Saifullah Khalid | Artificial Intelligence | Innovative Research Award

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Dr. Saifullah Khalid | Artificial Intelligence | Innovative Research Award

Principal Scientist | IBMM RESEARCH | Sudan

Dr. Saifullah Khalid is a distinguished aviation and aerospace researcher renowned for his groundbreaking work in AI-driven aviation systems, air traffic management optimization, and unmanned aerial systems. With dual PhDs in engineering and a career spanning advanced aeronautical research, he serves as Principal Scientist at IBMM Research, Sudan. His academic background includes a PhD in Electronics and Communication Engineering from SN University, India (2013). Dr. Khalid’s expertise encompasses autonomous UAV systems, quantum-inspired optimization algorithms, sustainable aviation power systems, and digital tower operations. He has authored over 270 publications, including 38 Web of Science-indexed papers, and holds an impressive portfolio of 85 patents—50 as sole inventor—setting two world records for patent achievements. His professional experience extends to teaching and mentoring, supervising PhD candidates in AI-based air route optimization and guiding over 200 engineering projects. A committed academic leader, he has developed ICAO-compliant curricula and serves as Vice Chairman of the Academic Council Asia at NextGen University International. His awards include world records for patent excellence and international recognition for research innovation. His technical skills span MATLAB/Simulink, Python, UAV system design, and AI applications in aviation. 305 Citations; 67 Documents; h-index: 10

Profiles: Google scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Khalid, S., & Dwivedi, B. (2011). Power quality issues, problems, standards & their effects in industry with corrective means. International Journal of Advances in Engineering & Technology, 1(2), 1–11. Citations: 167

  2. Nishad, D. K., Tiwari, A. N., Khalid, S., Gupta, S., & Shukla, A. (2024). AI-based UPQC control technique for power quality optimization of railway transportation systems. Scientific Reports, 14(1), 17935. Citations: 31

  3. Khalid, S. (2018). Performance evaluation of Adaptive Tabu Search and Genetic Algorithm optimized shunt active power filter using neural network control for aircraft power utility of 400 Hz. Journal of Electrical Systems and Information Technology, 5(3), 723–734. Citations: 30

  4. Khalid, S., Dwivedi, B., Kumar, N., & Agrawal, N. (2007). A review of state-of-art techniques in active power filters and reactive power compensation. National Journal of Technology, 3(1), 10–18. Citations: 26

  5. Khalid, S., & Dwivedi, B. (2010). Power quality: An important aspect. International Journal of Engineering Science and Technology, 2(11), 6485–6490. Citations: 25

Taija Juutinen Finni | Biomedical Sciences | Best Researcher Award

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Prof. Taija Juutinen Finni | Biomedical Sciences | Best Researcher Award

Professor | University of Jyväskylä | Finland

Dr. Taija Juutinen Finni is a distinguished Professor of Kinesiology at the Faculty of Sport and Health Sciences, University of Jyväskylä, Finland, and Vice Dean for Education. With a Ph.D. in Biomechanics (2001) and a Title of Docent in Exercise Physiology (2006), she has built a remarkable academic and research career at the intersection of biomechanics, exercise physiology, and rehabilitation sciences. Her academic training from the University of Jyväskylä, complemented by pedagogical and leadership qualifications, reflects her commitment to education and scientific excellence. Professionally, she has held several pivotal roles, including postdoctoral research at UCLA and multiple research and teaching positions in Finland, before her full professorship in 2010. Dr. Juutinen’s research focuses on muscle-tendon mechanics, Achilles tendon function, physical activity patterns, and rehabilitation in neurological and musculoskeletal disorders, supported by major national and international funding bodies such as the Research Council of Finland and the Ministry of Education and Culture. She has successfully led numerous high-impact projects (e.g., ACHILLES, EXECP, UNRESAT, CHIPASE) and supervised over 18 Ph.D. candidates and 80 M.Sc. theses. Her extensive publication record of 178 scientific papers and two patents underscores her global impact in biomechanics and sports medicine. A sought-after keynote speaker, she has contributed to major international congresses, served on editorial boards of leading journals, and evaluated professorships and grants across Europe and North America. Her awards include the First Class Knight’s Cross of the Order of the White Rose of Finland (2023) and multiple recognitions from international biomechanical societies. A fellow of both the International Society of Biomechanics and the European College of Sport Science, she continues to advance understanding of tendon structure, physical activity, and human performance through cutting-edge interdisciplinary research. Citations: 5,711; documents: 183; h-index: 44.

Profiles: Scopus | ORCID | ResearchGate

Featured Publications

  1. Juutinen, T., et al. (2025). The relationship between triceps surae muscle–tendon morphology and shear modulus across passive ankle range of motion in cerebral palsy. Journal of Biomechanics, 2025. (Open Access).

  2. Juutinen, T., et al. (2025). Medial gastrocnemius muscle and aponeurosis shear wave velocity and morphological changes after Achilles tendon rupture: A 1-year follow-up study. Journal of Biomechanics, 2025. (Open Access).

  3. Juutinen, T., et al. (2025). Physical activity in children and young adults with cerebral palsy: Results from a three-month exercise intervention. European Journal of Sport Science, 2025. (Open Access).

  4. Juutinen, T., et al. (2025). Acute effects of isometric plantarflexion exercise on Achilles tendon non-uniform displacement. Journal of Biomechanics, 2025. (Open Access). Citations: 1

  5. Juutinen, T., et al. (2025). A novel method to assess subject-specific architecture of the Achilles tendon in vivo in humans. Scandinavian Journal of Medicine & Science in Sports, 2025. (Open Access). Citations: 2

Iffat Prianka | Public Health | Public Health Impact Award

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Assist. Prof. Dr. Iffat Prianka | Public Health | Public Health Impact Award 

Asst.Professor | Ibrahim Medical College | Bangladesh

Dr. Iffat Tania Prianka is a dedicated public health professional and medical educator from Bangladesh, currently serving as Assistant Professor in the Department of Community Medicine & Public Health at Ibrahim Medical College (BIRDEM). She holds an M.Phil. in Preventive and Social Medicine from BSMMU (NIPSOM), an MPH in Epidemiology from AIUB, and has successfully completed FCPS Part I in Community Medicine and Public Health. She is presently pursuing her Ph.D. at Bangladesh University of Professionals. Her academic journey is distinguished by strong research engagement, with completed studies on autism awareness among medical students, internet addiction during the COVID-19 pandemic, and the psychosocial impact of infertility among women. She possesses advanced research skills in epidemiology, biostatistics, and data interpretation using SPSS and STATA, strengthened by extensive training in research methodology, medical education, and faculty development programs from institutions such as Eudoxia Research University and Fera Foundation. Her teaching and clinical experience span over a decade, with prior roles as Lecturer in Biochemistry and Community Medicine, and as Senior House Physician at United Hospital Dhaka. Recognized with Magna Cum Laude distinction and Dean’s Award, Dr. Prianka aims to contribute to global public health advancement through impactful research, evidence-based education, and community-focused healthcare solutions.

Profile: ORCID

Featured Publications

Prianka, I. T. (2022). Knowledge and Attitude on Early Sign of Autism Among 1st Year to 3rd Year Medical Students in a Selected Medical College in    Bangladesh. International Journal of Medical Research and Pharmaceutical Sciences, 9(9), 1–7. Available at: ijmrpsjournal.com

Jahan, N., Rumman, I., Prianka, I. T., & Gupta, P. K. S. (2023). Internet Addiction Among Medical Students During the COVID-19 Pandemic in Dhaka      City: Prevalence and Associated Factors. International Research Journal of Medical and Pharmaceutical Sciences, 1(1), 64–76. Available at: zapjournals.com

Konstantinos Lazopoulos | Applied Mathematics | Best Researcher Award

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Prof. Dr. Konstantinos Lazopoulos | Applied Mathematics | Best Researcher Award

researcher | National Technical University of Athens | Greece 

Prof. Dr. Konstantinos Lazopoulos is a distinguished scholar in Applied Mathematics and Mechanics, currently serving at the National Technical University of Athens (NTUA), Greece. With an academic foundation rooted in both engineering and mathematics, he earned his Diploma in Civil Engineering from NTUA in 1968, followed by a Diploma in Mathematics from the University of Athens in 1975. He then pursued advanced studies in the United States, obtaining a Master’s degree in Mechanics from Virginia Tech in 1977 and a Ph.D. in Mechanics from Georgia Tech in 1979, both supported by university scholarships. From 1980 to 2013, he was a dedicated faculty member at NTUA’s Department of Applied Mathematics and Physics, contributing profoundly to education and research. His prolific academic output includes over 100 research papers published in leading international journals, focusing on innovative analytical and computational methods in Applied Mathematics and Mechanics. Prof. Lazopoulos is internationally recognized for developing the mathematically rigorous Λ-Fractional Analysis, a novel fractional method inspired by Leibnitz’s foundational ideas of 1695 and satisfying the stringent conditions of Differential Topology. His research interests encompass fractional calculus, continuum mechanics, nonlinear analysis, and mathematical modeling of physical systems. His expertise lies in developing precise mathematical frameworks to describe complex mechanical behaviors, bridging theory and practical application in mechanics and physics. Acknowledged for his scholarly excellence, Prof. Lazopoulos has been featured in Stanford University’s global catalog of the top 2% most influential researchers, underscoring his lasting impact on the scientific community. His career reflects a lifelong commitment to advancing the frontiers of mathematical science and engineering through original thought, rigor, and innovation.1,280 Citations; 79 Documents; 19 h-index.

Profiles: Google scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Lazopoulos, K. A. (2006). Non-local continuum mechanics and fractional calculus. Mechanics Research Communications, 33(6), 753–757. [Cited by: 225]

  2. Lazopoulos, K. A., & Lazopoulos, A. K. (2010). Bending and buckling of thin strain gradient elastic beams. European Journal of Mechanics – A/Solids, 29(5), 837–843. [Cited by: 163]

  3. Lazopoulos, K. A. (2009). On bending of strain gradient elastic micro-plates. Mechanics Research Communications, 36(7), 777–783. [Cited by: 147]

  4. Lazopoulos, K. A. (2004). On the gradient strain elasticity theory of plates. European Journal of Mechanics – A/Solids, 23(5), 843–852. [Cited by: 116]

  5. Lazopoulos, K. A., & Stamenović, D. (2008). Durotaxis as an elastic stability phenomenon.Journal of Biomechanics, 41(6), 1289–1294. [Cited by: 66]

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