Amany Elbehary | Health and Medicine | Best Researcher Award

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Dr. Amany Elbehary | Health and Medicine | Best Researcher Award

Assistant lecturer at Department of Clinical Pathology, Faculty of Medicine, Zagazig University, Egypt.

Dr. Amani Mohamed Ibrahim Mohamed is an accomplished Assistant Lecturer in the Department of Clinical Pathology at the Faculty of Medicine, Zagazig University. Born on January 26, 1986, Dr. Amani has established a reputable academic and clinical profile, contributing significantly to the fields of laboratory medicine and diagnostic sciences. She brings a rigorous approach to teaching and research, with a focus on advancing diagnostic accuracy and improving clinical outcomes through innovative laboratory practices. As a dedicated academic professional, Dr. Amani is committed to integrating teaching excellence with active research and community service. Her role at Zagazig University reflects her passion for fostering knowledge in medical laboratory sciences, particularly in clinical pathology. She is recognized among her peers for her meticulous work ethic, collaborative mindset, and dedication to student mentorship. With a robust educational foundation and a growing portfolio of research endeavors, Dr. Amani continues to contribute to the academic and healthcare sectors in Egypt. She maintains active communication with the scientific community through conferences, workshops, and academic collaborations. Her professional journey is driven by a profound interest in bridging the gap between laboratory diagnostics and clinical application, striving to enhance healthcare delivery and patient care through evidence-based medical laboratory practices.

Publication Profile

Google Scholar

Education

Dr. Amani Mohamed Ibrahim Mohamed pursued her academic career with a strong commitment to clinical and biomedical sciences. She obtained her Bachelor of Medicine and Surgery (M.B.B.Ch) from Zagazig University, one of Egypt’s leading medical schools. Following her undergraduate studies, she completed her Master’s degree in Clinical Pathology, also at Zagazig University, which laid the groundwork for her expertise in laboratory medicine. Her academic training emphasized diagnostic hematology, clinical chemistry, immunology, and molecular pathology, providing her with comprehensive knowledge of disease mechanisms and laboratory techniques. During her postgraduate studies, Dr. Amani actively participated in clinical laboratory rotations, case discussions, and academic seminars, which honed her diagnostic acumen and critical thinking abilities. She is currently pursuing her doctoral studies in Clinical Pathology, aiming to deepen her research competencies and clinical applications in hematopathology and laboratory-based diagnostics. Her educational journey has been marked by a continuous pursuit of academic excellence, scientific inquiry, and a passion for improving laboratory diagnostics. In addition to her formal education, Dr. Amani frequently engages in professional development through specialized courses and workshops in areas such as quality assurance, molecular diagnostics, and emerging diagnostic technologies, ensuring her skills remain aligned with modern medical and scientific standards.

Professional Experience

Dr. Amani Mohamed Ibrahim Mohamed serves as an Assistant Lecturer in the Department of Clinical Pathology at the Faculty of Medicine, Zagazig University. Since joining the department, she has played a vital role in academic instruction, laboratory supervision, and clinical teaching. Her responsibilities include delivering lectures and practical sessions to undergraduate and postgraduate students, contributing to curriculum development, and ensuring high standards in laboratory diagnostics. Dr. Amani collaborates closely with hospital laboratories affiliated with the university, where she supports diagnostic services in hematology, clinical chemistry, and immunopathology. She has also participated in multidisciplinary clinical meetings and contributed to case reviews, enhancing the integration of laboratory findings into clinical decision-making. Prior to her current academic role, she completed her residency and training in clinical laboratories, gaining hands-on experience in diagnostic testing, quality control, and patient-centered laboratory reporting. Her professional background combines both academic and clinical expertise, which enhances her ability to deliver practical, evidence-based education. Dr. Amani is also involved in supervising master’s and medical student research projects, guiding students through methodological design and data analysis. Her professional experience reflects a deep commitment to academic growth, clinical collaboration, and improving diagnostic education for the next generation of healthcare professionals.

Research Interest

Dr. Amani Mohamed Ibrahim Mohamed’s research interests lie at the intersection of clinical pathology, diagnostic innovation, and disease biomarker discovery. Her primary focus is on hematological malignancies, immunohematology, and molecular diagnostics. She is particularly interested in the identification and validation of novel biomarkers that can improve the early detection, diagnosis, and prognosis of various diseases, especially hematological cancers. Additionally, Dr. Amani explores the application of advanced diagnostic technologies, such as PCR-based techniques, flow cytometry, and automated hematology analyzers, in routine laboratory practice. Another area of her interest includes the study of inflammatory markers and their diagnostic relevance in autoimmune disorders and infectious diseases. She is also keen on investigating laboratory quality assurance and standardization procedures to enhance diagnostic accuracy and reliability. Her research often involves cross-disciplinary collaboration with clinicians, bioinformaticians, and molecular biologists, reflecting her integrative approach to laboratory medicine. As part of her academic role, she actively mentors students on research projects that align with her areas of interest. With a strong foundation in clinical pathology and a vision for diagnostic innovation, Dr. Amani aspires to contribute to translational research that bridges the gap between laboratory findings and clinical applications for improved patient care.

Research Skills

Dr. Amani Mohamed Ibrahim Mohamed has developed a comprehensive set of research skills that reflect her advanced training in clinical pathology and medical diagnostics. She is proficient in a wide range of laboratory techniques including blood smear examination, bone marrow aspirate evaluation, coagulation assays, immunoassays, and automated hematology analysis. Her molecular diagnostic skills encompass PCR, gel electrophoresis, and nucleic acid extraction techniques, which she has employed in various research settings. Additionally, she is skilled in ELISA, flow cytometry, and spectrophotometry, enabling her to carry out immunological and biochemical investigations with precision. Dr. Amani is adept at research design and methodology, statistical data analysis using SPSS and GraphPad Prism, and systematic literature reviews. She has received training in Good Clinical Laboratory Practices (GCLP), research ethics, and laboratory quality management systems. Furthermore, she is experienced in preparing research proposals, IRB submissions, and scientific presentations for academic conferences. Her ability to work both independently and collaboratively in research settings has allowed her to contribute meaningfully to several projects and academic discussions. Dr. Amani’s research skills are continually enhanced through workshops, courses, and hands-on laboratory supervision, all of which contribute to her ongoing development as a competent and innovative clinical researcher.

Awards and Honors

Throughout her academic and professional journey, Dr. Amani Mohamed Ibrahim Mohamed has received recognition for her dedication to clinical pathology and her contributions to medical education. She has been honored by the Faculty of Medicine at Zagazig University for her outstanding academic performance during both undergraduate and postgraduate studies. Her consistent excellence in coursework and laboratory practice earned her a place among the top students in her class, which paved the way for her recruitment as an academic staff member. In addition to her academic honors, she has received commendations from colleagues and supervisors for her commitment to teaching and mentorship. Dr. Amani has also been selected to participate in competitive training programs and workshops funded by the university and national health initiatives, reflecting her strong professional standing. Her poster and oral presentations at national medical conferences have received positive feedback and served to highlight her skills in scientific communication. Furthermore, she has been recognized for her active role in departmental activities, such as quality control audits and curriculum updates. These honors underscore Dr. Amani’s reputation as a diligent, knowledgeable, and forward-thinking medical professional, committed to advancing the standards of laboratory medicine and medical education in Egypt.

Author Metrics

Dr. Amani Mohamed Ibrahim Mohamed’s academic contributions have begun to gain recognition within the scientific and medical research communities. According to citation databases such as Google Scholar, her work has accumulated a total of 108 citations, reflecting the growing impact of her research in clinical pathology and related biomedical sciences. She has achieved an h-index of 6, which indicates that six of her published articles have each received at least six citations. This metric suggests a consistent level of scholarly influence across multiple publications. Furthermore, Dr. Amani holds an i10-index of 3, meaning that three of her articles have been cited ten times or more, underlining the quality and relevance of her most cited work. These metrics provide insight into her emerging academic visibility and research engagement. Her publications, primarily in the areas of hematology, immunopathology, and diagnostic biomarkers, contribute to advancing medical knowledge and laboratory practices. As she continues to expand her research activities and collaborate on interdisciplinary studies, her citation indices are expected to rise. Dr. Amani’s author metrics underscore her potential as a developing researcher and highlight the importance of her contributions to the field of clinical diagnostics and academic medicine.

Publications Top Notes

  • Impact of cytotoxin-associated gene A of Helicobacter pylori strains on microalbuminuria in type 2 diabetes
    Journal: Saudi Journal of Kidney Diseases and Transplantation
    Volume: 21(4)
    Citations: 35
    Year: 2010

  • MicroRNA‐199b expression level and coliform count in irritable bowel syndrome
    Journal: IUBMB Life
    Volume: 68(5)
    Citations: 14
    Year: 2016

  • Endoscopic band ligation of internal haemorrhoids versus stapled haemorrhoidopexy in patients with portal hypertension
    Journal: Arab Journal of Gastroenterology
    Volume: 12(1)
    Citations: 13
    Year: 2011

  • Annexin A2 versus AFP as an efficient diagnostic serum marker for hepatocellular carcinoma
    Journal: Journal of Gastroenterology and Hepatology Research
    Volume: 2(9)
    Citations: 8
    Year: 2013

  • Role of gallstones in typhoid carriage in Egyptian patients
    Journal: Journal of Microbiology and Infectious Diseases
    Volume: 2(4)
    Citations: 8
    Year: 2012

  • Current status of schistosomiasis in Egypt: parasitologic and endoscopic study in Sharqia Governorate
    Journal: Afro-Egyptian Journal of Infectious and Endemic Diseases
    Volume: 1(1)
    Citations: 8
    Year: 2011

  • Study of frequency of spontaneous bacterial empyema in cirrhotic patients with hepatic hydrothorax
    Journal: Journal of Gastroenterology and Hepatology Research
    Volume: 4(4)
    Citations: 6
    Year: 2015

  • Glutathione S‐Transferase M1 and T1 gene polymorphisms and the outcome of chronic hepatitis C virus infection in Egyptian patients
    Journal: Annals of Human Genetics
    Volume: 80(1)
    Citations: 5
    Year: 2016

  • Impact of oesophageal variceal injection on gastric varices in cirrhotic patients
    Journal: Journal of Gastroenterology and Hepatology Research
    Volume: 3(6)
    Citations: 4
    Year: 2014

  • Association of MnSOD Ala16Val genotype and activity with hepatocellular carcinoma risk in HCV-infected Egyptian patients
    Journal: Arab Journal of Gastroenterology
    Volume: 11(1)
    Citations: 4
    Year: 2010

Conclusion

Dr. Amani Mohamed Ibrahim Mohamed exemplifies the qualities of a dedicated academic and clinical pathologist with a passion for diagnostic excellence and medical education. Her professional journey reflects a solid foundation in medical sciences, strengthened by rigorous academic training and practical experience in clinical pathology. As an Assistant Lecturer at Zagazig University, she actively contributes to the academic development of students, the advancement of diagnostic practices, and the pursuit of impactful research. Her work in laboratory medicine combines traditional diagnostic techniques with emerging molecular approaches, demonstrating a commitment to innovation and quality. Dr. Amani’s research interests in hematology, immunopathology, and biomarker discovery position her as a promising contributor to the field of clinical diagnostics. Her technical expertise, research acumen, and teaching skills enable her to inspire the next generation of clinicians and researchers. Through continued professional development, participation in academic conferences, and interdisciplinary collaboration, she remains at the forefront of medical laboratory sciences in Egypt. Dr. Amani’s career embodies the integration of academic rigor, research innovation, and clinical service, marking her as a vital asset to both her institution and the wider healthcare community.

 

Jinfu Fan | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr. Jinfu Fan | Machine Learning | Best Researcher Award

Professor at Qingdao University, China.

Assoc. Prof. Dr. Jinfu Fan is a dedicated researcher and academic currently serving as an Associate Professor at the College of Computer Science Technology, Qingdao University (QU), China. He earned his Ph.D. in Computer Science from Tongji University, Shanghai, and further expanded his academic horizons as a visiting scholar at the School of Computing (SoC), National University of Singapore (NUS), from January to December 2022. Dr. Fan specializes in the fields of machine learning, data mining, and computer vision, with a notable emphasis on weakly supervised multi-label learning and super-resolution image reconstruction. His recent research project, MDiffSR, explores the application of mutual information and diffusion models in image super-resolution and has been published in the renowned Neurocomputing journal. His scholarly work demonstrates a solid blend of theoretical foundations and practical innovation, offering new directions in data-efficient learning and visual computing. Beyond research, Dr. Fan is actively involved in curriculum development and student mentorship at QU, contributing significantly to academic growth and collaborative learning. His passion for integrating advanced algorithms with real-world applications marks him as a progressive thinker and an impactful contributor in the field of artificial intelligence and computational imaging.

Publication Profile

Scopus

Orcid

Google  Scholar

Educational Details

Dr. Jinfu Fan obtained his Ph.D. degree in Computer Science from Tongji University, Shanghai, one of China’s leading research universities known for its engineering and technological disciplines. During his doctoral training, he focused on advanced learning algorithms and optimization techniques, gaining strong expertise in machine learning and data-driven modeling. His academic foundation combines rigorous computational training with a deep understanding of mathematical modeling, which laid the groundwork for his current research in weakly supervised learning and super-resolution technologies. In addition to his doctoral studies, Dr. Fan further honed his academic skills through a postdoctoral or visiting scholar tenure at the National University of Singapore (NUS), a globally recognized institution in computer science and AI research. This international experience provided him with broader research exposure, particularly in collaborative and cross-disciplinary projects, and allowed him to work alongside some of the field’s top minds. His educational background not only reflects technical depth but also a proactive approach toward lifelong learning and global academic engagement. His training in both national and international settings has helped cultivate a well-rounded understanding of computer science principles and their real-world applications, making him a versatile researcher and educator in the evolving tech landscape.

Professional Experience

Assoc. Prof. Dr. Jinfu Fan is currently affiliated with the College of Computer Science Technology at Qingdao University (QU), where he serves as an Associate Professor. In this role, he is actively involved in both research and teaching, guiding undergraduate and graduate students in areas related to machine learning, computer vision, and artificial intelligence. Prior to joining QU, he completed his Ph.D. at Tongji University and enriched his professional experience as a visiting scholar at the National University of Singapore (NUS) from January to December 2022. During his time at NUS, Dr. Fan collaborated with prominent researchers at the School of Computing, which broadened his research scope and provided him with valuable international experience. At Qingdao University, he has initiated and led several research projects, including the development of image super-resolution frameworks using mutual information and diffusion models. His role as an academic also includes curriculum development, research supervision, and interdisciplinary collaboration. His professional journey reflects a strong commitment to technological advancement and academic excellence, marked by his ability to integrate research with education and translate theory into practical innovations. Dr. Fan’s progressive academic and research track record underscores his dedication to scholarly leadership in AI and computational science.

Research Interest

Dr. Jinfu Fan’s research interests span across several cutting-edge areas within artificial intelligence and computer vision. He is particularly focused on machine learning and data mining, with a growing specialization in weakly supervised multi-label learning, an area that seeks to develop intelligent systems capable of learning from limited or incomplete labeled data. This field is crucial for reducing the cost and effort associated with data annotation, making AI more accessible and scalable. In addition, Dr. Fan is extensively involved in super-resolution image reconstruction, aiming to enhance the resolution of images using deep learning techniques and novel optimization models. His recent work on MDiffSR integrates mutual information and diffusion modeling to boost image quality and reconstruction accuracy, addressing core challenges in medical imaging, remote sensing, and surveillance. He also maintains active interest in areas such as representation learning, information theory in AI, and unsupervised learning strategies. His goal is to bridge the gap between theoretical development and real-world application, and his projects frequently target practical outcomes in health diagnostics, smart cities, and digital imaging. Dr. Fan’s interdisciplinary vision and technical versatility position him at the forefront of research aimed at making AI models more robust, efficient, and interpretable.

Research Skills

Assoc. Prof. Dr. Jinfu Fan possesses a comprehensive suite of research skills in both theoretical and applied computer science. His primary strength lies in machine learning algorithm design, where he has developed and evaluated models for classification, multi-label learning, and super-resolution tasks. He is proficient in deep learning frameworks such as TensorFlow and PyTorch, which he uses to build and test neural networks tailored for image processing and representation learning. Additionally, Dr. Fan has a strong grasp of information theory, particularly mutual information, which he applies to improve learning efficiency and performance in weakly supervised environments. His research methodology is firmly rooted in rigorous mathematical modeling and statistical analysis, supported by tools like Python, MATLAB, and R. He is also skilled in experimental design and evaluation, ensuring that his studies follow reproducible and scalable processes. Moreover, his experience with image reconstruction techniques, especially in the context of the MDiffSR project, demonstrates his ability to integrate domain-specific knowledge with advanced AI models. Dr. Fan’s collaborative experience at the National University of Singapore further highlights his international research exposure and ability to work on multidisciplinary teams, equipping him with both technical and cross-cultural collaboration skills vital for modern scientific research.

Awards and Honors

While specific awards and honors are not detailed in the available records, Assoc. Prof. Dr. Jinfu Fan’s academic and research career reflects commendable achievements that position him as a strong candidate for national and international recognition. His selection as a visiting scholar at the National University of Singapore (NUS)—a prestigious institution ranked among the top in Asia for computer science—demonstrates peer recognition of his academic potential and research capabilities. His publication in Neurocomputing, a well-regarded SCI-indexed journal, adds to his credentials, showcasing his ability to contribute impactful research to the scientific community. Dr. Fan’s research project “MDiffSR: Mutual information and diffusion model in image super-resolution” represents an innovative stride in AI-based imaging solutions and has earned citation attention, indicating its influence in the academic domain. As his body of work continues to expand, it is likely that his contributions will be recognized by leading societies and research funding bodies. He is an ideal candidate for honors such as the Best Researcher Award, Excellence in Research, or Outstanding Scientist Award, given his growing research portfolio, international collaborations, and commitment to academic advancement in machine learning and computer vision.

Author Metrics

  • Total Citations: 186

  • h-index: 8
    (8 publications have at least 8 citations each)

  • i10-index: 8
    (8 publications have at least 10 citations each)

Top Noted Publication

  • A dynamic ensemble method for residential short-term load forecasting
    Author: sY. Yang, F. Jinfu, W. Zhongjie, Z. Zheng, X. Yukun
    Journal: Alexandria Engineering Journal, 2023, 
    Citations: 25

  • GraphDPI: Partial label disambiguation by graph representation learning via mutual information maximization
    Author: J. Fan, Y. Yu, L. Huang, Z. Wang
    Journal: Pattern Recognition, 2023, 
    Citations: 23

  • Spatial-frequency dual-domain feature fusion network for low-light remote sensing image enhancement
    Author: Z. Yao, G. Fan, J. Fan, M. Gan, C.L.P. Chen
    Journal: IEEE Transactions on Geoscience and Remote Sensing, 2024.
    Citations: 17

  • A new multi-source transfer learning method based on two-stage weighted fusion
    Author: L. Huang, J. Fan, W. Zhao, Y. You
    Journal: Knowledge-Based Systems, 2023, 
    Citations: 17

  • Partial label learning based on disambiguation correction net with graph representation
    Author: J. Fan, Y. Yu, Z. Wang, J. Gu
    Journal: IEEE Transactions on Circuits and Systems for Video Technology, 2021, 
    Citations: 17

Conclusion

Assoc. Prof. Dr. Jinfu Fan exemplifies a forward-thinking academic who integrates rigorous research with practical innovation in the fields of machine learning and computer vision. With a solid educational foundation from Tongji University and global exposure through his time at the National University of Singapore, he brings a well-rounded and internationally informed perspective to his work. His specialized interests in weakly supervised multi-label learning and image super-resolution position him at the cutting edge of artificial intelligence research. The MDiffSR project, as one of his leading contributions, reflects his ability to blend theory with impactful applications. At Qingdao University, he not only leads significant research initiatives but also plays a vital role in mentoring students and fostering academic excellence. His research skills, encompassing deep learning, data mining, and mathematical modeling, make him a valuable contributor to both academic and industry-oriented projects. As he continues to expand his publication record and research collaborations, Dr. Fan stands as a promising candidate for recognition in scientific innovation. His commitment to knowledge advancement, problem-solving, and global engagement makes him a distinguished figure in the AI research landscape, with continued potential to make meaningful contributions to science and society.