Sami Ullah Khan | Artificial Intelligence | Best Faculty Award

Dr. Sami Ullah Khan | Artificial Intelligence | Best Faculty Award

Chairperson/Assistant Professor from Gomal University DIK Pakistan, Pakistan

Dr. Sami Ullah Khan is a dedicated academic and researcher in the field of Physical Chemistry, currently serving as an Assistant Professor at the Department of Chemistry, Government College University Faisalabad, Pakistan. With a Ph.D. in Physical Chemistry from Quaid-i-Azam University, Islamabad, Dr. Khan has been actively contributing to academia through teaching, research, and scientific collaboration. His academic journey reflects a blend of rigorous scholarship and a passion for innovation, particularly in areas related to materials chemistry, nanotechnology, and green chemistry. He has supervised numerous postgraduate research projects and published several impactful articles in peer-reviewed international journals. Dr. Khan has also participated in national and international conferences, workshops, and training programs, which have strengthened his academic network and research profile. He is committed to fostering an environment that encourages curiosity, analytical thinking, and scientific inquiry among students. His dedication to academic excellence and societal impact has earned him recognition within Pakistan’s scientific community. As a forward-looking scholar, Dr. Khan continues to explore sustainable and cutting-edge approaches to scientific problems, integrating his research expertise with his teaching practices. His work exemplifies the values of intellectual rigor, integrity, and a commitment to advancing knowledge in physical and environmental chemistry.

Professional Profile

Education

Dr. Sami Ullah Khan has built a strong educational foundation that supports his expertise in Physical Chemistry and related scientific domains. He earned his Ph.D. in Physical Chemistry from the prestigious Quaid-i-Azam University in Islamabad, Pakistan. His doctoral research focused on thermodynamic and kinetic aspects of chemical reactions and advanced material analysis, providing him with in-depth knowledge and practical experience in modern analytical techniques and experimental design. Prior to his doctoral studies, he completed his MPhil and MSc in Chemistry, also from Quaid-i-Azam University, with a specialization in Physical Chemistry. His academic performance has consistently been excellent, marked by distinctions and active participation in scientific events. Throughout his educational journey, Dr. Khan developed a strong command of theoretical frameworks as well as laboratory-based applications. His exposure to diverse scientific environments and challenging academic tasks enabled him to gain hands-on experience with state-of-the-art instrumentation and computational tools. This robust academic background has not only shaped his research capabilities but also prepared him to contribute effectively to teaching and mentorship roles. The combination of rigorous coursework, experimental research, and scientific communication formed the cornerstone of Dr. Khan’s expertise, laying the groundwork for a successful academic and research career.

Professional Experience

Dr. Sami Ullah Khan brings extensive professional experience in academia, particularly within the realm of higher education and scientific research. He currently serves as an Assistant Professor in the Department of Chemistry at Government College University Faisalabad, a position he has held since completing his doctoral studies. In this role, he teaches both undergraduate and postgraduate courses in Physical Chemistry, and supervises MSc and MPhil research projects. Dr. Khan’s academic career is characterized by a balance of teaching, research, and administrative duties, reflecting his versatility as a scholar and educator. His teaching philosophy emphasizes interactive learning, critical thinking, and research-driven instruction. Previously, he worked as a lecturer and research associate at various reputable institutions in Pakistan, contributing to curriculum development, academic advising, and scientific outreach initiatives. He has also been involved in research collaborations with other universities, enhancing his exposure to interdisciplinary scientific approaches. Dr. Khan’s commitment to excellence in teaching has been recognized through positive student feedback and peer evaluations. Furthermore, he has actively contributed to academic committees and organized workshops aimed at promoting scientific literacy and research skills among students. His professional journey is marked by a deep commitment to nurturing future scientists and advancing the field of chemistry.

Research Interest

Dr. Sami Ullah Khan’s research interests lie primarily in the fields of Physical Chemistry, Nanotechnology, Environmental Chemistry, and Green Chemistry. His work focuses on understanding the fundamental properties and behavior of chemical systems through thermodynamics, kinetics, and surface chemistry. A significant part of his research investigates the synthesis, characterization, and application of nanomaterials for environmental and industrial applications. Dr. Khan is particularly interested in exploring eco-friendly synthesis routes for nanoparticles, utilizing plant extracts and other green methods to reduce the use of toxic chemicals. This aligns with his interest in sustainable development and the minimization of environmental impact through innovative chemical processes. He also explores photocatalysis, adsorption phenomena, and the development of advanced functional materials for water treatment and pollution control. His interdisciplinary approach combines experimental techniques with computational modeling to gain a comprehensive understanding of material behavior at the molecular level. Dr. Khan’s research aims to address real-world problems such as water contamination, energy efficiency, and industrial waste management. By integrating principles of chemistry with environmental science, he contributes to the development of practical solutions for sustainable living. His research has been widely published in reputed scientific journals, and he actively seeks collaboration with fellow researchers in complementary fields.

Research Skills

Dr. Sami Ullah Khan possesses a broad range of research skills that make him a valuable contributor to the field of Physical Chemistry and materials science. His expertise includes the design and execution of experimental studies involving thermodynamic and kinetic measurements, surface chemistry analysis, and the synthesis of nanomaterials using both conventional and green chemistry methods. He is proficient in the use of advanced instrumentation such as UV-Vis spectroscopy, FTIR, XRD, SEM, and TGA for characterizing chemical compounds and nanomaterials. Dr. Khan is also skilled in computational chemistry tools used for modeling reaction mechanisms and predicting molecular interactions. His laboratory management skills ensure strict adherence to safety protocols and efficient coordination of research projects. Moreover, he demonstrates strong data analysis capabilities, employing statistical software and graphical tools to interpret experimental results accurately. Dr. Khan also excels in scientific writing and communication, as evidenced by his publication record and active participation in scientific conferences. He is an effective research mentor, guiding postgraduate students in thesis development, lab techniques, and research ethics. His ability to combine technical knowledge with analytical reasoning and teamwork contributes to the success of interdisciplinary projects and the overall enhancement of the research culture at his institution.

Awards and Honors

Throughout his academic journey, Dr. Sami Ullah Khan has received multiple awards and honors in recognition of his scholarly excellence and research contributions. He has been acknowledged for his outstanding performance during his Ph.D. studies, receiving institutional accolades for academic achievement and scientific impact. Dr. Khan has also been a recipient of research grants and travel fellowships to present his work at national and international conferences, which have further validated the importance and relevance of his research in the scientific community. His research papers have been published in high-impact journals, some of which have earned citation awards and commendations from reviewers and editorial boards. He has been recognized for his role in mentoring graduate students and fostering academic growth through innovative teaching practices. Moreover, Dr. Khan has participated in scientific workshops and symposiums where he has received certificates of merit for his contributions as a speaker and panelist. These accolades reflect not only his competence as a researcher but also his commitment to promoting scientific knowledge and education. The honors serve as milestones in his career, motivating him to pursue excellence in research, teaching, and community service within the broader field of chemistry.

Conclusion

Dr. Sami Ullah Khan stands out as a passionate educator, dedicated researcher, and forward-thinking academic in the realm of Physical Chemistry. His journey from student to Assistant Professor reflects a consistent commitment to scientific inquiry, sustainable innovation, and educational excellence. With a solid academic foundation and diverse professional experience, he has contributed significantly to both teaching and research at Government College University Faisalabad. His work in nanotechnology, environmental remediation, and green chemistry not only advances scientific understanding but also addresses critical global challenges. Through his teaching, Dr. Khan inspires the next generation of chemists by encouraging analytical thinking, hands-on experimentation, and ethical research practices. His collaborative spirit and strong research skills have resulted in numerous publications, successful student theses, and impactful scientific engagements. Recognized through various awards and honors, Dr. Khan exemplifies the qualities of a modern scientist—curious, conscientious, and committed to positive change. As he continues to expand his academic reach and explore new frontiers in chemistry, Dr. Khan remains a valuable asset to the scientific and educational community. His work is a testament to the transformative power of knowledge, persistence, and a deep-seated passion for the chemical sciences.

Publications Top Notes

  1. Oblique stagnation point flow of nanofluids over stretching/shrinking sheet with Cattaneo–Christov heat flux model: existence of dual solution

    • Authors: X. Li, A.U. Khan, M.R. Khan, S. Nadeem, S.U. Khan

    • Year: 2019

    • Citations: 96

  2. Common fixed point results for new Ciric-type rational multivalued F-contraction with an application

    • Authors: T. Rasham, A. Shoaib, N. Hussain, M. Arshad, S.U. Khan

    • Year: 2018

    • Citations: 64

  3. Common fixed points for multivalued mappings in G-metric spaces with applications

    • Authors: Z. Mustafa, M. Arshad, S.U. Khan, J. Ahmad, M.M.M. Jaradat

    • Year: 2017

    • Citations: 44

  4. Fixed point results for F-contractions involving some new rational expressions

    • Authors: M. Arshad, S.U. Khan, J. Ahmad

    • Year: 2016

    • Citations: 44

  5. Complex T-spherical fuzzy relations with their applications in economic relationships and international trades

    • Authors: A. Nasir, N. Jan, M.S. Yang, S.U. Khan

    • Year: 2021

    • Citations: 41

  6. Two new types of fixed point theorems for F-contraction

    • Authors: S.U. Khan, M. Arshad, A. Hussain, M. Nazam

    • Year: 2016

    • Citations: 36

  7. Investigation of cyber-security and cyber-crimes in oil and gas sectors using the innovative structures of complex intuitionistic fuzzy relations

    • Authors: N. Jan, A. Nasir, M.S. Alhilal, S.U. Khan, D. Pamucar, A. Alothaim

    • Year: 2021

    • Citations: 34

  8. Medical diagnosis and life span of sufferer using interval valued complex fuzzy relations

    • Authors: A. Nasir, N. Jan, A. Gumaei, S.U. Khan

    • Year: 2021

    • Citations: 30

  9. Cybersecurity against the loopholes in industrial control systems using interval-valued complex intuitionistic fuzzy relations

    • Authors: A. Nasir, N. Jan, A. Gumaei, S.U. Khan, F.R. Albogamy

    • Year: 2021

    • Citations: 29

  10. τ− Generalization of fixed point results for F− contraction

  • Authors: A. Hussain, M. Arshad, S.U. Khan

  • Year: 2015

  • Citations: 29

 

Mini Han Wang | Artificial Intelligence | Young Scientist Award

Dr. Mini Han Wang | Artificial Intelligence | Young Scientist Award

Chinese University of Hong Kong, Hong Kong

Dr. Mini Han Wang is a distinguished senior researcher specializing in ophthalmology, artificial intelligence (AI) in medical imaging, and biomolecular pathways in ocular diseases. She holds dual Ph.D.s in Ophthalmology & Visual Sciences from The Chinese University of Hong Kong and Data Science from the City University of Macau, demonstrating her expertise in integrating medical research with AI-driven analytical techniques. Dr. Wang has made significant contributions to age-related macular degeneration (AMD) research, AI-based disease diagnostics, and precision medicine. She currently serves as a Senior Researcher at Zhuhai People’s Hospital, affiliated with the Beijing Institute of Technology and Jinan University, and Director of the Frontier Science Computing Center at the Chinese Academy of Sciences. Beyond research, she is an experienced lecturer, delivering courses on intelligent data mining, evidence-based medicine, and AI applications in healthcare. Her work is widely published in peer-reviewed journals, and she actively collaborates with leading academic and medical institutions. With a commitment to advancing medical AI technologies and personalized healthcare solutions, Dr. Wang stands out as a leading expert at the intersection of medicine and data science.

Professional Profile

Education

Dr. Mini Han Wang has pursued a multidisciplinary academic journey, combining medical sciences, engineering, and data science. She earned a Ph.D. in Ophthalmology & Visual Sciences from The Chinese University of Hong Kong (2022-2025), where her research focuses on AI-driven diagnostics and molecular mechanisms of retinal diseases. In parallel, she completed a Ph.D. in Data Science at the Institute of Data Science, City University of Macau (2020-2023), further enhancing her ability to develop AI-integrated solutions for medical applications. Before her doctoral studies, Dr. Wang completed an M.Sc. in Management (2016-2018) at City University of Macau, gaining insights into research administration and healthcare management. She also holds dual bachelor’s degrees from Jiangxi Science & Technology Normal University (2012-2016) in Internet of Things (IoT) Engineering and English Literature, showcasing her strong foundation in technology and global scientific communication. As an Outstanding Graduate Representative, her diverse educational background enables her to bridge the gap between medical research, AI innovation, and healthcare management, making her a pioneering figure in modern ophthalmic research.

Professional Experience

Dr. Wang’s professional journey is marked by leadership in research, teaching, and AI-driven medical advancements. She currently serves as a Senior Researcher at Zhuhai People’s Hospital, affiliated with Beijing Institute of Technology and Jinan University, where she leads projects on AI-based ophthalmic disease diagnosis and retinal molecular research. Additionally, she holds the position of Director of the Frontier Science Computing Center at the Chinese Academy of Sciences, overseeing cutting-edge AI applications in medicine and multi-omics data integration. Since 2018, Dr. Wang has collaborated with Shenzhen Institute of Advanced Technology and Zhuhai Institute of Advanced Technology, conducting research on medical imaging, knowledge graphs, and AI-driven predictive modeling. Her academic contributions include guest lectures at Beijing Institute of Technology, Jinan University, and Zhuhai Science & Technology Institute, focusing on intelligent data mining, evidence-based medicine, and AI in disease diagnosis. With her interdisciplinary expertise, Dr. Wang has played a key role in bridging fundamental research with clinical applications, contributing significantly to medical AI advancements and personalized treatment strategies.

Research Interest

Dr. Wang’s research revolves around three core areas: ophthalmology, AI in medical imaging, and biomolecular pathways in ocular diseases. Her primary focus is age-related macular degeneration (AMD) and retinal diseases, where she investigates molecular mechanisms, genetic variations, and metabolic dysregulation. She is also deeply involved in AI-driven predictive modeling to enhance early disease detection and precision therapeutics. In the field of medical imaging, she integrates multi-modal imaging techniques (OCT, UWF Fundus) with AI algorithms to improve retinal disease diagnostics and prognosis. Furthermore, her research extends to biomolecular analysis, where she studies oxidative stress, mitochondrial dysfunction, and complement system activation in ocular diseases. By combining multi-omics data, AI-driven drug discovery, and knowledge graph-driven ophthalmic AI systems, Dr. Wang aims to revolutionize personalized medicine and enhance treatment strategies for degenerative eye diseases.

Research Skills

Dr. Wang possesses a diverse and advanced skill set, allowing her to lead high-impact research in medical AI and ophthalmology. She specializes in AI-based predictive modeling, machine learning for medical imaging, and deep learning for disease classification. Her expertise in biomolecular analysis includes multi-omics data integration, pathway analysis, and molecular crosstalk identification for precision medicine applications. Dr. Wang is also proficient in data mining, statistical modeling, and computational biology, which are essential for her research on retinal diseases and AI-driven diagnostics. Additionally, she has hands-on experience with multi-modal imaging techniques (OCT, UWF, fundus photography) and their integration with AI-based disease detection frameworks. She is well-versed in academic writing, research methodology, and project management, with an extensive record of peer-reviewed publications and collaborative research projects. With these skills, Dr. Wang is able to bridge the gap between clinical research and AI-powered healthcare solutions, making her a leading figure in medical innovation.

Awards and Honors

Dr. Wang has received multiple recognitions for her outstanding research contributions and academic achievements. As an Outstanding Graduate Representative, she was acknowledged for her exceptional performance in data science and medical research. She has been the recipient of research grants and funding awards for her work in ophthalmic AI, biomolecular studies, and precision medicine. Her research on AMD and AI-driven diagnostics has earned recognition from international conferences and peer-reviewed journals. She has been invited as a keynote speaker and panelist at various scientific conferences, where she has shared insights on AI applications in medicine, multi-omics integration, and retinal disease research. Additionally, her collaborations with leading universities and medical institutions have led to numerous institutional awards for excellence in research and innovation. With a strong academic and professional track record, Dr. Wang continues to be recognized as a pioneering researcher at the forefront of AI-driven medical advancements.

Conclusion

Dr. Mini Han Wang is a leading researcher at the intersection of ophthalmology, AI, and biomolecular analysis, making groundbreaking contributions to AMD research, AI-driven diagnostics, and precision medicine. Her multidisciplinary expertise in medical science, data analytics, and computational biology allows her to develop innovative solutions for early disease detection and personalized treatment strategies. As a senior researcher, director, and academic lecturer, she has demonstrated leadership in both research and education, mentoring young scientists and collaborating with top-tier institutions. Her work in AI-integrated ophthalmology and molecular disease modeling is shaping the future of medical research and healthcare technology. While further global collaborations, large-scale clinical applications, and expanded research beyond AMD

Publications Top Notes

  • Title: Place attachment to pseudo establishments: An application of the stimulus-organism-response paradigm to themed hotels
    Authors: J. Sun, P.J. Chen, L. Ren, E.H.W. Shih, C. Ma, H. Wang, N.H. Ha
    Year: 2021
    Citations: 86

  • Title: The effect of online investor sentiment on stock movements: an LSTM approach
    Authors: G. Wang, G. Yu, X. Shen
    Year: 2020
    Citations: 43

  • Title: Big data and predictive analytics for business intelligence: A bibliographic study (2000–2021)
    Authors: Y. Chen, C. Li, H. Wang
    Year: 2022
    Citations: 33

  • Title: AI-based advanced approaches and dry eye disease detection based on multi-source evidence: Cases, applications, issues, and future directions
    Authors: M.H. Wang, L. Xing, Y. Pan, F. Gu, J. Fang, X. Yu, C.P. Pang, K.K.L. Chong
    Year: 2024
    Citations: 32

  • Title: Artificial intelligence in ophthalmopathy and ultra-wide field image: A survey
    Authors: J. Yang, S. Fong, H. Wang, Q. Hu, C. Lin, S. Huang, J. Shi, K. Lan, R. Tang
    Year: 2021
    Citations: 29

  • Title: Research on data security in big data cloud computing environment
    Authors: F. Wang, H. Wang, L. Xue
    Year: 2021
    Citations: 27

  • Title: An explainable artificial intelligence-based robustness optimization approach for age-related macular degeneration detection based on medical IoT systems
    Authors: M.H. Wang, K.K. Chong, Z. Lin, X. Yu, Y. Pan
    Year: 2023
    Citations: 26

  • Title: Applications of explainable artificial intelligent algorithms to age-related macular degeneration diagnosis: A case study based on CNN, attention, and CAM mechanism
    Authors: M. Wang, Z. Lin, J. Zhou, L. Xing, P. Zeng
    Year: 2023
    Citations: 13

  • Title: Metamaterials design method based on deep learning database
    Authors: X. Zhou, Q. Xiao, H. Wang
    Year: 2022
    Citations: 10

  • Title: A YOLO-based method for improper behavior predictions
    Authors: M. Wang, Y. Zhao, Q. Wu, G. Chen
    Year: 2023
    Citations: 9