Gabriel Osei Forkuo | Machine Learning | Best Researcher Award

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Mr. Gabriel Osei Forkuo | Machine Learning | Best Researcher Award

Doctoral Researcher/ Research Assistant at Transilvania University of Brasov, Romania

Gabriel Osei Forkuo is a dedicated forestry specialist and researcher with an extensive background in forest operations engineering, postural ergonomics, and machine learning applications. He has built a career that merges practical field experience with academic research, contributing significantly to the development of innovative and cost-effective technologies in forest monitoring and conservation. Currently pursuing a Ph.D. in Forest Operations Engineering at Transilvania University of Brasov, Romania, Gabriel has emerged as a leading figure in the exploration of low-cost LiDAR technologies and smart solutions for ergonomic assessments in forestry. His multifaceted expertise is grounded in over two decades of professional service in teaching, field operations, and advanced scientific investigations.

Profile

Orcid

Education

Gabriel’s educational journey is marked by academic excellence and a continuous drive for specialized knowledge. He is currently enrolled in a Ph.D. program in Forest Operations Engineering at Transilvania University of Brasov, where his research focuses on integrating machine learning and computer vision for ergonomic assessments in forest operations. He previously earned a Master’s degree in Multiple Purpose Forestry from the same university, achieving excellent grades and a cumulative ECTS average of 9.76. His foundational studies include a Bachelor of Science degree in Natural Resources Management from Kwame Nkrumah University of Science and Technology, Kumasi, Ghana, where he graduated with First Class Honours. Earlier academic milestones include completing his GCE A-Level in science subjects and his GCE O-Level in science, supported by performance scholarships recognizing his consistent academic distinction.

Experience

Gabriel’s professional experience spans across teaching, research, and forest management. Between 2002 and 2011, he worked as a Forest Range Manager and Supervisor at the Forestry Commission Ghana, where he was instrumental in nursery planning, restoration of degraded forests, and report writing. From 1999 to 2001, he served as a Science and Maths Teacher at Maria Montessori School in Kumasi, followed by a role as a Teaching Assistant at his alma mater, Kwame Nkrumah University of Science and Technology. In this capacity, he conducted laboratory classes, supervised research data collection, and participated in academic presentations, establishing a strong foundation in both pedagogical and research methodologies. His leadership in afforestation programs and practical forest management further reflects his field-based competency and organizational capability.

Research Interest

Gabriel’s research interests are centered on forest operations engineering, with a special focus on postural ergonomics, machine learning applications, and smart technologies for environmental monitoring. He is passionate about developing affordable and efficient technological solutions, particularly the use of mobile LiDAR and AI-driven tools for soil disturbance estimation and posture evaluation in forest labor. His interdisciplinary approach merges forestry, computer science, and ergonomics, contributing to sustainable and safe forestry practices. Through these interests, he aims to bridge the gap between traditional forestry operations and modern intelligent systems.

Award

Gabriel’s academic and professional contributions have been recognized through several prestigious scholarships and awards. He has twice secured first place in the “My Bachelor/Dissertation Project” competitions held in 2022 and 2023, scoring nearly perfect marks. In 2022, he received the “Premiul special pentru studenti straini” award at the Premiul AFCO. He has also been a recipient of multiple scholarships, including the Transilvania Academica Scholarship, UNITBV Ph.D. Scholarship for International Graduates, and funding from “Proiectul Meu de Diploma” programs. Earlier in his career, he was awarded performance scholarships by the Government of Ghana and Poku Transport Ghana for his outstanding performance in forest sciences.

Publication

Gabriel has authored several notable publications that demonstrate his expertise in forest operations and technological innovation. His key works include:

Forkuo, G.O., & Borz, S.A. (2023). Accuracy and inter-cloud precision of low-cost mobile LiDAR technology in estimating soil disturbance in forest operations. Frontiers in Forests and Global Change, 6. Cited in multiple studies on forest soil impact monitoring.

Forkuo, G.O. (2023). A systematic survey of conventional and new postural assessment methods. Revista Padurilor, 138(3), 1-34.

Borz, S.A., Morocho Toaza, J.M., Forkuo, G.O., Marcu, M.V. (2022). Potential of measure app in estimating log biometrics: a comparison with conventional log measurement. Forests, 13(7), 1028.

Borz, S.A., Forkuo, G.O., Oprea-Sorescu, O., & Proto, A.R. (2022). Development of a robust machine learning model to monitor the operational performance of sawing machines. Forests, 13(7), 1115.

Forkuo, G.O., Proto, A.R., & Borz, S.A. (2024). Feasibility of low-cost mobile LiDAR technology in estimating soil disturbance in forest operations. SSRN.

Forkuo, G.O. (1999). Post-fire tree regeneration studies in the Kumawu Water Supply Forest Reserve. B.Sc. Thesis, KNUST-Kumasi.

Presented paper at FORMEC 2023 in Florence, Italy, highlighting applications of mobile LiDAR in operational environments.

Conclusion

Gabriel Osei Forkuo exemplifies the intersection of academic rigor, practical expertise, and technological innovation in the field of forest operations. His work continues to advance the integration of smart technologies into sustainable forestry, driven by a deep commitment to both ecological preservation and worker safety. Through his research, publications, and leadership roles, Gabriel has built a profile of excellence, contributing significantly to forestry engineering and shaping the next generation of sustainable forest management solutions.

Gang Wang | AI in Healthcare | Best Researcher Award

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Prof. Dr. Gang Wang | AI in Healthcare | Best Researcher Award

Director of The Department of Oncology and Laparoscopy surgery at The First Affiliated Hospital of Harbin Medical University, China 

Dr. Wang Gang is a distinguished general surgeon and postdoctoral researcher specializing in oncology and laparoscopic surgery. As the Director of the Department of Oncology and Laparoscopic Surgery at The First Affiliated Hospital of Harbin Medical University, he has made significant contributions to pancreatic disease research and clinical management. Recognized as a High-Level Talent of Heilongjiang Province, Dr. Wang has received multiple accolades for his pioneering work in acute pancreatitis, demonstrating a strong commitment to advancing surgical procedures and therapeutic strategies.

Profile

Scholar

Education

Dr. Wang earned his medical degree (MD) and doctoral degree (Ph.D.) from Harbin Medical University, where he developed a deep interest in pancreatic disease research. His postdoctoral studies further strengthened his expertise in surgical oncology, focusing on minimally invasive procedures and translational medicine. With a strong foundation in both clinical and academic research, he has cultivated a reputation for excellence in gastrointestinal and pancreatic surgery.

Experience

With years of clinical practice and research experience, Dr. Wang has played a pivotal role in advancing laparoscopic and minimally invasive surgical techniques. He has served as a principal investigator on numerous national and provincial research projects and has mentored numerous postgraduate students in the field of pancreatic disease. His leadership roles include Vice Chair positions in several prestigious medical committees, further demonstrating his influence in surgical oncology and digestive diseases. As a widely respected clinician, he has successfully performed complex surgical interventions, improving patient outcomes through precision and innovation.

Research Interests

Dr. Wang’s research is centered on the molecular mechanisms underlying pancreatic diseases, with a particular focus on acute pancreatitis and pancreatic cancer. His work has explored ferroptosis, necroptosis, mitochondrial autophagy, and exosomal miRNA-mediated cell communication in pancreatic pathology. His translational research bridges molecular discoveries with clinical applications, optimizing surgical protocols and therapeutic strategies to enhance patient survival rates and reduce postoperative complications.

Awards

Dr. Wang has been the recipient of several prestigious awards, including multiple Heilongjiang Science & Technology Progress First Prizes (2024, 2021). His innovative research contributions have earned him recognition as an Outstanding Talent of Heilongjiang New Century. He has been honored with more than 14 provincial and national awards, acknowledging his significant impact on pancreatic disease management and surgical advancements.

Publications

Wang G. et al. (2023). “Ferroptosis in Acute Pancreatitis: The Role of Nrf2-Beclin1-Slc7a11 Axis.” Journal of Pancreatic Research, cited by 150.

Wang G. et al. (2022). “Necroptosis and Pancreatic Inflammation: Insights from ATG7-miR-30b-5p/CAMKII Pathway.” Surgical Oncology Journal, cited by 120.

Wang G. et al. (2021). “Mitochondrial Autophagy Imbalance in Acute Pancreatitis: BCL2L1/FUNDC1 Pathway.” Digestive Surgery Research, cited by 110.

Wang G. et al. (2020). “Exosomal miRNA and Pancreatic Inflammation: Crosstalk Between Acinar Cells and Macrophages.” Translational Cancer Research, cited by 95.

Wang G. et al. (2019). “HIF-1α and Metabolic Reprogramming in Acute Pancreatitis.” World Journal of Gastroenterology, cited by 80.

Wang G. et al. (2018). “CHOP/PGAM5/Drp1: A Novel Pathway in Pancreatic Cell Death.” Journal of Clinical Gastroenterology, cited by 75.

Wang G. et al. (2017). “Innovative Surgical Strategies for Pancreatic Necrosis Management.” Journal of Hepatopancreatobiliary Surgery, cited by 60.

Conclusion

Based on his extensive research portfolio, high-impact publications, and numerous accolades, Professor Gang Wang is an exemplary candidate for the Best Researcher Award. His commitment to advancing knowledge in pancreatic diseases, innovative contributions to clinical practices, and leadership in the research community establish him as a leading figure in his field.

Abu Sarwar Zamani | AI in Healthcare | Best Researcher Award

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Dr. Abu Sarwar Zamani | AI in Healthcare | Best Researcher Award 

Asst. Professor | Prince Sattam bin Abdulaziz University | Saudi Arabia

Dr. Abu Sarwar Zamani is a dedicated and disciplined academic and research professional with over 15 years of experience. Specializing in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Data Mining, and the Internet of Things (IoT), he has made significant contributions in both the academic and research fields. His teaching focuses on core computer science subjects, with a particular interest in the integration of emerging technologies such as AI and IoT. His professional journey reflects a passion for knowledge sharing and innovative research, contributing to scientific advancements in computer science and technology. Currently, he serves as an Assistant Professor at Prince Sattam Bin Abdulaziz University, Saudi Arabia, while also working as a Post-Doctoral Fellow at the International Islamic University Malaysia.

Profile

Scholar

Education

Dr. Zamani’s academic foundation includes a Ph.D. in Computer Science from the Pacific Academy of Higher Education and Research University, Udaipur, India, earned in 2019. Prior to his doctorate, he completed a Master of Philosophy in Computer Science (2009) from Vinayak Mission University, Chennai, and a Master of Science in Computer Science (2007) from Jamia Hamdard, New Delhi. His undergraduate studies were in Computer Applications at MCRP, Bhopal, India (2002). This extensive academic background, paired with his continuous pursuit of knowledge, has laid the foundation for his research contributions and teaching success.

Experience

Dr. Zamani has held various academic positions throughout his career. He is currently an Assistant Professor in the Department of Computer Science at Prince Sattam Bin Abdulaziz University in Saudi Arabia, a position he has held since August 2020. In addition to his teaching role, Dr. Zamani serves as a Post-Doctoral Fellow at the International Islamic University Malaysia, where he has been engaged in advanced research since July 2022. Prior to these positions, he worked as a Senior Lecturer at Shaqra University in Saudi Arabia from 2010 to 2016 and as a Lecturer at King Saud University in Riyadh (2009-2010). His academic career began as a Lecturer at Ibne Seena Pharmacy College in India (2007-2009). Over the years, Dr. Zamani has contributed significantly to both the academic and administrative frameworks of these institutions, including curriculum development and research committees.

Research Interests

Dr. Zamani’s research interests lie primarily in AI, ML, Deep Learning, Data Mining, IoT, and their applications in various domains. His work focuses on leveraging machine learning techniques to develop predictive models for healthcare, cybersecurity, and educational services. He has also researched IoT-based systems, contributing to advancements in real-time data analytics for improved decision-making and optimization of resources. His research has garnered attention in areas like automated disease detection, smart health monitoring, and the design of secure and efficient systems for IoT networks.

Awards

Dr. Zamani’s contributions have been recognized both nationally and internationally. He has been granted three international patents from India and Australia, further solidifying his standing as an innovator in the fields of machine learning and IoT-based systems. His patents cover key areas such as machine learning-based prediction systems for heart disease and systems for improving educational services. In addition to his patents, he has served as an academic reviewer for prestigious journals such as Elsevier, Springer, MDPI, and Taylor & Francis.

Publications

Dr. Zamani has published more than 100 papers in SCI, PubMed, and Scopus-indexed journals, as well as two conference papers. Some of his significant publications include:

Zamani, A. S., et al. “Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics.” Biomedical Signal Processing and Control, 2024, Elsevier, DOI: 10.1016/j.bspc.2024.106247.

Zamani, A. S., et al. “The Prediction of Sleep Quality using Wearable-assisted Smart Health Monitoring System based on Statistical Data.” Journal of King Saud University-Science, 2023, Elsevier, DOI: 10.1016/j.jksus.2023.102927.

Zamani, A. S., et al. “Machine Learning Techniques for Automated and Early Detection of Brain Tumor.” International Journal of Next-Generation Computing, 2022, Perpetual Innovation, DOI: 10.47164/ijngc.v13i3.711.

Zamani, A. S., et al. “Cloud Network Design and Requirements for the Virtualization System for IoT Networks.” International Journal of Computer Science and Network Security, 2022, DOI: 10.22937/IJCSNS.2022.22.11.101.

Zamani, A. S., et al. “Towards Applicability of Information Communication Technologies in Automated Disease Detection.” International Journal of Next-Generation Computing, 2022, Perpetual Innovation, DOI: 10.47164/ijngc.v13i3.705.

Akhtar, M. M., Zamani, A. S., et al. “Stock Market Prediction Based on Statistical Data Using Machine Learning Algorithm.” Journal of King Saud University-Science, 2022, Elsevier, DOI: 10.1016/j.jksus.2022.101940.

Prasad, V. D. P., Zamani, A. S., et al. “Computational Technique Based on Machine Learning and Image Processing for Medical Image Analysis of Breast Cancer Diagnosis.” Security and Communication Networks, 2022, Hindawi, DOI: 10.1155/2022/1918379.

Conclusion

Dr. Abu Sarwar Zamani’s career has been marked by a steadfast commitment to advancing knowledge in computer science, particularly in the domains of AI, ML, and IoT. His extensive experience in both teaching and research has made him a key figure in these fields, with numerous published works and patents to his name. As a dedicated educator and researcher, Dr. Zamani continues to make valuable contributions to the academic community and industry, with a focus on developing innovative solutions for healthcare, cybersecurity, and education. His work exemplifies the intersection of technology and human well-being, ensuring that his research has a lasting impact on society.