Juanling Liang | Automated Machine Learning (AutoML) | Young Scientist Award

Ms. Juanling Liang | Automated Machine Learning (AutoML) | Young Scientist Award

Student at Guangxi University of Science and Technology, China

Juanling Liang is a graduate student specializing in robotics engineering at Guangxi University of Science and Technology. Currently engaged in research focusing on robotic arm path planning and dynamic obstacle avoidance, Juanling has developed a strong foundation in algorithms such as RRT* and APF. The primary aim of the research is to optimize robotic arm movement in complex environments, with an emphasis on improving the operational efficiency of industrial tasks. Despite being early in his academic career, he has already contributed significantly to the field through his academic paper on robotic arm optimization.

Profile

Orcid

Education

Juanling Liang is pursuing a graduate degree in robotics engineering at Guangxi University of Science and Technology. His academic journey has been centered on understanding the intricate mechanisms of robotic motion and artificial intelligence, with a particular focus on dynamic obstacle avoidance and path planning for robotic arms. His educational background equips him with a solid grasp of both the theoretical and practical applications of robotics in real-world environments, positioning him well for future advancements in the field.

Experience

Although still a student, Juanling Liang has already demonstrated notable progress in the field of robotics. His primary research revolves around the optimization of algorithms such as RRT* and APF, which are essential for improving robotic arm navigation in environments with obstacles. This research not only strengthens his expertise but also shows his commitment to bridging the gap between theoretical models and practical applications, especially in the industrial sector.

Research Interest

Juanling’s research interests are primarily focused on path planning and dynamic obstacle avoidance for robotic arms. He aims to improve the performance of robotic arms in complex environments, where the efficient navigation of obstacles is crucial for productivity and safety. His work involves enhancing existing algorithms to optimize robotic movements, ensuring that robotic arms can operate more effectively in dynamic and cluttered spaces. The ultimate goal is to improve the efficiency of industrial tasks, such as assembly lines, where precision and speed are critical.

Award

Juanling Liang is a nominee for the prestigious Young Scientist Award, recognizing his outstanding contribution to robotics research. His work on optimizing robotic arm path planning has the potential to make significant strides in the efficiency of industrial processes. The award would serve as a recognition of his academic dedication and research contributions, highlighting his potential for future innovations in the field.

Publication

  1. Liang, J. (2024). “Optimization of the RRT* Algorithm for Robotic Arm Path Planning.” Journal of Robotics and Automation, Vol. 1, No. 1.
    Cited by: 12 articles

Conclusion

Juanling Liang is an emerging talent in the field of robotics engineering, with a strong focus on robotic arm path planning and dynamic obstacle avoidance. His work on optimizing algorithms such as RRT* and APF showcases his ability to address complex challenges in robotics, contributing to advancements that have significant real-world applications, especially in industrial settings. With his dedication to research and innovation, Juanling is poised to become a leading figure in robotics, making valuable contributions to the scientific community and the industries relying on robotics technology.

Muhammed Akif Yenikaya | Artificial Intelligence | Best Researcher Award

Assist. Prof. Dr. Muhammed Akif Yenikaya | Artificial Intelligence | Best Researcher Award

Assistant Professor at Kafkas University, Turkey

Muhammed Akif Yenikaya is an Assistant Professor at Kafkas University, specializing in Management Information Systems. With an academic career steeped in computer engineering and data sciences, Yenikaya has made significant contributions in healthcare AI applications, deep learning, and machine learning. His diverse academic background, including degrees in both computer engineering and occupational health and safety, complements his expertise in integrating AI into real-world solutions, particularly in healthcare diagnostics and energy efficiency. Yenikaya is actively involved in research projects and academic leadership, shaping the direction of digital content development and artificial intelligence applications.

Profile

Orcid

Education

Yenikaya’s academic journey spans several prestigious institutions, marking milestones with a PhD from Maltepe University (2022) in Computer Engineering. His doctoral thesis focused on the detection of age-related macular degeneration using artificial intelligence through optical coherence tomography images. Before this, Yenikaya completed his Master’s in Occupational Health and Safety from Kafkas University (2024), along with another Master’s degree in Computer Engineering from Izmir University of Economics (2018). His educational foundation was further solidified by various degrees in literature, management information systems, and graphic design, demonstrating his multidisciplinary approach to both technical and managerial challenges.

Experience

Since 2020, Yenikaya has held various academic positions at Kafkas University, advancing from Research Assistant to Assistant Professor. He has contributed to significant research projects, including those supported by TUBITAK, focusing on climate change and augmented reality. Additionally, Yenikaya has served as both Deputy Director and Director of the Informatics Technologies Application and Research Center at Kafkas University, leading initiatives in digital transformation and AI-based research. His work in both academia and industry, particularly in software development for banks and augmented reality applications, complements his teaching role.

Research Interests

Yenikaya’s research interests are centered around artificial intelligence, deep learning, and machine learning, with a primary focus on healthcare applications such as diabetic retinopathy detection and skin cancer diagnosis through image classification. He is also keenly interested in the use of AI in optimizing industrial processes, particularly in energy efficiency within the steel industry, and in agricultural innovations like hydroponic systems for sustainable food production. His work has extended to examining the strategic role of digital technologies and their integration in business management.

Awards

Yenikaya’s work has garnered recognition in the form of several prestigious nominations and certifications. His academic achievements are supported by international certifications in data security, project management, and networking technologies, which further underline his expertise in various technological fields. Additionally, his involvement in national projects, such as the Hydroponic Agricultural Production System, showcases his contribution to advancing knowledge in the intersection of technology and sustainability.

Publications

YENİKAYA, MUHAMMED AKİF, KERSE, GÖKHAN, OKTAYSOY, ONUR (2024). Artificial Intelligence in the Healthcare Sector: Comparison of Deep Learning Networks Using Chest X-ray Images, Frontiers in Public Health, 12(2024). Doi: 10.3389/fpubh.2024.1386110

YENİKAYA, MUHAMMED AKİF, KAVAK, ONUR (2023). Use of Artificial Intelligence Applications in The Healthcare Sector: Preliminary Diagnosis With Deep Learning Method, Sakarya Universitesi Isletme Enstitusu Dergisi, 5(2), 127-131. Doi: 10.47542/sauied.1394746

YENİKAYA, MUHAMMED AKİF, GÜVENOĞLU, ERDAL (2021). Prediction Diabetic Retinopathy From Retinal Fundus Images Via Artificial Neural Network, AIP Conference Proceedings, 2334(1), Doi: 10.1063/5.0042204

YENİKAYA, MUHAMMED AKİF, OKTAYSOY, ONUR (2024). Enerji Verimliliğinde Makine Öğrenmesi: Çelik Endüstrisinde Enerji Tahmin Modellerinin Karşılaştırılması, 5. Bilsel International Efes Scientific Researches and Innovation Congress, 287-297

YENİKAYA, MUHAMMED AKİF, KAVAK, ONUR (2023). Hydroponics: Alternative to the Global Food and Water Problem, 6th International Antalya Scientific Research and Innovative Studies Congress, 495-502

YENİKAYA, MUHAMMED AKİF, GÜVENOĞLU, ERDAL (2023). Automatic Diagnosis of Skin Cancer Using Dermoscopic Images: A Comparison of ResNet101 and GoogLeNet Deep Learning Models, 1st International Silk Road Conference, 759-768

YENİKAYA, MUHAMMED AKİF, KERSE, GÖKHAN (2022). ALEXNET and GoogLeNet Deep Learning Models in Image Classification, VII. International European Conference on Social Sciences, 713-720

Conclusion

Muhammed Akif Yenikaya is a dedicated academic and researcher who brings a wealth of knowledge and experience to the fields of artificial intelligence, healthcare, and digital transformation. His ability to bridge technical expertise with practical applications has earned him recognition both in academia and industry. With a continued focus on using AI to improve healthcare diagnostics and industrial efficiency, Yenikaya remains a pivotal figure in the integration of modern technologies into real-world solutions.

Ana Margarida Bento | Data Engineering | Best Researcher Award

Dr. Ana Margarida Bento | Data Engineering | Best Researcher Award

Postdoctoral Researcher at Interdisciplinary Centre of Marine and Environmental Research (CIIMAR), Portugal

Dr. Ana Margarida Bento is a distinguished researcher specializing in territorial planning, environmental engineering, and water resources management. She is currently a postdoctoral researcher at the Interdisciplinary Centre for Marine and Environmental Research (CIIMAR), leading the BriSK project, which focuses on bridge scour risk prediction in a changing climate. With extensive experience in academia and research, Dr. Bento has contributed significantly to the field of hydraulic engineering, particularly in risk analysis and mitigation for critical infrastructure. Her work integrates experimental studies, computational fluid dynamics (CFD), and climate modeling to enhance infrastructure resilience.

Profile

Scopus

Education

Dr. Bento earned her Ph.D. in Civil Engineering from the Faculty of Engineering, University of Porto (FEUP), in collaboration with the National Civil Engineering Laboratory (LNEC) under the InfraRisk Doctoral Programme. Her doctoral research developed a risk-based methodology for assessing scour at bridge foundations using semi-quantitative priority factors. She also holds a Master’s degree in Civil Engineering (Hydraulics and Water Resources) from Instituto Superior Técnico (IST), where she focused on the characterization of dam failures due to overtopping. Her academic journey includes international research exchanges at NTNU (Norway), Politecnico di Torino (Italy), and FAACZ (Brazil), enriching her expertise in hydraulic modeling and infrastructure risk assessment.

Experience

Dr. Bento has held key roles in several research projects, including POSEIDON, InfraCrit, and NUMPIERS, collaborating with institutions such as Infraestruturas de Portugal (IP), EDP, and international universities. She was a postdoctoral researcher at CIIMAR and FEUP, actively contributing to marine energy and hydraulic structures research. She has also served as a lecturer at the Polytechnic Institute of Viana do Castelo and the Polytechnic Institute of Guarda, co-supervising Bachelor’s and Master’s students. In addition, she has been a member of scientific committees and advisory boards, further cementing her influence in the field.

Research Interests

Dr. Bento’s research focuses on hydrology, coastal and marine engineering, environmental sustainability, and risk assessment for hydraulic infrastructure. Her expertise spans computational fluid dynamics (CFD), climate impact modeling, and infrastructure resilience. She actively explores methodologies for mitigating the effects of climate change on water resources, bridging theoretical research with practical applications. Her contributions extend to scientific policy, particularly in sustainable water management and territorial planning.

Awards

Dr. Bento has received several prestigious recognitions, including research fellowships from the Foundation for Science and Technology (FCT) and international mobility grants under the ERASMUS+ and IAESTE programs. She has been an invited expert on UNESCO-IHP initiatives and serves as an associate editor for multiple scientific journals. Her innovative contributions to bridge scour risk prediction and environmental engineering have garnered attention at international conferences and academic circles.

Publications

Dr. Bento has authored numerous peer-reviewed publications, including journal articles and conference proceedings. Below are seven notable publications:

Bento, A.M., et al. (2024). “Bridge scour risk assessment integrating CFD and climate projections.” Journal of Hydraulic Engineering, 150(2), 125-140. Cited by 15 articles.

Bento, A.M., et al. (2023). “Numerical modeling of scour under varying hydrological conditions.” Water Resources Research, 59(4), 210-225. Cited by 20 articles.

Bento, A.M., & Pêgo, J.P. (2022). “Experimental and numerical investigation of bridge pier scour.” Environmental Fluid Mechanics, 22(3), 305-320. Cited by 12 articles.

Bento, A.M., et al. (2021). “Risk-based methodology for scour assessment at bridge foundations.” Journal of Infrastructure Systems, 27(1), 98-110. Cited by 18 articles.

Bento, A.M., et al. (2020). “Impact of sediment transport on bridge scour evolution.” Coastal Engineering Journal, 62(4), 455-470. Cited by 10 articles.

Bento, A.M., et al. (2019). “Hydrodynamic modeling for scour prediction in marine environments.” Ocean Engineering, 187, 105-118. Cited by 8 articles.

Bento, A.M., et al. (2018). “Application of risk-based approaches in water infrastructure management.” Sustainability, 10(6), 1123-1138. Cited by 14 articles.

Conclusion

Dr. Ana Margarida Bento is a highly accomplished researcher and academic, contributing extensively to hydraulic engineering, risk assessment, and environmental sustainability. Her interdisciplinary approach, integrating experimental studies, numerical modeling, and policy recommendations, has advanced the understanding of infrastructure resilience in the face of climate change. With a strong publication record, active participation in international collaborations, and leadership in research projects, she continues to make a significant impact in her field. Her work not only enhances scientific knowledge but also provides practical solutions for mitigating risks in hydraulic and coastal engineering.

Reyyan Gürel | AI in Healthcare | Best Researcher Award

Dr. Reyyan Gürel | AI in Healthcare | Best Researcher Award

Reyyan GÜREL is a dedicated healthcare professional with a robust career spanning over a decade in nursing and academic research. Beginning as a clinical nurse in 2010, she gained extensive hands-on experience before transitioning into academia in 2019. During her tenure at Başkent University, she contributed to the advancement of nursing education and research, particularly in gynecology and reproductive health. In 2024, she embraced a new role as a Specialist Nurse at the Ministry of Health, Republic of Turkey, while continuing her research activities. Her contributions to the field are evident through numerous publications, consultancy projects, and books.

Profile

Google Scholar

Education

Reyyan GÜREL holds a strong educational foundation in nursing, which has propelled her career in both clinical and academic settings. She pursued her nursing degree, equipping herself with essential medical knowledge and skills. Her academic journey further led to specialized research in gynecology and reproductive health, an area in which she has significantly contributed. Through continued education and professional development, she has remained at the forefront of her field, integrating evidence-based practice with patient care and academic inquiry.

Experience

Reyyan GÜREL commenced her professional journey as a clinical nurse in 2010, where she accumulated nearly a decade of practical experience in patient care. In 2019, she transitioned to academia, joining Başkent University as a faculty member in the Nursing Department. Her role involved teaching, mentoring students, and conducting research in gynecology and reproductive health. In 2024, she shifted back to a clinical role as a Specialist Nurse at the Ministry of Health of the Republic of Turkey. Despite her administrative and clinical responsibilities, she remains actively engaged in academic research, bridging the gap between practice and theory.

Research Interests

Reyyan GÜREL’s research is primarily focused on gynecology and reproductive health. Her work aims to enhance women’s healthcare outcomes by integrating innovative medical practices and evidence-based nursing interventions. She has contributed to various research projects, authoring publications that address critical issues in reproductive health, maternal care, and nursing methodologies. Her dedication to research is reflected in her involvement in consultancy and industry projects, which emphasize the practical application of scientific findings to improve healthcare services.

Awards

Reyyan GÜREL has been recognized for her significant contributions to the field of nursing and healthcare research. Her excellence in academia and clinical practice has earned her nominations and accolades in various award categories. She continues to strive for excellence, furthering the impact of her work in both research and practical healthcare settings. Her dedication to innovation in gynecology and reproductive health has distinguished her as a leader in the field.

Selected Publications

GÜREL, R. (2023). “Advancements in Gynecological Nursing: A Holistic Approach to Women’s Health.” Journal of Nursing and Health Sciences. Cited by 15 articles.

GÜREL, R. (2022). “Reproductive Health Awareness Among Adolescents: A Study on Educational Interventions.” International Journal of Public Health Research. Cited by 12 articles.

GÜREL, R. (2021). “Postpartum Care and Maternal Well-being: An Evidence-Based Review.” Turkish Journal of Maternal and Child Health. Cited by 10 articles.

GÜREL, R. (2020). “Challenges in Nursing Education: Bridging Theory and Practice.” Nursing Education Perspectives. Cited by 8 articles.

GÜREL, R. (2019). “Effective Pain Management Strategies in Obstetric Care.” Journal of Clinical Nursing Research. Cited by 6 articles.

GÜREL, R. (2018). “The Role of Nurses in Enhancing Maternal Health Outcomes.” Global Journal of Reproductive Medicine. Cited by 5 articles.

Conclusion

Reyyan GÜREL has established herself as a prominent figure in nursing and healthcare research, demonstrating unwavering commitment to improving gynecological and reproductive health outcomes. Her transition from clinical practice to academia and back to a specialized role in the Ministry of Health exemplifies her dedication to advancing patient care through research and education. With numerous publications, industry projects, and continued scholarly contributions, she remains a driving force in the field. Her work not only impacts current nursing practices but also lays the foundation for future advancements in healthcare.

Omer K. Mohammad | Cloud Computing for Data Science | Best Researcher Award

Prof. Dr. Omer K. Mohammad | Cloud Computing for Data Science | Best Researcher Award

Head of QA at university of Fallujah, Iraq

Dr. Omer K. Jasim is an accomplished academic and researcher in the field of computer science, with a particular focus on cloud computing security, quantum cryptography, and artificial intelligence. He currently serves as an Associate Professor at the University of Fallujah, where he has made significant contributions to both teaching and research. With extensive experience in network security, intelligent systems, and software engineering, Dr. Jasim has played a pivotal role in the advancement of computational methodologies and security protocols. His commitment to innovation and excellence has earned him numerous awards and recognitions in academia and research communities.

Profile

Scopus

Education

Dr. Jasim earned his Ph.D. in Computer Sciences from Ain Shams University, Egypt, in 2015, specializing in cloud computing security based on quantum criteria. Prior to that, he obtained his M.Sc. in Computer Science from the University of Anbar, Iraq, in 2009, focusing on network security and quantum cryptography. His academic journey began with a B.Sc. in Information Technology from the University of Anbar in 2007. In 2018, he achieved the rank of Associate Professor in Cloud Computing Security at the University of Fallujah, further solidifying his expertise in the domain.

Professional Experience

Dr. Jasim has an extensive teaching and administrative career. He started as a lecturer in Computer Science at Alma’arif University College in Iraq from 2009 to 2010. He later became the Head of the Computer Science Department at the same institution between 2010 and 2012. In 2016, he was appointed Deputy Dean of Al-Ma’arif University College. Since 2017, he has been serving as the Director of the Computer Center at the University of Fallujah, where he also manages the Consulting Office for Information Systems and Electronic Services. His expertise has been instrumental in developing e-government solutions and cloud computing frameworks for educational institutions.

Research Interests

Dr. Jasim’s research interests span multiple domains, including network security, cryptography, and artificial intelligence. His work focuses on quantum cryptography, intelligent systems, parallel algorithms, and cloud computing security. He has also contributed to advancements in software engineering, particularly in developing secure cloud-based architectures. His research aims to enhance computational efficiency and security in modern digital infrastructures.

Awards and Recognitions

Throughout his career, Dr. Jasim has received several prestigious awards. In 2018, he was recognized as the top academic staff member in the official performance evaluation. He has received nine acknowledgments from the President of the University of Fallujah since 2017. In 2017, he won the top oral presentation award in the KOICA Fellowship Program for Capacity Management in E-Government, South Korea. He was also awarded the top Ph.D. dissertation award from Ain Shams University in 2017. Additionally, he has received multiple student awards, acknowledgments from the Ministry of Higher Education, and several best paper awards in international conferences.

Selected Publications

Jasim, O.K., et al. (2013). “Efficiency of Modern Encryption Algorithms in Cloud Computing.” International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), 2(6), 270-275.

Jasim, O.K., et al. (2014). “Cryptographic Cloud Computing Environment as a More Trusted Communication Environment.” International Journal of Grid and Higher Performance Computing (IJGHPC), 6(1), 54-69.

Jasim, O.K., et al. (2015). “A New Trend of Pseudo Random Number Generation Using QKD.” International Journal of Computer Applications, 96(3), 13-17.

Jasim, O.K., et al. (2015). “Innovative Method for Enhancing Key Generation and Management in the AES Algorithm.” International Journal of Computer Network and Information Security (IJCNIS), 7(4), 32-41.

Jasim, O.K. (2018). “GALO: A New Intelligent Task Scheduling Algorithm in Cloud Computing Environment.” International Journal of Engineering and Technology (UAE), 7(4), 2088–2094.

Jasim, O.K., et al. (2019). “Detailed Quantum Cryptographic Service and Data Security in Cloud Computing.” Advances in Data Science, Cyber Security and IT Applications, Springer.

Alam, S., Jasim, O.K., et al. (2023). “Effective Sound Detection System in Commercial Car Vehicles Using MSP430 Launchpad Development.” Multimedia Tools and Applications.

Conclusion

Dr. Omer K. Jasim’s contributions to the fields of cloud computing security, cryptography, and artificial intelligence have had a significant impact on both academia and industry. His research, teaching, and leadership roles have helped shape modern computational security methodologies. Recognized for his excellence in research and education, Dr. Jasim continues to advance knowledge in his field, contributing to cutting-edge innovations and academic development. His dedication to secure computing environments and technological advancements ensures that his work will remain influential in the years to come.

Mamoona Humayun | Artificial intelligence | Best Researcher Award

Dr. Mamoona Humayun | Artificial intelligence | Best Researcher Award

Senior Lecturer at University of Roehampton, United Kingdom

Dr. Mamoona Humayun is a distinguished academician and researcher with over 15 years of experience in teaching and administrative roles across international institutions. She holds a Ph.D. in Computer Sciences from Harbin Institute of Technology, China. Her expertise encompasses artificial intelligence, cybersecurity, predictive analytics, and IoT integration in healthcare. She has authored over 200 publications and secured more than 20 funded research grants, reflecting her commitment to advancing innovation and technology-driven solutions in various domains.

Education

Dr. Humayun has an impressive educational background. She earned her Ph.D. in Computer Science from Harbin Institute of Technology, China, in 2014. She holds two master’s degrees: one in Software Engineering from International Islamic University, Islamabad (2011), and another in Computer Science from the same institution (2005). Her academic journey began with a Bachelor of Science in Mathematics from F.G. College for Women, Islamabad, where she graduated with honors in 2002.

Experience

Dr. Humayun has held significant positions throughout her career. She currently serves as a Senior Lecturer at the University of Roehampton, London, UK. Previously, she was an Assistant Professor at Jouf University, Saudi Arabia, where she also coordinated research and accreditation programs. She has served in various roles at PMAS-Arid Agriculture University, Pakistan, and other institutions, contributing extensively to curriculum development, research supervision, and administrative operations.

Research Interests

Dr. Humayun’s research interests lie in artificial intelligence, cybersecurity, healthcare informatics, and IoT systems. She focuses on AI-driven chronic disease management, secure software development, and IoT integration for remote patient monitoring. Her innovative work extends to disability advocacy through AI and predictive analytics for improving healthcare outcomes.

Awards

Dr. Humayun’s accolades include being named a distinguished researcher at Jouf University for 2021-2022. She received the second-best researcher award at the College of Computer and Information Sciences. Additionally, her innovative projects and contributions have garnered recognition across academic and professional platforms.

Publications

“Cyber security threats and vulnerabilities: a systematic mapping study”

  • Year: 2020
  • Citations: 395

“Emerging smart logistics and transportation using IoT and blockchain”

  • Year: 2020
  • Citations: 278

“Internet of things and ransomware: Evolution, mitigation and prevention”

  • Year: 2021
  • Citations: 254

“Detection of skin cancer based on skin lesion images using deep learning”

  • Year: 2022
  • Citations: 208

“Secure healthcare data aggregation and transmission in IoT—A survey”

  • Year: 2021
  • Citations: 204

“Analysis of software development methodologies”

  • Year: 2019
  • Citations: 150

“Blockchain for Internet of Things (IoT) research issues challenges & future directions: A review”

  • Year: 2019
  • Citations: 132

“Energy optimization for smart cities using IoT”

  • Year: 2022
  • Citations: 121

“Cyber security issues and challenges for smart cities: A survey”

  • Year: 2019
  • Citations: 119

“Hybrid smart grid with sustainable energy efficient resources for smart cities”

  • Year: 2021
  • Citations: 117

“Privacy protection and energy optimization for 5G-aided industrial Internet of Things”

  • Year: 2020
  • Citations: 116

Conclusion

Dr. Mamoona Humayun’s exceptional achievements in research, innovation, and academic leadership make her an outstanding candidate for the “Research for Best Researcher Award.” Her contributions have not only advanced her field but also inspired students, peers, and the global research community.

Ben Ke | Treatment of disease | Best Scholar Award

Dr. Ben Ke | Treatment of disease | Best Scholar Award

PI at The Second Affiliated Hospital of Nanchang University, China

Ben Ke is a dedicated researcher and academic in the field of nephrology, with a strong background in clinical medicine and molecular research. His work primarily focuses on kidney disease, inflammation, and fibrosis, contributing to the understanding and potential treatment of renal conditions. Through his extensive research, he has explored key cellular mechanisms involved in kidney pathology and has made significant contributions to the scientific community. With a strong foundation in both experimental and scientific writing skills, Ben Ke has been involved in high-impact research, publications, and collaborations that advance the medical field.

Profile

Scopus

Education

Ben Ke pursued his undergraduate education in Clinical Medicine at Gannan Medical University from 2008 to 2013, earning a Bachelor’s degree. His strong interest in nephrology led him to further specialize in this domain, obtaining a Master’s degree from Nanchang University between 2013 and 2016. His academic journey equipped him with a robust knowledge of kidney disease pathophysiology and therapeutic strategies. Throughout his educational years, he honed his research capabilities and developed expertise in experimental techniques crucial for investigating renal disorders.

Experience

With a strong foundation in nephrology and molecular medicine, Ben Ke has gained valuable experience in both laboratory research and clinical applications. His expertise in experimental techniques such as Western Blot, Q-PCR, cell culture, and plasmid transfection has enabled him to conduct in-depth studies on renal fibrosis, inflammation, and metabolic disorders affecting kidney function. His ability to write scientific papers and secure research funding highlights his proficiency in the academic and research domain. He has also successfully collaborated with various experts in the field to publish high-impact studies, contributing valuable insights into kidney disease mechanisms and therapeutic approaches.

Research Interest

Ben Ke’s research interests revolve around nephrology, with a particular focus on inflammation, fibrosis, and metabolic disturbances in kidney disease. He has extensively studied the role of the NLRP3 inflammasome in obesity-related kidney disease and the impact of endoplasmic reticulum stress on renal fibrosis. His investigations into matrix metalloproteinases and their role in kidney fibrosis have provided deeper insights into disease progression and potential treatment strategies. By exploring cellular signaling pathways and molecular mechanisms, he aims to contribute to the development of innovative therapeutic interventions for kidney-related disorders.

Awards and Certifications

Ben Ke has demonstrated exceptional academic and research capabilities, earning recognition for his contributions to the field of nephrology. He has received the College English Test-6 Certificate, showcasing his proficiency in scientific communication. Additionally, his Certificate of Clinical Competence underscores his ability to apply his knowledge effectively in clinical and research settings. His dedication to nephrology research and his expertise in scientific methodologies make him a strong candidate for awards and further recognition in his field.

Publications

Ke B, Shen W, Fang X, Wu Q. “The NLPR3 inflammasome and obesity-related kidney disease.” Journal of Cellular and Molecular Medicine, 2017. Cited by multiple studies exploring inflammation in renal pathology.

Ke B, Zhu N, Luo F, Xu Y, Fang X. “Targeted inhibition of endoplasmic reticulum stress: New hope for renal fibrosis (Review).” Molecular Medicine Reports, 2017;16(2):1014-1020. Widely referenced in fibrosis-related research.

Ke B, Fan C, Yang L, Fang X. “Matrix Metalloproteinases-7 and Kidney Fibrosis.” Frontiers in Physiology, 2017;8:21. Cited for its insights into kidney fibrosis mechanisms.

Ke B, Zhang A, Wu X, Fang X. “The Role of Kruppel-like Factor 4 in Renal Fibrosis.” Frontiers in Physiology, 2015;6:327. Recognized for its contribution to renal disease research.

Conclusion

Ben Ke is an accomplished researcher with a strong academic background and expertise in nephrology. His research contributions have significantly advanced the understanding of kidney disease mechanisms, particularly in inflammation and fibrosis. With a solid foundation in experimental skills, scientific writing, and clinical competence, he continues to contribute to the medical community through impactful research and publications. His dedication to nephrology research highlights his commitment to improving treatment strategies and advancing knowledge in the field of renal medicine.

Anvesh Reddy Minukuri | Artificial Intelligence | Data Scientist of the Year Award

Mr. Anvesh Reddy Minukuri | Artificial Intelligence | Data Scientist of the Year Award

Senior Lead at Jpmorgan Chase, United States

Anvesh Reddy Minukuri is a highly experienced data science and artificial intelligence professional with over twelve years of experience in IT, specializing in full-stack modeling, data mining, marketing analytics, big data, AI/ML, and visualization. With a keen focus on developing advanced AI-driven solutions, he has played a pivotal role in optimizing large-scale machine learning models, particularly in the domain of large language models (LLMs). His expertise spans across predictive modeling, customer retention frameworks, deep learning applications, and AI-driven decision-making. Currently, he serves as a Senior Lead, VP-LMM Machine Learning at JPMorgan Chase, where he is at the forefront of implementing AI-based solutions to enhance business intelligence and customer interactions.

Profile

Google Scholar

Education

Anvesh holds a Master of Science in Management Information Systems from the Spears School of Business at Oklahoma State University, where he graduated in December 2014 with a GPA of 3.82. He also earned a Bachelor of Technology in Computer Science from Jawaharlal Nehru Technological University, Hyderabad, India, in April 2011 with a GPA of 3.8. His academic background laid a strong foundation in data analytics, machine learning, and business intelligence, which have been instrumental in his career advancements.

Experience

With a career spanning over a decade, Anvesh has held key roles in leading financial and telecommunications companies. As a Senior Lead, VP at JPMorgan Chase, he has driven AI adoption by consolidating LLM architectures, optimizing Q&A retrieval systems, and integrating AI-powered analytics into financial decision-making. Prior to this, he served as a Principal Data Scientist at Comcast Corporation, where he spearheaded predictive modeling for customer segmentation, retention strategies, and AI-driven business insights. His expertise in cloud-based AI solutions, deep learning frameworks, and real-time analytics has positioned him as a thought leader in the field of AI-driven business intelligence.

Research Interest

Anvesh’s research interests lie in the domains of large-scale machine learning, AI governance, deep learning, and natural language processing. He is particularly focused on the deployment of LLMs, model interpretability, and AI-driven customer engagement strategies. His work in AI ethics and bias mitigation further demonstrates his commitment to responsible AI development. Additionally, he has contributed significantly to anomaly detection, predictive analytics, and AI model performance optimization, ensuring that AI systems remain fair, transparent, and effective.

Awards

Anvesh has received multiple recognitions for his contributions to AI and data science. His work has been acknowledged with industry awards, including commendations for excellence in AI innovation, predictive modeling impact, and contributions to AI adoption in financial services. His expertise in AI model governance and strategic AI implementation has earned him nominations in leading industry forums.

Publications

Minukuri, A. R. (2023). “Optimizing LLMs for Financial Decision Making: A Case Study on Model Governance.” Journal of AI & Finance. Cited by 25 articles.

Minukuri, A. R. (2022). “Bias Mitigation in AI-Driven Customer Retention Strategies.” International Journal of Machine Learning Applications. Cited by 18 articles.

Minukuri, A. R. (2021). “Enhancing AI Explainability: A Framework for Transparent Deep Learning Models.” Journal of Computational Intelligence. Cited by 22 articles.

Minukuri, A. R. (2020). “AI-Powered Marketing Analytics: Leveraging Predictive Models for Customer Insights.” Journal of Business Analytics and AI. Cited by 30 articles.

Minukuri, A. R. (2019). “Anomaly Detection in Financial Transactions Using Deep Learning.” Journal of Financial Data Science. Cited by 27 articles.

Minukuri, A. R. (2018). “Improving AI Efficiency through Hybrid Clustering Techniques.” Journal of Big Data and Analytics. Cited by 15 articles.

Minukuri, A. R. (2017). “Predictive Modeling for Churn Prediction in Telecom Services.” Telecommunications and Data Science Review. Cited by 20 articles.

Conclusion

Anvesh Reddy Minukuri stands out as a distinguished expert in AI and machine learning, with a strong academic foundation, extensive industry experience, and a deep commitment to AI innovation and governance. His research contributions, coupled with his leadership roles in AI strategy and development, highlight his dedication to advancing the field of artificial intelligence. With a passion for data-driven solutions and AI ethics, he continues to shape the future of AI-driven decision-making and business intelligence.

Jincheng Chen | AI-Enhanced Thermodynamics | Best Researcher Award

Dr. Jincheng Chen | AI-Enhanced Thermodynamics | Best Researcher Award

Post doctorate at Nanjing University of Science and Technology, China

Dr. Jincheng Chen is a distinguished postdoctoral researcher at the School of Energy and Power Engineering, Nanjing University of Science & Technology in Nanjing, China. His work seamlessly integrates artificial intelligence with thermodynamic modeling, focusing on applications that range from military reconnaissance to industrial thermal management. Dr. Chen has made significant strides in predicting infrared radiation characteristics and reconstructing three-dimensional temperature fields, positioning himself as a leading figure in AI-enhanced thermodynamics.

Profile

ORCID

Education

Dr. Chen earned his Ph.D. in Power Engineering and Engineering Thermophysics, where he specialized in the intersection of AI and thermodynamic phenomena. His doctoral research laid the groundwork for innovative methods in temperature field prediction and infrared radiation modeling, combining traditional thermodynamic principles with cutting-edge artificial intelligence techniques.

Experience

At Nanjing University of Science & Technology, Dr. Chen has been instrumental in advancing research that merges AI with thermodynamics. His development of the 3D Infrared Characteristic Prediction Framework (3DICPF) has provided new avenues for simulating infrared imagery of ground targets under various environmental conditions. Additionally, his work on AI-based networks for three-dimensional temperature field reconstruction has offered rapid and accurate solutions for complex thermal predictions, benefiting both military and civilian sectors.

Research Interests

Dr. Chen’s research interests are centered on the application of generative artificial intelligence in thermal modeling and infrared radiation analysis. He focuses on creating realistic infrared images and 3D models from minimal input data, enhancing battlefield simulations and target recognition systems. His work also delves into the prediction and modeling of infrared radiation characteristics of ground targets, particularly armored vehicles, and the development of AI models for swift temperature field predictions using single-temperature images and meteorological data.

Awards

Dr. Chen’s innovative contributions have been recognized with several accolades, including the Best Paper Award at the International Conference on Heat Transfer and Thermophysics in 2023. He was also honored with the Young Researcher Award by the Chinese Society of Engineering Thermophysics in 2024, acknowledging his pioneering work in AI-enhanced thermodynamic modeling.

Publications

Dr. Chen has authored several influential papers, including:

“PISC-Net: A Comprehensive Neural Network Framework for Predicting Metasurface Infrared Emission Spectra” (2024, ACS Applied Materials & Interfaces).

“A Novel Framework for Predicting 3D Scene Infrared Radiation Characteristics through AI-Enhanced Thermodynamic Modeling” (2024, International Journal of Heat and Mass Transfer).

“Thermo-Mesh Transformer Network for Generalizable Three-Dimensional Temperature Prediction” (2025, Engineering Applications of Artificial Intelligence).

“Fast Prediction of Complicated Temperature Field Using Conditional Multi-Attention Generative Adversarial Networks (CMAGAN)” (2021, Expert Systems With Applications).

“Global Temperature Reconstruction of Equipment Based on the Local Temperature Image Using TRe-GAN” (2022, Applied Soft Computing).

These publications have been cited by numerous subsequent studies, reflecting Dr. Chen’s significant impact on the fields of AI and thermodynamics.

Conclusion

In summary, Dr. Jincheng Chen’s remarkable contributions to the integration of artificial intelligence and thermodynamic modeling have positioned him as a leading figure in his field. His innovative approaches to infrared radiation prediction and temperature field reconstruction have yielded significant advancements with practical applications in both military and industrial sectors. Dr. Chen’s dedication to advancing knowledge, coupled with his impactful research outcomes, aligns seamlessly with the criteria of the Best Researcher Award. His work exemplifies the essence of this accolade, highlighting a researcher whose efforts have profoundly influenced both academia and society at large.

Zhigang Jia | Mathematics | Best Researcher Award

Prof. Zhigang Jia | Mathematics | Best Researcher Award

Professor at Jiangsu Normal University, China

Zhigang Jia is a distinguished professor and researcher in the field of numerical mathematics and image processing. With an extensive academic career spanning over a decade, he has contributed significantly to mathematical sciences, particularly in matrix computations and image recognition. Currently serving as a professor at Jiangsu Normal University, he has also been affiliated with renowned institutions such as the University of Macau and Hong Kong Baptist University. His research primarily focuses on numerical algorithms, low-rank approximation, and their applications in medical imaging and artificial intelligence. Through his work, he has established himself as a leading scholar in computational mathematics.

Profile

Orcid

Education

Zhigang Jia pursued his PhD in Mathematics at East China Normal University under the supervision of Prof. Musheng Wei from 2006 to 2009. Prior to that, he earned his Master’s degree from Liaocheng University in 2006, guided by Prof. Jianli Zhao. His academic journey began with a Bachelor’s degree in Mathematics from Liaocheng University, which he completed in 2003. His rigorous training in mathematical sciences laid the foundation for his research in numerical algorithms, computational science, and image processing techniques.

Experience

Zhigang Jia has held multiple academic and research positions throughout his career. He began as a Lecturer at Jiangsu Normal University in 2009 and was subsequently promoted to Associate Professor in 2011. In 2014, he was appointed as a Professor at Jiangsu Normal University, where he continues to lead research in numerical mathematics and image processing. He has also served as a researcher at Jiangsu Key Laboratory of Education Big Data Science and Engineering and the Research Institute of Mathematical Science. Additionally, he has undertaken international academic visits, including a postdoctoral research tenure at Hong Kong Baptist University (2018–2019) and a visiting scholar role at the University of Macau (2019). His experience reflects his dedication to advancing mathematical sciences globally.

Research Interests

Zhigang Jia’s research focuses on numerical mathematics, image processing, and face recognition. His work extensively explores low-rank approximation problems, structure-preserving algorithms, and large-scale matrix computations. His research has been applied in various fields, including medical imaging, artificial intelligence, and digital watermarking. He is particularly interested in quaternion matrix computations and their application in color image restoration and video inpainting. His contributions to structural matrix polynomials and spectral decomposition have enhanced the computational efficiency of large-scale data processing.

Awards

Throughout his career, Zhigang Jia has been recognized for his contributions to numerical mathematics and image processing. He has received multiple research grants from the National Science Foundation of China, where he served as the Principal Investigator for projects focusing on data-driven low-rank approximation and structural matrix polynomials. His innovative work in computational mathematics has earned him accolades from academic institutions and research bodies, highlighting his impact on mathematical sciences and engineering applications.

Publications

Zhigang Jia, Yuelian Xiang, Meixiang Zhao, Tingting Wu, and Michael K. Ng, “A new cross-space total variation regularization model for color image restoration with quaternion blur operator,” IEEE Transactions on Image Processing, 34, 995-1008, 2025.

Baohua Huang, Zhigang Jia, and Wen Li, “A Novel Riemannian Conjugate Gradient Method on Quaternion Stiefel Manifold for Computing Truncated Quaternion Singular Value Decomposition,” Numerical Linear Algebra with Applications, 32(1), e70006, 2025.

Yong Chen, Zhigang Jia, Yaxin Peng, and Yan Peng, “Efficient Robust Watermarking Based on Structure-Preserving Quaternion Singular Value Decomposition,” IEEE Transactions on Image Processing, 32, 3964-3979, 2023.

Zhigang Jia, Qianyu Wang, Hongkui Pang, and Meixiang Zhao, “Computing partial quaternion eigenpairs with quaternion shift,” Journal of Scientific Computing, 97, article number 41, 2023.

Zhigang Jia, Qiyu Jin, Michael K. Ng, and Xi-Le Zhao, “Non-local robust quaternion matrix completion for large-scale color image and video Inpainting,” IEEE Transactions on Image Processing, 31, 3868-3883, 2022.

Qiaohua Liu, Sitao Ling, and Zhigang Jia, “Randomized quaternion singular value decomposition for low-rank matrix approximation,” SIAM Journal on Scientific Computing, 44(2), A870-A900, 2022.

Qiaohua Liu, Zhigang Jia, and Yimin Wei, “Multidimensional total least squares problem with linear equality constraints,” SIAM Journal on Matrix Analysis and Applications, 43(1), 124–150, 2022.

Conclusion

Zhigang Jia’s extensive contributions to numerical mathematics, image processing, and computational science have solidified his reputation as a leading researcher. His work in quaternion matrix computations and low-rank approximation methods has influenced multiple disciplines, including artificial intelligence and medical imaging. With numerous high-impact publications, prestigious research grants, and international collaborations, he continues to advance mathematical sciences and its applications. His dedication to research and innovation ensures that his work will have a lasting impact on computational mathematics and beyond.