Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Posted on by ScienceFather

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Brunel University of London | United Kingdom

Mr. Ahmet Serhat Yildiz is an emerging researcher in sensing technology with growing expertise in machine learning, deep learning, embedded systems, and multi-sensor fusion, demonstrating strong potential for advanced research roles and academic leadership. He is currently pursuing his PhD in Electronic and Computer Engineering at Brunel University London, where he focuses on real-time object detection, semantic 3D depth sensing, LiDAR–camera fusion, and intelligent autonomous perception systems, aligning closely with sensing applications in robotics, transportation, surveillance, and industrial automation. His academic foundation includes degrees in electronics, electrical engineering, business management, and extensive English language training, providing a multidisciplinary perspective that strengthens his analytical and communication abilities. His professional experience includes roles as a Graduate Teaching Assistant in digital design, embedded systems, and computer architecture, as well as serving as an IoT facilitator, where he mentored learners and contributed to community-oriented technology initiatives. Mr. AHMET SERHAT YILDIZ has developed notable research projects, including FPGA-based embedded game systems, PLC-controlled industrial automation setups, and biomedical sensing circuits for pulse wave velocity measurement, demonstrating strong hands-on engineering skills. His research portfolio includes Scopus-indexed publications on YOLO-based detection models, sensor fusion for autonomous vehicles, and real-time navigation using LiDAR and deep learning frameworks, reflecting his ability to integrate theory with practical sensing applications. His technical skills include Python, PyTorch, embedded C, FPGA development, digital circuit design, PLC programming, and multi-sensor signal processing, enabling him to contribute to both algorithmic and hardware-oriented research environments. His achievements include scholarly publications, increasing citation impact, and recognition through participation in international conferences and multidisciplinary research projects.

Professional Profiles: ORCID | Google Scholar

Featured Publications 

  1. Alkandary, K., Yildiz, A. S., & Meng, H. (2025). A comparative study of YOLO series (v3–v10) with DeepSORT and StrongSORT: A real-time tracking performance study. Electronics.

  2. Tunali, M. M., Yildiz, A., & Çakar, T. (2022). Steel surface defect classification via deep learning. International Conference on Computer Science and Engineering (UBMK).

  3. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). Real-time object detection and distance measurement enhanced with semantic 3D depth sensing using camera–LiDAR fusion. Applied Sciences.

  4. Tunali, M. M., Sayar, A., Aslan, Y., Mutlu, İ., & Çakar, T., including Yildiz, A. (2023). Enhancing quality control in plastic injection production: Deep learning-based detection and classification of defects. International Conference on Computer Science and Engineering (UBMK).

  5. Yıldız, A., Mişe, P., Çakar, T., Terzibaşıoğlu, A. M., & Öke, D. (2023). Spine posture detection for office workers with hybrid machine learning. International Conference on Computer Science and Engineering (UBMK).

  6. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). YOLOv8–LiDAR fusion: Increasing range resolution based on image-guided sparse depth fusion in self-driving vehicles. Lecture Notes in Networks and Systems.

  7. Yildiz, A. S., Meng, H., & Swash, M. R. (2024). A multi-sensor fusion approach to real-time bird’s-eye view navigation: YOLOv8 and LiDAR integration for autonomous systems. Korkut Ata Scientific Research Conference Proceedings.

Dr. Dianhao Zhang | Robot Collaboration Awards | Best Scholar Award

Posted on by ScienceFather

Dr. Dianhao Zhang | Robot Collaboration Awards | Best Scholar Award

Dr. Dianhao Zhang | Robot Collaboration Awards | Nantong University | China

Dr. Zhang Dianhao is a robotics researcher and lecturer at the School of Electrical and Automation Engineering, Nantong University, recognized for his contributions to robot safety control, human–robot collaboration, autonomous navigation, and intelligent manufacturing. He holds a PhD in Robotics from Queen’s University Belfast, where he developed advanced safety–critical control mechanisms and motion-planning frameworks that integrate sensing, perception, and adaptive behavior modeling in human–robot interactive environments. His academic training, strengthened by earlier degrees in electrical engineering, forms a strong foundation for cross-disciplinary research in sensing-driven autonomous systems. Dr. Zhang has accumulated valuable professional experience as a lecturer, postdoctoral researcher, and collaborator in international programs, including participation in a major European research initiative focusing on intelligent and connected mobility. His research interests span human–machine collaboration, safety-critical control using NMPC and ECBF, multi-sensor fusion, deep learning, graph neural networks, autonomous navigation of underwater and aerial robots, intelligent perception, and digital-twin-enabled industrial automation. His technical skills include advanced control algorithm design, deep learning, behavior prediction, multi-robot coordination, digital-twin modeling, and software expertise in C++, Python, MATLAB, ROS, and other development frameworks essential for modern intelligent systems. Dr. Zhang’s academic output includes high-quality publications in IEEE Transactions on Automation Science and Engineering, Machines, the World Electric Vehicle Journal, and Measurement Science and Technology, supported by Scopus-indexed articles and an ORCID-verified portfolio. His achievements also include multiple patents as first inventor, conference presentations at leading robotics and engineering venues, and contributions to international collaborations that bridge advanced sensing, industrial automation, and robotics. His growing scholarly influence and leadership potential are reflected in his ability to integrate sensing technologies with decision-making architectures for complex robotic environments. Dr. Zhang’s awards, recognitions, and invited presentations further demonstrate his emerging standing within the robotics research community. He continues to expand his research scope through intelligent manufacturing applications, deep-sea robotics, safety-aware autonomy, and human-robot collaborative systems.

Professional Profiles: ORCID

Featured Publications 

  1. Zhang, D., Van, M., Sopasakis, P., & McLoone, S. (). Adaptive safety-critical control with uncertainty estimation for human–robot collaboration. IEEE Transactions on Automation Science and Engineering. Published 2024.

  2. Xu, Y., Yan, S., Qi, Y., Ding, Z., & Zhang, D. (). CDIF-Net: Cross-dimensional interactive fusion network with dual-branch attention for pavement crack segmentation. Measurement Science and Technology. Published 2025.

  3. Zhang, D., Van, M., Sopasakis, P., & McLoone, S. (). An NMPC-ECBF framework for dynamic motion planning and execution in vision-based human–robot collaboration. Machines. Published 2025.

  4. Xu, Y., Zhu, S., Zhang, D., Fang, Y., & Van, M. (). Safety–efficiency balanced navigation for unmanned tracked vehicles in uneven terrain using prior-based ensemble deep reinforcement learning. World Electric Vehicle Journal. Published 2025.

Mr. Didier Ngabonziza | Chemical Sensor Awards | Best Research Article Award

Posted on by ScienceFather

Mr. Didier Ngabonziza | Chemical Sensor Awards | Best Research Article Award

Mr. Didier Ngabonziza | Chemical Sensor Awards | Institute of Mountain Hazards and Environment, Chinese Academy of Sciences | China

Mr. Didier NGABONZIZA is a dedicated Rwandan soil scientist whose academic and research trajectory reflects strong commitment to advancing soil physics, water movement, and contaminant-transport studies within environmentally sensitive landscapes. He is completing his Master’s degree in Soil Science at the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, where he previously earned a Bachelor of Science with Honors in Soil Science from the University of Rwanda, building a solid foundation in hydrology, soil structure, ecological restoration, and environmental assessment. Throughout his professional engagement at the Institute of Mountain Hazards and Environment, Mr. Didier NGABONZIZA has gained valuable research experience in laboratory and field-based sensing, soil macropore characterization, contaminant leaching, and water flow modelling, contributing both technically and scientifically to interdisciplinary projects. His research interests lie in soil physics, water and contaminant transport, environmental sensing, hydrological risk evaluation, and the integration of soil-based data to improve ecological resilience in mountainous regions. He has attended major international conferences, including the Belt and Road Forum for Young Scientists, the International Mountain Forum, and specialized symposiums on soil nutrient cycling and gully erosion, which have strengthened his scientific communication abilities and broadened his collaborative networks. His research skills include soil hydraulic-property analysis, environmental sensing interpretation, experimental design, advanced data processing, GIS and modelling applications, and scientific writing supported by his ORCID-linked scholarly record. His peer-reviewed publication in Sustainability demonstrates his ability to conduct impactful work at the interface of soil systems and environmental risks, and his growing citation record reflects increasing academic visibility. Mr. Didier NGABONZIZA has also received multiple training opportunities offered by international experts, further strengthening his technical proficiency in multiphase mass-flow behaviour and ecological restoration approaches. His honors include successful participation in international scientific exchanges and recognition within research teams for reliability, academic rigor, and teamwork.

Professional Profiles: ORCID

Featured Publications 

  1. Ngabonziza, D., Liu, C., Cui, J., Liu, X., Sun, Z., & Zheng, Q. (2025). Macropore characteristics and their contribution to sulfonamide antibiotics leaching in a calcareous farmland Entisol. Citations: 2

Ms. Leiyao Liao | Deep Learning Awards | Best Researcher Award

Posted on by ScienceFather

Ms. Leiyao Liao | Deep Learning Awards | Best Researcher Award

Ms. Leiyao Liao | Deep Learning Awards | Nanjing University Of Posts And Telecommunications | China

Ms. Leiyao Liao is a distinguished researcher and lecturer at the School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, renowned for her contributions to synthetic aperture radar (SAR) image understanding, target recognition, and explainable deep learning. She obtained her Doctorate in Electronic Science and Technology from Xi’an University of Electronic Science and Technology, where she developed a solid foundation in radar signal processing and mechanism-driven neural networks, and her Bachelor of Science from the same institution, focusing on communication and information systems. In her professional career, Ms. Liao has demonstrated exceptional leadership and technical expertise through her involvement in multiple national-level research projects, including those funded by the National Natural Science Foundation of China and the Central Military Commission, where she played key roles in advancing interpretable deep models for radar target analysis. Her primary research interests encompass synthetic aperture radar (SAR) target recognition, explainable deep learning, mechanism-driven neural networks, radar signal processing, and multimodal intelligent sensing, with a particular focus on small object detection and imbalanced recognition in complex environments. Ms. Liao’s research skills include advanced radar data analysis, model interpretability design, and deep probabilistic modeling, complemented by proficiency in simulation, signal processing, and algorithmic optimization. Her impactful body of work includes 16 Scopus-indexed publications, accumulating 187 citations with an h-index of 7, highlighting her growing international recognition. She has published extensively in high-impact journals such as IEEE Transactions on Geoscience and Remote Sensing (TGRS), IEEE Geoscience and Remote Sensing Letters (GRSL), IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), and IEEE Journal of Selected Topics in Signal Processing (JSTSP). Ms. Liao has received multiple academic honors and research commendations for her outstanding contributions to radar intelligence and interpretability, reflecting her dedication to bridging the gap between physical modeling and deep learning.

Professional Profiles: Scopus

Featured Publications 

  1. Liao, L. (2025). Integrated Physically Interpretable Model for SAR Target Recognition. IEEE Geoscience and Remote Sensing Letters. (Citations: 26)

  2. Liao, L. (2025). Research on Collision Access Method for Satellite Internet of Things Based on Bayliss Window Function. Sensors (Basel, Switzerland). (Citations: 0)

  3. Liao, L. (2024). EMI-Net: Interpretable Deep Network for SAR Target Recognition. IEEE Transactions on Geoscience and Remote Sensing. (Citations: 41)

  4. Liao, L. (2024). Based on Physical Solvability: Mechanism-Driven Neural Networks for Radar Target Understanding. Journal of Electronics. (Citations: 18)

  5. Liao, L. (2022). Interpretable Deep Probabilistic Model for HRR Radar Signal and Its Application to Target Recognition. IEEE Journal of Selected Topics in Signal Processing. (Citations: 52)

  6. Liao, L. (2023). Fusion-Based Multimodal SAR Target Classification Using Explainable Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (Citations: 29)

  7. Liao, L. (2023). Mechanism-Driven Deep Learning for Small Object Detection in Complex Radar Scenarios. IEEE Access. (Citations: 21)

Dr. Cristian Dan Pavel | Deep Learning | Best Research Article Award

Posted on by ScienceFather

Dr. Cristian Dan Pavel | Deep Learning | Best Research Article Award 

Dr. Cristian Dan Pavel | Deep Learning | University of Medicine and Pharmacy Grigore T. Popa | Romania

Dr. Cristian Dan Pavel is an accomplished Gastroenterology Specialist and an emerging clinical researcher with a strong academic and professional background in digestive medicine and biomedical sciences. Currently serving at the Dimitrie Castroian Municipal Hospital in Huși, Romania, he brings extensive expertise in hepatology, gastrointestinal imaging, and endoscopic diagnostics. Dr. Cristian Dan Pavel is pursuing his Ph.D. in Histology at the “Grigore T. Popa” University of Medicine and Pharmacy, Iași, where his research focuses on the morphological and biochemical mechanisms underlying gastrointestinal and hepatic disorders. His doctoral work, under the supervision of Prof. Dr. Carmen Zamfir, integrates histological imaging and oxidative stress modeling, bridging fundamental pathology with clinical application. He holds an M.Sc. in Gastroenterology from the University of South Wales, UK, where his thesis explored the risk of hepatocellular carcinoma in patients with chronic hepatitis C treated with direct-acting antivirals. His academic training also includes a postgraduate course in gastroenterology and a Medical Doctor (MD) degree from the same Romanian institution. Professionally, Dr. Cristian Dan Pavel’s clinical journey spans roles as Resident Doctor in Gastroenterology at “Sf. Spiridon” County Clinical Emergency Hospital, Iași, and as a Specialist in Gastroenterology at Dimitrie Castroian Municipal Hospital, where he provides advanced endoscopic diagnostics and evidence-based patient management. His research interests lie in hepatology, antiviral therapy outcomes, oxidative stress in intestinal pathology, and biomedical imaging, often intersecting clinical medicine with computational and experimental analysis. Dr. Pavel has developed advanced research skills in gastrointestinal endoscopy, optical coherence tomography (OCT), histological data interpretation, and systematic review methodology, with publications indexed in Scopus and IEEE-linked medical journals. He has been an active participant and presenter at multiple national and international gastroenterology congresses, reflecting his commitment to scientific exchange and collaboration.

Professional Profiles: ORCID | Scopus 

Featured Publications 

  1. Pavel, C. D. (2024). Facial Anthropometric Assessment: Importance in Ophthalmology and Orthodontics. Citations: 33.

  2. Pavel, C. D. (2024). Variabilities in Retinal Hemodynamics Across the Menstrual Cycle in Healthy Women Identified Using Optical Coherence Tomography Angiography. Citations: 41.

  3. Pavel, C. D. (2023). Hybrid Deep Learning Models for Analyzing Histological Images of the Zebrafish Intestine Under Oxidative Stress. Citations: 29.

  4. Pavel, C. D. (2023). The Relevance of Experimental Models in Assessing the Impact of Oxidative Stress on Intestinal Pathology. Citations: 36.

  5. Pavel, C. D. (2022). Evaluating Fundoscopy as a Screening Tool for Optic Nerve Atrophy in Multiple Sclerosis: An Optical Coherence Tomography (OCT) Comparative Study. Citations: 42.

  6. Pavel, C. D. (2021). Vision and Life Quality: A Comparative Study on Students from Medical Universities. Citations: 27.

  7. Pavel, C. D. (2020). Computer Vision Syndrome: An Ophthalmic Pathology of the Modern Era. Citations: 39.

Dr. Xiaoyan liu | Biosensors Awards | Young Scientist Award

Posted on by ScienceFather

Dr. Xiaoyan liu | Biosensors Awards | Young Scientist Award

Dr. Xiaoyan liu | Biosensors Awards | City University of Hong Kong | Hong Kong

Dr. Xiaoyan Liu, Ph.D is an accomplished researcher and Research Fellow at the City University of Hong Kong, specializing in nanoscience, nanotechnology, biomedical microfluidics, and sensing systems. She earned her Doctor of Science (Ph.D.) in Nanoscience and Nanotechnology from the Academy for Advanced Interdisciplinary Studies, Peking University, under the supervision of Professor Xingyu Jiang, where she developed advanced microfluidic devices for biomedical and neural applications. Her Bachelor of Science in Chemistry from Shandong University laid the foundation for her deep understanding of chemical materials and nanoscale systems. Professionally, Dr. Liu has held research positions at globally recognized institutions, including the Institute for Health Innovation and Technology at the National University of Singapore and the Department of Biomedical Engineering at the Southern University of Science and Technology, China, where she contributed to international projects on organ-on-chip technologies, tumor microenvironments, and soft electronic neural interfaces. Her expertise encompasses flexible e-biochips, wearable biosensors, neural microelectrode design, and nanomaterial toxicity studies. Dr. Liu’s research interests focus on integrating nanomaterials with microfluidic and bioelectronic systems for real-time health monitoring, organoid drug screening, and brain-on-chip development. She has published multiple high-impact papers in IEEE Sensors Journal, Biosensors and Bioelectronics, and ACS Nano, with a growing citation record in Scopus and Google Scholar, demonstrating her scholarly influence. Her research skills include microfabrication, biointerface engineering, electrophysiological recording, and advanced imaging techniques, contributing to cutting-edge applications in smart biomedical systems.

Professional Profiles: ORCID  

Featured Publications

  1. Liu, X. (2024). Tumor Microenvironment Based on Extracellular Matrix Hydrogels for On-Chip Drug Screening. Citations: 52.

  2. Liu, X. (2024). Coupling Nanoscale Precision with Multiscale Imaging: A Multifunctional Near-Infrared Dye for the Brain. Citations: 47.

  3. Liu, X. (2023). Wearable Flexible Microfluidic Sensing Technologies. Citations: 61.

  4. Liu, X. (2023). Bioeffects of Inhaled Nanoplastics on Neurons and Alteration of Animal Behaviors through Deposition in the Brain. Citations: 58.

  5. Liu, X. (2022). A Soft and Absorbable Temporary Epicardial Pacing Wire. Citations: 43.

  6. Liu, X. (2022). Highly Stretchable Metal-Polymer Conductor Electrode Array for Electrophysiology. Citations: 39.

  7. Liu, X. (2021). Integrating a Concentration Gradient Generator and a Single-Cell Trapper Array for High-Throughput Screening the Bioeffects of Nanomaterials. Citations: 65.

Dr. Adelayo Adeoye | Agricultural Investment | Excellence in Research Award

Posted on by ScienceFather

Dr. Adelayo Adeoye | Agricultural Investment | Excellence in Research Award

Dr. Adelayo Adeoye | Agricultural Investment | Oyo State College of Agriculture and Technology, Igbo-Ora | Nigeria

Dr. Adeoye Adelayo is an accomplished academic and professional in the field of Agricultural Economics and Agribusiness Management, currently serving as a Principal Lecturer in the Faculty of Plants and Environmental Sciences. His career reflects an unwavering dedication to teaching, research, and agricultural development. With over a decade of academic experience, he has played a significant role in shaping future agricultural professionals through innovative instruction and project supervision. Dr. Adelayo’s contributions to agribusiness management and cooperative economics have advanced institutional research and enhanced the practical learning experience of students. His academic journey demonstrates a continuous pursuit of excellence and a strong commitment to agricultural transformation, rural development, and sustainable livelihood systems in Nigeria.

Professional Profile

Scopus

Summary of Suitability for the “Excellence in Research Award”

Dr. Adeoye Adelayo demonstrates a strong and progressive academic and professional record that aligns well with the standards of the Excellence in Research Award. With over a decade of teaching and research experience in agricultural economics and agribusiness management, he has significantly contributed to advancing knowledge and student development in the field of agricultural sciences. His academic progression—from a Bachelor’s in Agricultural Economics and Farm Management to a forthcoming Ph.D. in Agricultural Economics—reflects a consistent commitment to scholarly growth and research excellence.

Education

Dr. Adelayo’s educational foundation is rooted in agricultural and economic sciences, complemented by a strong pedagogical background. He obtained his Bachelor’s degree in Agricultural Economics and Farm Management (Second Class Upper Division) from the Federal University of Agriculture, Abeokuta. He went on to earn an M.Sc. in Agricultural Economics and subsequently completed a Master of Philosophy (M.Phil.) in the same discipline from the University of Ibadan, which solidified his expertise in advanced economic modeling and farm management systems. Additionally, he acquired a Postgraduate Diploma in Education (PGDE), demonstrating his proficiency in instructional design and academic administration. His Doctor of Philosophy (Ph.D.) in Agricultural Economics further deepened his analytical skills and research capabilities, focusing on agricultural market structures, value chains, and rural income dynamics. Complementary certifications in computer appreciation and research methods using Stata software have enhanced his research productivity and data analysis proficiency.

Professional Experience

Dr. Adeoye’s professional trajectory within academia has been marked by steady progression through teaching, research, and administrative leadership. Beginning his academic career as a Lecturer III in the Department of Agricultural Technology, he consistently demonstrated excellence in pedagogy and research, which led to his promotion to Lecturer II and later Lecturer I in the Department of Cooperative Economics and Management. His effective management and coordination skills earned him the position of Acting Head of Department, where he implemented academic and administrative reforms that improved departmental efficiency. Currently, as a Principal Lecturer in Agribusiness Management, he teaches both undergraduate and higher national diploma courses, supervises student research projects, and contributes to curriculum development. Beyond teaching, he has served as Admission Officer, Member of the COVID-19 Committee, Chairman of the College Canteen Committee, and an active member of various institutional and faculty-level committees, reflecting his commitment to academic leadership and institutional development.

Research Interests

Dr. Adeoye’s research focuses on agricultural economics, agribusiness value chains, farm management, resource economics, and rural livelihoods. He has a keen interest in the socio-economic factors that influence agricultural productivity, farm profitability, and sustainable agribusiness practices in Nigeria. His work explores the interplay between agricultural policies, value chain integration, and smallholder farmers’ participation in markets. Additionally, his research extends into entrepreneurship in agriculture, microeconomics, and managerial economics, emphasizing how innovative economic strategies can transform agricultural enterprises and improve food security. His analytical approach to research combines quantitative techniques, econometric modeling, and field data interpretation, which he applies to assess policy interventions and agribusiness performance in emerging economies.

Awards and Recognitions

Dr. Adeoye has earned institutional recognition for his academic service, research engagement, and contribution to faculty development. His leadership as a committee member and departmental head has been commended for promoting collaboration, transparency, and academic excellence. He is a registered member of several professional associations, including the Nigerian Association of Agricultural Economists (NAAE), the Agricultural Society of Nigeria (ASN), the Institute of Professional Agriculturists of Nigeria (IPAN), and the Farm Management Association of Nigeria (FMAN). His professional affiliations with organizations such as the Sustainable Livelihoods and Development Network (SLIDEN) and the Teachers Registration Council of Nigeria (TRCN) further signify his credibility and commitment to professional ethics and continuous development.

Publication Top Notes

Impact of conflicts on agricultural crop investment in rural areas: Policy insight from a nationally representative survey dataset

Dr. Goo Bok Jung | Agricultural Sector | Best Scholar Award

Posted on by ScienceFather

Dr. Goo Bok Jung | Agricultural Sector | Best Scholar Award

Dr. Goo Bok Jung | Agricultural Sector | National Institute of Agricultural Sciences | South Korea

Dr. Goo-Bok Jung is a distinguished soil scientist whose extensive career has been dedicated to advancing agricultural sustainability, soil health, and climate change adaptation. As a Senior Researcher at the National Institute of Agricultural Sciences (NIAS) under the Rural Development Administration (RDA), he has played a vital role in shaping Korea’s agricultural environmental policies through research, strategic leadership, and scientific innovation. His contributions span the domains of soil chemistry, heavy metal contamination assessment, water quality monitoring, and climate change impact analysis on agricultural systems. With a deep commitment to improving environmental resilience in agriculture, Dr. Jung has become a key figure in developing data-driven solutions and scientific frameworks that enhance national responses to climate variability and environmental challenges in farming systems.

Professional Profile

ORCID

Summary of Suitability for the “Best Scholar Award” 

Dr. Goo-Bok Jung is an exceptionally accomplished scholar whose extensive research career and leadership in soil science and agricultural environmental management make him an outstanding candidate for the Research for Best Scholar Award. His work exemplifies scholarly excellence, innovation, and a lifelong dedication to advancing sustainable agriculture in the face of global environmental challenges.

Education

Dr. Jung earned his Ph.D. in Agricultural Environment from Dankook University, where his doctoral research focused on the dynamics of heavy metals in soils and their environmental implications. His academic background provided a strong foundation in soil chemistry, environmental pollution control, and sustainable land management. Through his studies, he developed expertise in analytical methods for evaluating soil and water quality and understanding the ecological consequences of anthropogenic contaminants. This education positioned him to lead interdisciplinary research that bridges soil science, environmental protection, and climate adaptation. His scientific curiosity and methodological rigor continue to inform his applied research in environmental sustainability and agricultural policy.

Professional Experience

Dr. Goo-Bok Jung has built a remarkable career within the Rural Development Administration, beginning as a Research Scientist and progressing through multiple leadership roles that reflect his expertise and dedication. During his early career at the RDA and NAAS, he focused on soil chemical property analysis, heavy metal contamination, and the development of environmental indicators for agricultural sustainability. His work contributed to establishing national guidelines for soil and water quality assessment, which continue to serve as references for sustainable agricultural management across Korea.

As Team Leader for the Climate Change Division at NAAS, Dr. Jung spearheaded initiatives to understand and mitigate the effects of climate change on soil ecosystems and agricultural productivity. His leadership in strategic planning enabled the integration of climate resilience into Korea’s agricultural research agenda. Later, as Division Director at the National Institute of Agricultural Sciences, he led the Climate Change Assessment Division, overseeing multidisciplinary research on greenhouse gas emissions, carbon sequestration, and the adaptation of agricultural practices to environmental stressors.

Currently, as Director within the RDA’s New Agriculture Climate Response Program, Dr. Jung manages national-level projects aimed at transforming agricultural systems to withstand future climatic and environmental challenges. His visionary leadership ensures that research outputs are effectively translated into policy and practice, strengthening the sustainability of Korea’s agricultural landscapes and contributing to global environmental goals.

Research Interests

Dr. Jung’s research interests are deeply rooted in soil science, environmental chemistry, and agricultural sustainability. He is particularly focused on the interactions between soil properties, heavy metal behavior, and climate-driven changes in agricultural systems. His work explores the assessment of soil contamination, development of remediation techniques, and creation of environmental quality indicators that guide sustainable land use. In recent years, his research has expanded to include climate change adaptation in agriculture, emphasizing carbon management, soil health improvement, and the development of predictive models for agricultural resilience. By integrating scientific research with policy initiatives, Dr. Jung has contributed to the creation of frameworks that help agricultural communities respond effectively to environmental stress and ensure long-term food security.

Awards

Throughout his distinguished career, Dr. Jung has received numerous recognitions for his scientific excellence and leadership in agricultural environmental research. His achievements have been acknowledged by the Rural Development Administration for advancing soil contamination analysis, developing water quality indicators, and leading national climate response initiatives. His contributions to environmental policy formulation, as well as his mentorship of young researchers, have strengthened Korea’s position as a leader in sustainable agricultural science. His award nomination reflects his lifelong dedication to improving agricultural resilience, fostering climate-smart innovation, and promoting responsible stewardship of natural resources.

Publication Top Notes

Decadal Trends and Spatial Analysis of Irrigation Suitability Indices Based on Groundwater Quality (2015–2024) in Agricultural Regions of Korea
Evaluation of long-term water quality trends and CCME-WQI applicability in agricultural watersheds of Korea
Future phenological changes of Hydrochara affinis and Sternolophus rufipes in agro-ecosystem under climate change scenarios
Proposal of model-based methodologies for assessing climate change vulnerability in agriculture: Focusing on nutrient discharge assessment in agricultural land using a linked APEX and regression model
Evaluation of nutrient losses of the furrow dike system during the cultivation of soybean (Glycine max L.) in paddy fields

Dr. Lauren Rimmel | Health Monitoring | Best Researcher Award

Posted on by ScienceFather

Dr. Lauren Rimmel | Health Monitoring | Best Researcher Award

Dr. Lauren Rimmel | Health Monitoring | Brigham and Women’s Hospital | United States

Dr. Lauren Rimmel, PT, DPT, OCS, CSCS, is a dedicated physical therapist, educator, and researcher whose work bridges orthopedic rehabilitation, health equity, and community-engaged care. With advanced clinical specialization and a passion for social justice in healthcare, she has contributed significantly to the advancement of evidence-based practice and inclusive education in physical therapy. As a Clinical Specialist at Brigham and Women’s Health Center and Adjunct Faculty at the Massachusetts General Hospital Institute of Health Professions, Dr. Rimmel combines clinical expertise with academic mentorship. Her professional philosophy emphasizes patient-centered care, interdisciplinary collaboration, and the promotion of equitable access to rehabilitation services across diverse populations.

Professional Profile

Scopus

Summary of Suitability for the “Best Researcher Award” 

Dr. Lauren Rimmel stands out as an exemplary candidate for the Research for Best Researcher Award, combining advanced clinical expertise, academic scholarship, and a strong commitment to social justice and health equity in physical therapy research. Her scholarly and professional achievements clearly demonstrate the blend of innovation, leadership, and evidence-based practice that this award seeks to recognize.

Education

Dr. Rimmel completed her Doctor of Physical Therapy (DPT) and Bachelor of Science in Exercise Physiology at Marquette University, graduating magna cum laude from both programs. Her foundational education in exercise physiology provided a strong scientific background in human performance, biomechanics, and therapeutic exercise. She later pursued a postdoctoral Physical Therapy Residency in Orthopedics at the Massachusetts General Hospital Institute of Health Professions, where she further honed her clinical skills in managing complex musculoskeletal and neurologic conditions. This rigorous academic and clinical training positioned her as a well-rounded clinician and academic, capable of translating scientific evidence into practical rehabilitation strategies. Through continuing education in vestibular rehabilitation, dry needling, concussion management, and community health equity, she has remained deeply engaged in lifelong learning and advanced clinical development.

Professional Experience

Dr. Rimmel currently serves as a Clinical Specialist in the Outpatient Physical Therapy Department at Brigham and Women’s Health Center, where she manages a broad patient population encompassing orthopedic, vestibular, oncologic, neurologic, antepartum and postpartum, and gender-diverse health cases. Her clinical leadership extends beyond patient care—she is an active contributor to institutional committees focused on Diversity, Equity, and Inclusion (DEI) and the Sports Protocols Team, where she has authored multiple physical therapy rehabilitation guidelines, including those for Biceps Tendon Repair, PCL Reconstruction, OATS, and ACI procedures. Her work on these committees reflects a deep commitment to standardizing high-quality, equitable rehabilitation practices.

Simultaneously, Dr. Rimmel holds a faculty appointment as Adjunct Professor at the MGH Institute of Health Professions, where she contributes to curriculum development and instruction within the Social Justice and Health Equity Thread of the physical therapy program. Her teaching emphasizes the integration of evidence-based care with cultural competence and community awareness. She has led qualitative research, facilitated case-based learning, and guided future clinicians to provide compassionate care to marginalized and housing-insecure populations. Her earlier professional experience includes a Physical Therapy Residency at Massachusetts General Hospital, where she conducted clinical research, mentored peers, and gained valuable experience during the COVID-19 pandemic through service at Boston Hope Hospital with Boston’s Healthcare for the Homeless program.

Research Interests

Dr. Rimmel’s research centers on health inequity, diversity in rehabilitation education, and structural competency in physical therapy practice. She investigates disparities in physical therapy referral and participation, with an emphasis on identifying systemic barriers that contribute to unequal access to care. Her work also examines how culturally and linguistically diverse learners navigate higher education in physical therapy and how educational institutions can leverage community cultural wealth to foster inclusive learning environments. By combining qualitative and quantitative research approaches, Dr. Rimmel advances understanding of the intersection between social determinants of health and rehabilitation outcomes. Her ongoing research aims to transform healthcare education and practice by embedding social justice principles into clinical frameworks.

Awards

Dr. Rimmel’s exceptional contributions to clinical excellence, research, and educational innovation have earned her recognition within the physical therapy and health equity communities. She is a Board-Certified Clinical Specialist in Orthopaedics through the American Board of Physical Therapy Specialties, a certification reflecting her advanced expertise in musculoskeletal rehabilitation. She is also a Certified Strength and Conditioning Specialist through the National Strength and Conditioning Association and a Basic Cardiac Life Support provider. Her professional development includes participation in the Community Health Equity Scholars Program at Cambridge Health Alliance, which further underscores her leadership in community-based healthcare initiatives. Her nomination for this award highlights her distinguished role as a clinician-researcher dedicated to equitable healthcare delivery, diversity advocacy, and clinical excellence.

Publication Top Notes

Investigating Disparities in Physical Therapy Utilization: An Intersectionality Perspective

Mr. Mohamed Hamroun | Healthcare | Breakthrough Research Award

Posted on by ScienceFather

Mr. Mohamed Hamroun | Healthcare | Breakthrough Research Award

Mr. Mohamed Hamroun | Healthcare | XLIM/ University of Limoges | France

Dr. Mohamed Hamroun is an accomplished computer scientist and engineer specializing in artificial intelligence, image processing, and multimodal information retrieval. Currently serving as a researcher and lecturer at the 3iL School and the XLIM Laboratory at the University of Limoges, France, he has made significant contributions to the fields of deep learning, computer vision, and semantic data indexing. His multidisciplinary expertise spans across AI, VR/AR systems, big data analytics, and intelligent information retrieval systems, positioning him as a leading researcher in computational intelligence and multimedia data analysis. Through his work, Dr. Hamroun has advanced both theoretical understanding and practical applications of machine learning and artificial intelligence for complex visual and semantic data challenges.

Professional Profile

Google Scholar

Summary of Suitability for the “Breakthrough Research Award” 

Dr. Mohamed Hamroun is an exceptionally qualified candidate for the Research for Breakthrough Research Award, demonstrating a strong academic foundation, extensive research experience, and impactful scientific contributions in the fields of artificial intelligence (AI), image processing, deep learning, and multimodal information retrieval.

Education

Dr. Hamroun’s academic journey reflects a deep commitment to advancing computer science and AI-driven data analysis. He earned his Ph.D. in Computer Science from the University of Bordeaux, where his doctoral research focused on “Indexing and retrieval by visual, semantic, and multi-level content of multimedia documents,” under the supervision of Professors Henri Nicolas and Ikram Amous. His doctoral work bridged the gap between computational semantics and large-scale multimedia information retrieval. He later completed his Habilitation to supervise research at the University of Limoges, where his postdoctoral contributions were consolidated into a major research theme titled “Contributions to indexing and information retrieval: application to generalist and medical multimodal data,” under the guidance of Professor Damien Sauveron. Before his doctoral studies, he obtained a Computer Engineering degree from the University of Sfax, Tunisia, and a Bachelor’s degree in Computer Science from the same institution. His undergraduate and graduate projects revolved around multilingual search engine development and database management systems, establishing his foundation in applied informatics and intelligent systems.

Professional Experience

Dr. Hamroun’s professional experience demonstrates a steady trajectory of academic excellence and applied innovation. He began his career as an R&D Engineer at SIM-SOFT in Tunisia, where he was involved in software development and data-driven industrial applications. Following this, he pursued his Ph.D. research jointly between the University of Bordeaux and the University of Sfax, working on hybrid semantic and visual content retrieval models. After completing his Ph.D., he joined the XLIM Laboratory at the University of Limoges as a Postdoctoral Researcher, where he focused on the integration of deep learning and ontology-based frameworks for medical and multimedia data analysis. Later, he was appointed as a Lecturer at EILCO Engineering School in France, contributing to both teaching and research in computer science and artificial intelligence. He now holds the position of Associate Professor at 3iL Engineering School, affiliated with the XLIM Laboratory, where he supervises research projects and mentors graduate students in AI, machine learning, and multimedia information systems.

Research Interests

Dr. Hamroun’s research interests cover a wide spectrum of computational and artificial intelligence domains. His core expertise includes image and signal processing, deep learning architectures for data classification and clustering, virtual and augmented reality applications, and semantic data mining. His studies often combine statistical learning, ontology modeling, and multimodal data fusion to enhance human-computer interaction and knowledge extraction. A significant part of his current research focuses on developing intelligent systems for multimodal medical data retrieval and applying AI to improve healthcare diagnostics and decision support. His recent work also extends to federated learning frameworks and semantic interpretation in multimedia environments, bridging applied computer science with real-world AI applications.

Awards

Dr. Hamroun has been recognized for his innovative research in artificial intelligence and multimedia information systems through various academic honors and nominations. His outstanding work in deep learning-based image analysis and computational semantics has earned him recognition among peers in the international AI research community. He has contributed as a co-author to several highly cited papers and participated in collaborative European research projects aimed at integrating AI into real-world industrial and medical systems. His nomination for the award highlights his leadership in combining artificial intelligence with practical problem-solving across domains such as emotion recognition, diabetic foot ulcer diagnosis, and semantic retrieval.

Publication Top Notes

  • Title: Emotion recognition from speech using spectrograms and shallow neural networks
    Authors: A. Slimi, M. Hamroun, et al.
    Year: 2020
    Citations: 47

  • Title: DFU-Siam: A novel diabetic foot ulcer classification with deep learning
    Authors: M. S. A. Toofanee, M. Hamroun, et al.
    Year: 2023
    Citations: 43

  • Title: A survey on intention analysis: successful approaches and open challenges
    Authors: M. Hamroun
    Year: 2020
    Citations: 21

  • Title: An interactive engine for multilingual video browsing using semantic content
    Authors: M. B. Halima, M. Hamroun, et al.
    Year: (arXiv preprint, circa 2013)
    Citations: 16

  • Title: DFU-Helper: Innovative framework for longitudinal diabetic foot ulcer evaluation using deep learning
    Authors: M. S. A. Toofanee, M. Hamroun, et al.
    Year: 2023
    Citations: 11