PHILIPPE LEFF | Health Professions | Lifetime Achievement Award

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Dr. PHILIPPE LEFF | Health Professions | Lifetime Achievement Award

Medico | INPer | Mexico

Dr. Philippe Leff Gelman is a distinguished medical scientist and neuroscientist from Mexico City with extensive expertise in neurochemistry, neuroendocrinology, and clinical neuroscience, focusing on maternal mental health, addiction neurobiology, and perinatal neuroscience. Fluent in Spanish, English, and proficient in French, he earned his Medical Degree from UNAM, Mexico City, followed by a Master’s in Chemical Sciences (Biochemistry) at UNAM and a Doctorate in Medical Research from Instituto Politécnico Nacional, where he focused on biosynthetic precursors of endomorphin-like peptides. He completed postdoctoral studies in Cell Biology & Anatomy at the University of Miami and Behavioral Neuroscience at Boston University, training in neuronal protein synthesis and animal models of drug self-administration. Dr. Leff Gelman has held senior research positions at Instituto Nacional de Perinatología and Instituto Nacional de Psiquiatría, contributed to vaccine development for opioid addiction, and served as a visiting professor internationally. His research integrates neuroendocrine regulation, maternal behavior, neurodevelopment, and addiction neuroscience, bridging molecular, behavioral, and clinical approaches. He has received multiple national and international awards, reflecting his global impact, mentorship, and sustained scientific leadership.

Profile : Scopus 

Featured Publication 

Dr. Leff Gelman has authored numerous influential publications in international peer-reviewed journals, contributing significantly to neuroendocrinology, perinatal mental health, and addiction neuroscience. Key works include:

Leff-Gelman, P., Pellón-Díaz, G., Camacho-Arroyo, I., Palomera-Garfias, N., & Flores-Ramos, M. Neuroendocrine regulation and neural circuitry of parenthood: Integrating neuropeptides, brain receptors, and maternal behavior. International Journal of Molecular Sciences, 26(18), 9007.

Leff, P., Chinchilla-Ochoa, D., Olivas-Peña, E., Granados-Cepeda, M. L., Trejo-Sánchez, K. C., & Farfán-Labonne, B. E. Cognitive dysfunction in systemic lupus erythematosus during pregnancy. American Journal of Reproductive Immunology, 94(2), e70134.

Camacho-Arroyo, I., Flores-Ramos, M., Mancilla-Herrera, I., Cruz-Coronel, F. M., Farfán-Labonne, B., Jiménez-Aquino, L. E., et al. Alterations in adipokine levels are associated with human perinatal anxiety and depression. Journal of Clinical Medicine, 14(12), 4102.

Meza-Rodríguez, M. D. P., Leff-Gelman, P., et al. Serotonin, cortisol, and DHEA-S levels in anxious and depressive pregnant women living with HIV. BMC Psychology, 12, 563.

 

Amine Benchaabane | Remote Sensing | Best Researcher Award

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Mr. Amine Benchaabane | Remote Sensing | Best Researcher Award

Data Scientist Engineer | CLS Group | France

Mr. Amine Benchaabane is an accomplished MLOps Data Scientist and R&D Engineer with a strong interdisciplinary background in data science, geoscience, and applied mathematics, recognized for integrating artificial intelligence and machine learning into environmental and marine research. He pursued a Master’s in Geoscience Data Science at the European Institute for Marine Studies in partnership with IMT Atlantique, specializing in advanced machine learning and remote sensing for oceanography, and a Master’s in Hydrographic and Oceanographic Data Processing from ENSTA Bretagne, gaining deep expertise in marine data engineering and uncertainty propagation. His research and training at GEOAZUR, ONERA, and the French Naval Academy further enriched his skills in hydrographic modeling, SONAR inversion, and drone performance optimization. Professionally, he has advanced large-scale AI integration at CLS Group Brest, applied AI-based remote sensing at LOPS, developed hydrographic pipelines at GEOAZUR, and optimized drones for maritime surveillance at ONERA. His research interests lie at the intersection of AI, oceanography, and applied geosciences, focusing on satellite remote sensing, time-series analysis, semantic segmentation, and data assimilation for climate and environmental monitoring, alongside advanced MLOps-driven deployment of scalable AI models. He has worked extensively with SAR, LIDAR, and altimetry data to enhance retrieval of geophysical features such as wind, waves, and currents, ensuring operational efficiency through high-performance computing integration. Amine has earned recognition for his technical mastery, holding Google Cloud Advanced Machine Learning and Certified MLOps Data Scientist credentials, and his contributions have been acknowledged by leading institutes for their innovative impact in satellite remote sensing, oceanographic modeling, and AI deployment. With his adaptability, creativity, and leadership in bridging scientific challenges with real-world applications, he stands out as a strong candidate for prestigious awards in research and innovation.

Profile : ORCID

Featured Publication 

Benchaabane, A. (2023). AI-based oceanographic data assimilation for sea surface height prediction. Journal of Applied Remote Sensing.

Shimanto Saha | Financial Technology | Best Researcher Award

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Mr. Shimanto Saha | Financial Technology | Best Researcher Award

Lecturer| Bangladesh University of Business and Technology | Bangladesh

Mr. Shimanto Saha is an emerging academic and researcher in management and human resource development, widely recognized for his academic excellence, leadership qualities, and dedication to impactful research. He is currently serving as a Lecturer in the Department of Management at Bangladesh University of Business and Technology (BUBT), where he combines innovative teaching approaches with practical applications of management studies. He completed his BBA in Management Studies and MBA in Human Resource Management from Mawlana Bhashani Science and Technology University (MBSTU), achieving top ranks with exceptional CGPAs in both programs. His academic journey also includes outstanding results in SSC and HSC, along with specialized training in Microsoft Office, SPSS, SmartPLS, and digital content creation. Professionally, Shimanto has blended academic responsibilities with digital engagement, contributing to Minute School as a Project Executive and serving as Visual Content Lead at Business Haunt, where he developed educational content and managed creative projects. He has also been actively involved with the Rotaract Club of MBSTU, where he led community development and skill-building initiatives. His research interests focus on banking performance, financial technology, blockchain, RegTech, and sustainable management practices, with a particular emphasis on emerging markets. He has also conducted studies on entrepreneurship, mobile financial services, and user behavior in adopting new technologies. His achievements include departmental scholarships, presentation competition accolades, and the Best Lead Award from Business Haunt, reflecting both his academic brilliance and leadership capabilities. Dedicated, ambitious, and research-driven, Shimanto envisions mentoring future business leaders while contributing meaningfully to scholarship, policymaking, and the broader field of management.

Profile: Scopus | ORCID 

Featured Publication 

Saha, S. Enhancing banking performance through regulatory technology: Analyzing cost reduction, sustainability, and profitability in Bangladesh’s banking sector. Sustainable Futures. — Cited by 3

Saha, S. Examining the influence of interest rate fluctuations on the financial performance and stability of the UK’s Big 4 banks. Journal of Ekonomi. — Cited by 2

Saha, S. Riding the Bitcoin wave: Attitude and adoption in Bangladesh. Springer Nature Singapore. — Cited by 1

Saha, S. Unveiling the nexus of macroeconomic factors on bank performance in Bangladesh. Journal of Ekonomi. — Cited by 2

Saha, S. Nexus between perception, purpose of use, technical challenges and satisfaction for mobile financial services. Technological Sustainability. — Cited by 2

Saha, S. Factors influencing the adoption of cryptocurrency in Bangladesh: An investigation using TAM. Technological Sustainability. — Cited by 4

Dan Uchimura | Engineering | Best Researcher Award

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Mr. Dan Uchimura | Engineering | Best Researcher Award

Mr. Dan Uchimura|Kajima Corporation | Japan

Dan Uchimura is an emerging professional in nuclear power plant structural design, currently serving as a designer in the Kajima Corporation Nuclear Power Department. With a Master’s Degree in Architecture from Waseda University, he has swiftly transitioned from academia to industry, applying his expertise in structural systems, safety analysis, and computational modeling. During his graduate studies in Tokyo, he focused on enhancing the resilience and sustainability of energy facilities, developing technical skills in MATLAB, Python, and Excel to simulate structural integrity under extreme conditions. Since joining Kajima, Dan has contributed to the planning and design of nuclear power facilities while spearheading research on integrating non-destructive inspection techniques—especially infrared thermography—into plant systems to detect structural anomalies without operational interruptions. Known for his analytical thinking, precision, and interdisciplinary approach, he collaborates with engineers, material scientists, and safety analysts to deliver reliable, innovative design solutions aligned with stringent safety regulations. His research interests center on advancing inspection technologies, modeling structural behavior under thermal and seismic loads, and exploring AI-driven predictive maintenance systems to enhance safety and efficiency in nuclear infrastructure. Though early in his career, Dan has already earned recognition for his innovative contributions, including commendations for his thesis on resilient energy infrastructure and praise from senior engineers for merging theoretical concepts with practical design solutions.

Profile : ORCID

Featured Publication 

Uchimura, D. (2024). Application of infrared thermography for non-destructive structural inspection in nuclear power facilities. Journal of Structural Engineering and Technology.

Uchimura, D. (2023). Resilient architectural design framework for nuclear power plants. International Journal of Sustainable Energy Infrastructure.

Uchimura, D. (2023). Computational modeling of seismic loads in nuclear plant structures. Journal of Advanced Structural Engineering.

 

Shangshang Wu | Engineering | Best Researcher Award

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Dr. Shangshang Wu | Engineering | Best Researcher Award

Tianjin university | China

Wu Shangshang is a mechanical engineer pursuing her Ph.D. at the School of Mechanical Engineering, Tianjin University in China, where she also completed her B.S. and M.S. in Mechanical Engineering. Her research focuses on underwater gliders, emphasizing hydrodynamic identification, motion behavior analysis, and front-end data processing for acoustic communication. Since her master’s studies, she has worked as a graduate researcher, contributing to both experimental sea trials and theoretical modeling, and has published journal articles and conference papers in marine robotics, acoustics, and signal processing. Wu’s doctoral work advances model-based and data-driven methods to improve hydrodynamic prediction and control under uncertain underwater conditions, supporting the development of reliable seabed vehicles and underwater communication systems. She collaborates closely with colleagues at Tianjin University, including researchers such as Guangwei Lv and Shaoqiong Yang, and her early contributions are gaining citations. Her interests also include neural network–based hybrid modeling, online estimation, and mitigating the effects of environmental factors like sea currents and noise on underwater navigation and sensor performance. While no specific awards are publicly documented, Wu shows strong potential in combining experimental insights with computational techniques to enhance the design, control, and stability of underwater gliders.

Profile : Scopus| ORCID  

Featured Publications

AuthorLastName, A. A., & AuthorLastName, B. B. Model and data-driven hydrodynamic identification and prediction for underwater gliders. Physics of Fluids.

AuthorLastName, A. A., & AuthorLastName, B. B. An enhanced variational mode decomposition method for processing hydrodynamic data of underwater gliders. Measurement.

AuthorLastName, A. A., & AuthorLastName, B. B. Multi-body modelling and analysis of the motion platform for underwater acoustic dynamic communication. Applied Mathematical Modelling.

John Devar | Hepatopancreaticobiliary Surgery | Best Researcher Award

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Assoc. Prof. Dr. John Devar | Hepatopancreaticobiliary Surgery | Best Researcher Award

University of Witwatersrand | South Africa

Assoc. John Wesley Samuel Devar is a distinguished Senior Consultant Surgeon at Chris Hani Baragwanath Academic Hospital and a Lecturer at the University of Witwatersrand (Wits), specializing in Hepato-Pancreato-Biliary (HPB) surgery. He has demonstrated unwavering commitment to clinical excellence, surgical education, and mentorship, contributing significantly to the development of HPB surgery services in South Africa. Known for his patient-centered care, meticulous surgical skill, and innovative teaching rooted in Socratic dialogue, he integrates evidence-based medicine with local clinical realities to prepare the next generation of surgeons. Dr. Devar completed his MBBCH at Wits, followed by surgical specialization through the Colleges of Medicine of South Africa and later a Gastroenterology Fellowship. He is currently in the thesis phase of his PhD at Wits. His career began as a General Surgical Registrar in the Pietermaritzburg/Durban Complex, progressing to Consultant at Addington Hospital before joining Chris Hani Baragwanath as a GIT Surgical Fellow and Lecturer. As a Senior Consultant, he has led specialized HPB surgical services, supervised postgraduate training, shaped curricula, and driven surgical innovations at one of the largest hospitals in the Southern Hemisphere. His research focuses on improving outcomes in liver, pancreatic, and biliary surgeries, developing structured training models, and contextualizing global evidence for South African practice. Recognized for his mentorship and educational contributions, including roles with the European-African Hepato-Pancreato-Biliary Association, he has earned accolades for advancing surgical education and inspiring future surgical leaders.

Profile :  Scopus 

Featured Publications

Devar, J. W. S., et al. (2021). Outcomes of ERCP training implementation in a South African tertiary hospital. South African Journal of Surgery.

Devar, J. W. S., et al. (2020). Laparoscopic cholecystectomy training outcomes among surgical residents. World Journal of Surgery.

Devar, J. W. S., et al. (2019). Structured mentorship improves postgraduate surgical outcomes: A South African perspective. BMC Medical Education.

Murat KUL | Sport Science | Best Researcher Award

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Prof. Dr. Murat KUL | Sport Science | Best Researcher Award 

Professor | Bayburt Universty | Turkey 

Prof. Murat Kul is a distinguished academic and researcher in physical education and sports sciences, currently serving as a Professor at Bayburt University’s Faculty of Sport Sciences. With extensive experience, he has made significant contributions to sports education, coaching, and athletic training methodologies, blending practical teaching with rigorous research. His expertise spans leadership in sports, athlete psychology, ethical coaching, and the integration of traditional and modern training techniques. He completed his Bachelor’s in Physical Education and Sports Teaching, a second undergraduate degree in Business Administration, a Master’s in Physical Education and Sports Education focusing on teacher performance, a Ph.D. examining school leadership and teacher experiences, and an associate degree in Emergency and Disaster Management, reflecting a holistic approach to sports, management, and leadership. Professionally, he began as a Research Assistant, progressed through academic roles, and now coordinates programs and supervises over  doctoral theses at Bayburt University. His research interests include sports pedagogy, athlete psychology, coaching effectiveness, ethical leadership, traditional sports, and training methodologies aimed at optimizing performance and motivation. He has been widely recognized for mentoring students, leading national and international projects, and advancing sports sciences through innovative research and teaching. Prof. Kul has 9 documents, cited by 21 documents, with an h-index of 3, establishing him as a thought leader in Turkey and internationally.

Profile:  Scopus | Google Scholar 

Featured Publications 

Kul, M. Life-kinetic exercises’ effects on reaction time, cognitive flexibility, and attention. Bayburt University Thesis. Cited by 2 articles.

Kul, M. Organizational commitment and emotional states of sports federation personnel. Bayburt University Research. Cited by 3 articles.

Kul, M. Ethical leadership and exercise addiction among athletes. Bartın University Research. Cited by 4 articles.

 

 

kirti upadhyay | Biochemistry | Best Researcher Award

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Ms. kirti upadhyay | Biochemistry | Best Researcher Award 

Ms. kirti upadhyay | King George’s Medical University KGMU | India

Kirti Upadhyay is a dedicated Ph.D. Scholar at the Cytogenetics Lab, Centre for Advanced Research, King George’s Medical University (KGMU), Lucknow, Uttar Pradesh. She has a strong passion for genetic research and molecular biology, focusing on chromosomal abnormalities and their clinical applications. With a solid foundation in life sciences, she is advancing her expertise through active participation in training workshops and conferences, enhancing her skills in cytogenetic and molecular biology techniques. Kirti holds a B.Sc. in Life Sciences from Deen Dayal Upadhyay Gorakhpur University and an M.Sc. in Zoology from Maharishi University of Information Technology, Lucknow. She is currently pursuing her Ph.D. in Cytogenetics at KGMU, where she is involved in projects related to molecular diagnostics and genetic research. Her education has been complemented by specialized training in cancer biology, gene cloning, forensic science, basic life support, and advanced statistical analysis. Kirti has gained practical experience in karyotyping, FISH, PCR, cell culture, ELISA, microarrays, and chromatography. She has attended several national and international conferences, which broadened her understanding of genetics and precision medicine. Her research interests include chromosomal abnormalities, molecular markers, cancer genetics, and hematological disorders, with a focus on applying genomic tools for early diagnosis and personalized treatment. Kirti has been recognized for her contributions through certifications, nominations, and active participation in scientific events, demonstrating her commitment to advancing genetic research and improving diagnostic strategies.

Profile : ORCID

Featured Publication 

 

Jingyi Gao | Engineering | Best Researcher Award

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Ms. Jingyi Gao | University of Virginia | United States

Ms. Jingyi Gao | University of Virginia | United States

Jingyi Gao is a Ph.D. candidate in Systems and Information Engineering at the University of Virginia with a 3.75 GPA, focusing on time series prediction, Bayesian probabilistic modeling, and federated learning. She holds an M.S. in Applied Mathematics and Statistics from the Johns Hopkins University (GPA 3.9) and dual bachelor’s degrees in Mathematics–Computer Science and Economics from the University of California, San Diego. Jingyi has extensive teaching experience, serving as a teaching assistant at UVA where she has instructed over 1,000 students across multiple courses in statistical modeling, data mining, AI, and big data systems, and previously supported courses at Johns Hopkins and UC San Diego. She has mentored underrepresented students through the Data Justice Academy and completed research internships at the University of Pittsburgh and Tencent, developing machine learning models for stress detection, healthcare data analysis, and cloud resource forecasting. Jingyi has authored several publications, including work accepted by Pattern Recognition and under review at AAAI and IISE Transactions. Her recent projects involve designing deep latent variable models for ergonomic risk assessment, developing real-time adaptive prediction frameworks for occupational health monitoring, creating federated learning approaches for multi-output Gaussian processes, and modeling behavioral regularity and predictability from multidimensional sensing signals. Combining expertise in machine learning, statistical modeling, and data-driven decision systems, Jingyi aims to advance human-centered intelligent systems through interpretable and privacy-preserving predictive modeling.

Profile: Scopus | Google Scholar

Featured Publications 

Gao, J., Rahman, A., Lim, S., & Chung, S. TimeSets: A real-time adaptive prediction framework for multivariate time series (Manuscript under review at the Association for the Advancement of Artificial Intelligence).

Gao, J., Lim, S., & Chung, S. Gait-based hand load estimation via deep latent variable models with auxiliary information (Manuscript under review at IISE Transactions).

Gao, J., & Chung, S. Federated automatic latent variable selection in multi-output Gaussian processes (Accepted for publication in Pattern Recognition)*.

Gao, J., Yan, R., & Doryab, A. Modeling regularity and predictability in human behavior from multidimensional sensing signals and personal characteristics. Proceedings of the International Conference on Machine Learning and Applications (ICMLA). Institute of Electrical and Electronics Engineers.

Chen, T., Chen, Y., Gao, J., Gao, P., Moon, J. H., Ren, J., … & Woolf, T. B. Machine learning to summarize and provide context for sleep and eating schedules. bioRxiv.

UKBE SIRAYDER | Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Ukbe Sırayder | Neuroscience | Best Researcher Award

Assistant Professor of Physiotherapy and Rehabilitation | Nuh Naci Yazgan University | Turkey

Dr. Ukbe Sırayder is an academic and researcher specializing in physical therapy and rehabilitation, with expertise in cardiorespiratory and pulmonary rehabilitation.they have advanced from Research Assistant to Associate Professor (Doktor Öğretim Üyesi) at Nuh Naci Yazgan University’s Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation. Dr. Şırayder earned a Ph.D. in Cardiopulmonary Rehabilitation from Hacettepe University, following a master’s degree in the same field and a second master’s in Public Law, complementing a Bachelor of Law from Erciyes University. Their professional experience includes teaching courses in pulmonary rehabilitation, exercise physiology, and clinical practice, conducting research projects such as a multidisciplinary home-care study after total knee arthroplasty, and serving in administrative roles including Head of Department (Therapy and Rehabilitation) and Deputy Head of Medical Services & Technical Departments. Their research explores pulmonary and cardiopulmonary rehabilitation, functional capacity, inspiratory muscle training, and respiratory health in post-COVID-19 patients, scoliosis surgery patients, and occupationally exposed populations. Though formal awards are not listed, Dr. Şırayder has received recognition through full-tuition appointment, leadership roles, and frequent acceptance of research in international journals and conferences. Key publications include studies on blue/red light exposure and cognitive performance and on long-term COVID-19 impacts on respiratory function, highlighting their growing impact in rehabilitation research.

Profile: ORCID

Featured Publications

Sırayder, U., Orunoğlu, M., & Yılmaz, O. (2025). Acute effects of blue and red light exposure on cognitive performance, exercise capacity, perceived effort, and dynamic balance: A randomized crossover study. Journal of Exercise Science & Fitness, 23(4), 389–398.

Sırayder, U., İnal İnce, D., Kepenek Varol, B., & Açık, C. (2022). Long-term characteristics of severe COVID-19: Respiratory function, functional capacity, and quality of life. International Journal of Environmental Research and Public Health, 19(10), 6304.