PSM development initiative, which integrated education, standardization, and localized implementation of international safety practices. Dr. Gao’s growing citation record and Scopus-indexed publications reflect his dedication to advancing the frontiers of safety engineering. His goal is to strengthen global collaborations, increase Q1 journal publications, and contribute to international safety management discourse through keynote engagements and editorial participation. In recognition of his achievements and continued promise, Dr. Gao represents a new generation of researchers committed to elevating industrial safety standards and fostering sustainable, risk-free operations. Zihan Gao, China University of Petroleum (East China), Qingdao, China. Scopus ID: 57224466238. 2 Citations. 3 Documents. h-index: 1.

Profiles: Scopus | ORCID | ResearchGate

Featured Publications

1. Gao, Z., & Zhao, D. (2025, September 26). A hybrid DEMATEL–ISM–CN–BN framework for explosive risk analysis in hydrogenation processes. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology. https://doi.org/10.1177/18758967251374191

2. Gao, Z., Meng, Y., Chen, Q., Hu, Y., & Zhao, D. (2025, September 3). Key advances in chemical process safety management in China: A 2024 perspective. Process Safety Progress, 44(5), Article e70020. https://doi.org/10.1002/prs.70020

Justine Dushimirimana | Mathematical Sciences | Best Researcher Award

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Mrs. Justine Dushimirimana | Mathematical Sciences | Best Researcher Award

Assistant Lecturer | University of Rwanda | Rwanda

Mrs. Justine Dushimirimana is an accomplished Assistant Lecturer at the University of Rwanda, affiliated with the Mathematics Department, College of Science and Technology. She earned her Bachelor of Science in Applied Mathematics with First Class Honours and a Master of Science in Applied Mathematics, specializing in Statistical Modelling and Actuarial Sciences, from the University of Rwanda, where her master’s thesis was published in the African Journal of Applied Statistics (2021). Currently, she is pursuing a Ph.D. in Mathematical Statistics at the University of Nairobi, advancing the Generalized Growth Curve Model through improved parameter estimation and hypothesis testing and introducing tensor residuals for robust model adequacy assessment in spatio-temporal data. Her research spans multivariate statistics, focusing on the structure and estimation of covariance matrices, parameter estimation methods, hypothesis testing, and model diagnostics for complex datasets, with practical applications in environmental sciences. She has completed significant research projects, including her master’s thesis on calcium foliar feed effects on rose flowers, an NCST-funded project on predictive modeling of COVID-19 in Rwanda, and a University of Rwanda grant on multifluid cosmology in f(G) gravity, while her ongoing Ph.D. work further enhances statistical frameworks for tensor data analysis. Mrs. Dushimirimana has authored five publications in reputed journals and actively collaborates with distinguished researchers including Prof. Isaac K. Chumba, Prof. Joseph Nzabanita, Dr. Lydia Musiga, and Dr. Ronald Waliaula Wanyonyi. She is a member of the Eastern Africa Network for Women in Basic Sciences (EANWoBAS) and the Eastern Africa Universities Mathematics Programme (EAUMP) research network. Her innovative contributions, particularly the formulation of the general trilinear hypothesis and development of tensor residuals, have strengthened model diagnostics, inference accuracy, and decision-making in multivariate and spatio-temporal analyses. Recognized for her academic rigor, research excellence, and collaborative spirit, Mrs. Dushimirimana exemplifies a rising leader in mathematical statistics whose work significantly impacts both theoretical and applied domains.

Profiles: Scopus | ORCID | ResearchGate

Featured Publications

  • Dushimirimana, J., Chumba, I. K., Musiga, L., Nzabanita, J., & Waliaula Wanyonyi, R. (2025). Test for a general trilinear hypothesis in the generalized growth curve model. Journal of Multivariate Analysis, 210, 105470. https://doi.org/10.1016/j.jmva.2025.105470

  • Ntahompagaze, J., Twagirayezu, F., Ayirwanda, A., Munyeshyaka, A., Mukeshimana, S., Ruganzu Uwimbabazi, L. F., & Dushimirimana, J. (2025). On 1 + 3 covariant perturbation with Chaplygin-stiff fluid system in modified Gauss-Bonnet gravity. Rwanda Journal of Engineering, Science, Technology and Environment, 7(1), 1–15. https://doi.org/10.4314/rjeste.v7i1.1

  • Ngaruye, I., Nzabanita, J., Masabo, E., Gahamanyi, M., Nyandwi, B., Dushimirimana, J., Ndanguza, D., Mpinganzima, L., Kurujyibwami, C., & Ruganzu Uwimbabazi, L. F. (2025). The effect of meteorological factors on extreme COVID-19 infection in Rwanda: The generalized additive extreme value modeling approach. Rwanda Journal of Engineering, Science, Technology and Environment, 7(1), 8–21. https://doi.org/10.4314/rjeste.v7i1.8

  • Ndanguza, D., Ngendahayo, J. P., Uwimana, A., Niyigena, J. D., Mbalawata, I. S., Ngaruye, I., Nzabanita, J., Masabo, E., Gahamanyi, M., Nyandwi, B., Ngaruye, I., Dushimirimana, J., & Waliaula Wanyonyi, R. (2024). Analysis of the COVID-19 pandemic in Rwanda using a stochastic model. Mathematics Open, 3(1), 1–15. https://doi.org/10.1142/s281100722350013x

  • Mpinganzima, L., Ntaganda, J. M., Banzi, W., Muhirwa, J. P., Nannyonga, B. K., Niyobuhungiro, J., Rutaganda, E., Ngaruye, I., Ndanguza, D., Nzabanita, J., & Dushimirimana, J. (2023). Compartmental mathematical modelling of dynamic transmission of COVID-19 in Rwanda. IJID Regions, 5, 1–10. https://doi.org/10.1016/j.ijregi.2023.01.003

 

Lawrence Adetunde | Environmental Science | Excellence in Research Award

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Dr. Lawrence Adetunde | Environmental Science | Excellence in Research Award

Senior Lecturer | C.K.Tedam University of Technology and Applied Sciences | Ghana

Dr. Lawrence Adelani Adetunde is a Senior Lecturer in the Department of Applied Biology at C. K. Tedam University of Technology and Applied Sciences, Ghana, and holds a Ph.D. in Microbiology from Landmark University (2025). His educational background combines rigorous scientific training and a deep commitment to addressing environmental and public health challenges through microbiological innovation. Over the years, Dr. Adetunde has developed extensive expertise in environmental and industrial microbiology, water quality monitoring, and antimicrobial resistance studies, focusing on microbial characterization and biotechnological applications for sustainable ecosystems. Professionally, he has served as a dedicated educator, mentor, and research supervisor, guiding numerous undergraduate and postgraduate projects and contributing to the academic and personal development of students. His leadership extends beyond teaching—he is the departmental postgraduate coordinator and an active member of several academic and institutional committees, promoting quality research and curriculum advancement. Dr. Adetunde’s research interests encompass microbial water quality assessment, biofilm formation, antimicrobial activity testing, and the application of beneficial microorganisms in bioremediation and industrial processes. His research skills include microbial isolation and identification, molecular and biochemical analysis, and advanced laboratory management techniques. With more than 30 peer-reviewed publications in reputable Scopus-indexed journals such as Environmental Advances and the African Journal of Microbiology Research, he has made significant contributions to applied microbiological science. Dr. Adetunde has received recognition for his dedication to teaching, scientific innovation, and community engagement. His ongoing collaborations with international researchers continue to enhance the global relevance of his work in environmental and industrial microbiology. His scholarly impact is further reflected in 15 citations , 5 documents, and an h-index of 2.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Adetunde, L. A., & Glover, R. L. K. (2010). Bacteriological quality of borehole water used by students’ of University for Development Studies, Navrongo campus in Upper-East Region of Ghana. Current Research Journal of Biological Sciences, 2(6), 361–364. (Cited 78 times)

  2. Adetunde, L. A., Glover, R. L. K., & Oguntola, G. O. (2011). Assessment of the ground water quality in Ogbomoso township of Oyo State of Nigeria. (Cited 53 times)

  3. Adetunde, L. A., Glover, R. L. K., Oliver, A. W., & Samuel, T. (2011). Source and distribution of microbial contamination on beef and chevon in Navrongo, Kassena Nankana district of Upper East Region of Ghana. Journal of Animal Production Advances, 1(1), 21–28. (Cited 26 times)

  4. Adetunde, L. A., & Glover, R. L. K. (2011). Evaluation of bacteriological quality of drinking water used by selected secondary schools in Navrongo in Kassena-Nankana district of Upper East Region of Ghana. Prime Journal of Microbiology Research, 1, 47–51. (Cited 18 times)

  5. Adetunde, L., Sackey, I., Dombiri, D., & Mariama, Z. (2015). Potential links between irrigation water microbiological quality and fresh vegetables quality in Upper East Region of Ghana subsistence farming. Annual Research & Review in Biology, 6(6), 347–354. (Cited 15 times)

Feng Mao | Cognitive Science | Best Researcher Award

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Assist. Prof. Dr. Feng Mao | Cognitive Science | Best Researcher Award

Associate Professor | Shanghai University of International Business and Economics | China

Assist. Prof. Dr. Feng Mao is a distinguished Associate Professor and Senior Translator at Shanghai University of International Business and Economics with 28 years of higher education experience, specializing in country and area studies, translation studies, and foreign language education. He is currently pursuing a Ph.D. at Shanghai International Studies University (since 2022) and serves as a Master’s supervisor for MA in Linguistics and MTI programs. Over his career, he has led 11 research projects, including a national-level Social Science Fund project, and collaborated with international scholars from Singapore, Canada, the UK, and Germany, reflecting his strong global research network. His professional experience includes mentoring MA students, peer reviewing for SSCI and AHCI journals, editorial committee service, and contributions to national professional assessments, including CATTI examination grading. His research interests focus on translation and interpreting studies, foreign language education and policy, cross-cultural communication, applied linguistics, audiovisual translation, and country and area studies. MAO Feng has developed advanced research skills in big data analysis for textbook and material compilation, literary analysis, audiovisual translation methods, and educational program evaluation, supporting both theoretical and applied projects. He has authored 64 academic publications, including 20 SSCI/AHCI journal papers with 5 in Q1 journals, and published 5 academic monographs and translations totaling over 2 million words, alongside textbooks and review articles that serve thousands of students. He has also contributed to industry and government consultancy projects such as cultural brand promotion and copyright export research. His awards and honors include national-level recognition for professional degree assessment and leadership roles within the China Association for Educational Linguistics and the Translators Association of China. Overall, MAO Feng’s extensive research, teaching, publications, and international collaborations highlight his exceptional academic leadership and ongoing potential to advance translation studies and foreign language education globally. 7 Citations, 8 Documents, h-index 2.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

Mao, F., & Yang, X. (2024). Literary therapy based on positive psychology: Impact on college students’ happiness. Journal of Poetry Therapy, 37(1), 16–34. https://doi.org/[insert DOI] (Citations: 5)

Mao, F., & Liu, S. (2024). Book review: Networked feminism: How digital media makers transformed gender justice movements (R. Clark-Parsons, California, University of California Press, 2022). Feminist Media Studies, 24(2), 404–406. (Citations: 3)

Feng, M., Wenhui, L., Xinle, Y., & Biyu, W. (2022). Romantic narrative in the film The Battle at Lake Changjin. International Journal of English and Comparative Literary Studies, 3(1), 19–27. (Citations: 3)

Feng, M., Quan, L., & Wu, B. (2021). A review on the compilation of college English textbooks in China based on big data. Sino-US English Teaching, 18(3), 60–65. (Citations: 3)

Feng, M., Quan, L., & Biyu, W. (2021). Exploration of the compilation of English learning materials for Chinese college students based on big data under the guidance of complex dynamic theory. International Journal of Linguistics, Literature and Translation, 4(3), 22–32. (Citations: 2)

Sharifah Emilia Tuan Sharif | Environmental Science | Best Researcher Award

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Assoc. Prof. Dr. Sharifah Emilia Tuan Sharif | Environmental Science | Best Researcher Award

Pathologist | Universiti Sains Malaysia | Malaysia

Assoc. Prof. Dr. Sharifah Emilia Tuan Sharif is a distinguished Associate Professor and senior consultant anatomic pathologist at Universiti Sains Malaysia (USM), recognized for her subspecialty expertise in bone and soft tissue pathology and her contributions to clinical diagnostics, translational research, and innovative medical education. She earned her MBBS in 2000 and Master of Pathology (Anatomic Pathology) in 2005 from USM, establishing a strong foundation for her academic and clinical career. Professionally, she serves as Chairperson of the Pathology Specialty Committee, Director of SPICES (Interactive Gallery for Medical Sciences), and Laboratory-based Clinical Master Programme Coordinator, where she leads curriculum development, mentoring, and national quality assurance initiatives. Her research interests include biomarker discovery in liposarcoma (CDK4/MDM2), prognostic markers in colorectal adenoma and carcinoma, environmentally sustainable medical waste disposal, and the integration of VR/AR in pathology education. She has led multiple national research projects, including the KUBOWrapper initiative for deep-soil burial of medical waste, and developed award-winning educational platforms such as SPICESPath 360 and VI-SPICES. Her research skills encompass histopathology, immunohistochemistry, FISH analysis, protein profiling, translational oncology, biomaterials characterization, and digital/immersive medical education technologies. Dr. Sharifah Emilia has published over 80 papers in indexed journals, with significant contributions in Q1/Q2 journals and international conferences, demonstrating both clinical relevance and translational impact. Her work has earned innovation awards (AKRI 2023 & 2024), recognition in the Malaysia Book of Records for SPICESPath 360, and multiple research grants, reflecting her commitment to research excellence, leadership, and community engagement. She actively mentors students, collaborates with the Ministry of Health, and promotes STEM education through SPICES4U Jr. and SPICES4STEM programs. With her outstanding record of research, innovation, and societal impact, she exemplifies the qualities of a leading researcher in medical sciences. 645 Citations, 45 Documents, h-index 8.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Ibrahim, Y. S., Tuan Anuar, S., Azmi, A. A., Wan Mohd Khalik, W. M. A., Lehata, S., … (2021). Detection of microplastics in human colectomy specimens. JGH Open, 5(1), 116–121. Citations: 541

  2. Ch’ng, E. S., Tuan Sharif, S. E., & Jaafar, H. (2013). In human invasive breast ductal carcinoma, tumor stromal macrophages and tumor nest macrophages have distinct relationships with clinicopathological parameters and tumor …. Virchows Archiv, 462(3), 257–267. Citations: 54

  3. Ibrahim, Y. S., Tuan Anuar, S., Azmi, A. A., Wan Mohd Khalik, W. M. A., Lehata, S., … (2021). Detection of microplastics in human colectomy specimens. JGH Open, 5, 116–121. Citations: 43

  4. Pasupati, T. M., Yothasamutr, K., Wah, M. J., Sherif, S. E. T., & Palayan, K. (2008). A study of parasitic infections in the luminal contents and tissue sections of appendix specimens. Tropical Biomedicine, 25(2), 166–172. Citations: 38

  5. Ch’ng, E. S., Jaafar, H., & Tuan Sharif, S. E. (2011). Breast tumor angiogenesis and tumor-associated macrophages: Histopathologist’s perspective. Pathology Research International, 2011, 572706. Citations: 36

Alexander Kryukov | Astronomy and Space | Best Researcher Award

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Dr. Alexander Kryukov | Astronomy and Space | Best Researcher Award

Head of Laboratory | Lomonosov Moscow State University | Russia

Dr. Alexander Kryukov is a distinguished physicist and computational scientist with an extensive career in high-energy particle physics, distributed computing, and machine learning applications in cosmic and gamma-ray astronomy. He graduated from Lomonosov Moscow State University in 1977, earning a specialization in Physics with a focus on High Energy Physics, and completed his Ph.D. in 1988 on the design and implementation of integrated dialogue systems for analytical computing software. Since 1980, he has progressed through roles from Junior Researcher to Head of the Laboratory at the Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, demonstrating exemplary leadership and research management. Dr. Kryukov’s professional experience includes leading large-scale national and international projects, including the Russian national grid network for the Large Hadron Collider (CERN), CERN-INTAS projects, and multiple RSF-funded initiatives on machine learning for astrophysical data analysis. His research interests encompass computational modeling of elementary particle interactions, computer algebra methods, cloud and grid computing, and applications of artificial intelligence in physics. He has contributed to major international collaborations such as CMS (CERN), Hyper-Kamiokande (Japan), TAIGA (Russia), and JUNO (China), and his publication record includes over 200 documents in reputed journals such as Physics Letters B, Journal of Instrumentation, and Computer Physics Communications. Dr. Kryukov’s work has had significant scientific and societal impact through mentorship, leadership in international collaborations, and the development of advanced computational infrastructures. His professional skills include Fortran, C/C++, Python, Mathematica, Maple, REDUCE, Linux, distributed computing, cloud computing, and machine learning frameworks. Recognized for his excellence, he has been cited extensively, reflecting his influential contributions to physics and computational science. With a sustained record of innovation, leadership, and mentorship, Dr. Kryukov continues to shape the future of high-energy physics and computational research. 8,089 Citations, 200 Documents, 17 h-index.

Profiles: Scopus | ORCID | ResearchGate

Featured Publications

    1. Prosin, V., Astapov, I., Bezyazeekov, P., Bonvech, E., Borodin, A., Bulan, A., … Yashin, I. (2023, September 29). Primary cosmic ray energy spectrum and mean mass composition using data from the TAIGA astrophysical complex. SciPost Physics Proceedings, 13(037). https://doi.org/10.21468/SciPostPhysProc.13.037

    2. Ivanova, A. L., Astapov, I., Bezyazeekov, P., Bonvech, E., Borodin, A., Budnev, N., … (2023, September 28). The Tunka-Grande scintillation array: Current results. SciPost Physics Proceedings, 13(011). https://doi.org/10.21468/SciPostPhysProc.13.011

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