Sami Ullah Khan | Artificial Intelligence | Best Faculty Award

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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

 

Liangyu Yin | Artificial Intelligence | Best Researcher Award

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Dr. Liangyu Yin | Artificial Intelligence | Best Researcher Award

Research Professor at Xinqiao Hospital, Army Medical University, China

Dr. Liangyu Yin is an accomplished academic and researcher specializing in clinical nutrition, epidemiology, and artificial intelligence. He has made significant contributions to understanding cancer nutrition and malnutrition, particularly in oncology patients. His expertise spans the intersection of nutrition, cancer biology, and advanced machine learning methodologies. With numerous publications in prestigious journals such as Journal of Cachexia Sarcopenia Muscle, American Journal of Clinical Nutrition, and Clinical Nutrition, Dr. Yin is recognized as a thought leader in his field. He is currently a Research Professor at the Department of Nephrology, Xinqiao Hospital, Army Medical University, where he continues to advance research on cancer cachexia, nutritional interventions, and artificial intelligence applications. His work is aimed at improving patient outcomes, especially for cancer patients, by utilizing innovative research methods, including AI-driven diagnostics and predictive models for malnutrition and cancer prognosis.

Professional Profile

Education:

Dr. Liangyu Yin’s educational journey is marked by a strong foundation in medicine and nutrition. He earned his Ph.D. in Nutrition and Food Hygiene from Army Medical University in 2022, following a Master of Medicine in Nutrition and Food Hygiene from Chongqing Medical University in 2012. His academic journey began with a Bachelor of Arts degree in English, specializing in Biomedical English, from Chongqing Medical University. This diverse educational background has provided him with a robust understanding of both medical and nutritional sciences, which he applies in his research. His ongoing contributions reflect his dedication to bridging clinical nutrition with the latest advancements in artificial intelligence and cancer epidemiology.

Professional Experience:

Dr. Liangyu Yin’s professional experience spans several prestigious roles in academic research, clinical settings, and health science institutions. He currently serves as a Research Professor in the Department of Nephrology at Xinqiao Hospital, Army Medical University. Previously, he held positions as an Associate Research Professor at both Daping Hospital and Southwest Hospital within the Army Medical University, focusing on cancer epidemiology, nutrition, and artificial intelligence. Dr. Yin began his research career as a Research Assistant at the Institute of Hepatobiliary Surgery, Southwest Hospital, where he worked on cancer biology and non-coding RNA. His long-standing career at Army Medical University has contributed to the development of novel methodologies and interventions in clinical nutrition and cancer treatment. His expertise in epidemiology, nutrition, and AI has shaped the direction of his research in improving patient care outcomes.

Research Interests:

Dr. Liangyu Yin’s primary research interests lie at the intersection of clinical nutrition, cancer epidemiology, and artificial intelligence. His work focuses on understanding the role of malnutrition in cancer progression, with a particular emphasis on cancer cachexia, a complex metabolic syndrome associated with cancer. Dr. Yin is dedicated to developing predictive models and AI-driven solutions to identify and address malnutrition in cancer patients, improving patient outcomes and survival rates. His research also investigates non-coding RNA and its role in cancer biology, with a focus on its potential applications in cancer treatment. Through his interdisciplinary approach, combining machine learning with clinical nutrition, Dr. Yin aims to revolutionize cancer care by improving diagnosis, prognosis, and nutritional interventions in clinical practice.

Research Skills:

Dr. Liangyu Yin possesses a diverse set of research skills, enabling him to conduct cutting-edge investigations in the fields of clinical nutrition, cancer epidemiology, and artificial intelligence. His proficiency in utilizing machine learning models to predict and diagnose malnutrition in cancer patients demonstrates his technical expertise. Additionally, Dr. Yin’s deep understanding of cancer biology, especially cancer cachexia and non-coding RNA, is critical to his work. His research skills also extend to conducting large-scale cohort studies and multicenter analyses, as evidenced by his numerous publications. Moreover, his ability to integrate AI with clinical nutrition research allows him to pioneer innovative solutions in medical diagnostics and patient care, making him a leader in his field.

Awards and Honors:

Dr. Liangyu Yin has received numerous accolades and honors for his contributions to clinical nutrition and cancer research. His work has been consistently recognized in prestigious academic journals, and his research has influenced global medical practices regarding nutrition in cancer care. Dr. Yin’s expertise in combining artificial intelligence with nutrition science has earned him several recognitions for innovation in healthcare. He is a highly regarded researcher within the medical and scientific community, regularly invited to present his findings at international conferences and to collaborate on advanced research projects. His commitment to improving cancer patient outcomes through his interdisciplinary research has made him a prominent figure in his field.

Conclusion:

Liangyu Yin is an outstanding candidate for the Best Researcher Award. His research in clinical nutrition, cancer epidemiology, and the innovative use of artificial intelligence sets him apart as a leader in his field. His work has made significant strides in understanding malnutrition and cancer cachexia, with implications for improving patient care. By expanding the scope of his research and enhancing the real-world application of his findings, he has the potential to make an even greater impact on global health. Therefore, he is highly deserving of this award, and his future contributions will continue to shape the field of clinical nutrition and cancer care.

Publication Top Notes:

  1. Early prediction of severe acute pancreatitis based on improved machine learning models
    • Authors: Li, L., Yin, L., Chong, F., Wang, Y., Xu, H.
    • Journal: Journal of Army Medical University
    • Year: 2024
    • Volume: 46(7)
    • Pages: 753–759
  2. Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study
    • Authors: Yin, L., Song, C., Cui, J., Shi, H., Xu, H.
    • Journal: Journal of Nutrition, Health and Aging
    • Year: 2024
    • Volume: 28(1)
    • Article ID: 100023
    • Citations: 3
  3. Comment on: “Triceps skinfold-albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study” by Yin et al. – the authors reply
    • Authors: Yin, L., Cui, J., Lin, X., Shi, H., Xu, H.
    • Journal: Journal of Cachexia, Sarcopenia and Muscle
    • Year: 2023
    • Volume: 14(6)
    • Pages: 2993–2994
  4. Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study
    • Authors: Huo, Z., Chong, F., Yin, L., Shi, H., Xu, H.
    • Journal: Clinical Nutrition
    • Year: 2023
    • Volume: 42(6)
    • Pages: 1048–1058
    • Citations: 6
  5. Ensemble learning system to identify nutritional risk and malnutrition in cancer patients without weight loss information
    • Authors: Yin, L., Liu, J., Liu, M., Shi, H., Xu, H.
    • Journal: Science China Life Sciences
    • Year: 2023
    • Volume: 66(5)
    • Pages: 1200–1203
  6. Kruppel-like Factors 3 Regulates Migration and Invasion of Gastric Cancer Cells Through NF-κB Pathway
    • Authors: Liang, X., Feng, Z., Yan, R., Lu, H., Zhang, L.
    • Journal: Alternative Therapies in Health and Medicine
    • Year: 2023
    • Volume: 29(2)
    • Pages: 64–69
    • Citations: 1
  7. Triceps skinfold–albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study
    • Authors: Yin, L., Cui, J., Lin, X., Shi, H., Xu, H.
    • Journal: Journal of Cachexia, Sarcopenia and Muscle
    • Year: 2023
    • Volume: 14(1)
    • Pages: 517–533
    • Citations: 5

 

 

Abid Iqbal | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Abid Iqbal | Artificial Intelligence | Best Researcher Award

Assistant Professor at King Faisal University, Saudi Arabia

Dr. Abid Iqbal is an accomplished Assistant Professor at the University of Engineering and Technology Peshawar, specializing in Electrical Engineering and artificial intelligence. He earned his Ph.D. from Griffith University, Australia, where he researched piezoelectric energy harvesters. With a strong academic background, he ranked first in his Master’s program at Ghulam Ishaq Khan Institute, Pakistan. Dr. Iqbal has a diverse professional experience, including roles as an Electrical Design Engineer and Research Assistant. His expertise encompasses developing embedded devices and innovative teaching methodologies, mentoring students, and conducting impactful research. He has successfully secured funding for multiple projects in AI applications for health and agriculture. Dr. Iqbal’s publication record includes numerous papers in reputable journals, reflecting his commitment to advancing knowledge in his field. His technical skills in programming and software further enhance his research capabilities, making him a valuable asset to academia and industry.

Profile

Education

Dr. Abid Iqbal is a highly accomplished academic with a solid educational foundation in electrical and electronics engineering. He earned his Ph.D. from the Queensland Micro- and Nanotechnology Centre at Griffith University, Australia, from April 2013 to February 2017. His doctoral research focused on the design, fabrication, and analysis of aluminum nitride (AlN)/silicon carbide (SiC)-based piezoelectric energy harvesters, contributing significantly to renewable energy technologies. Prior to his Ph.D., Dr. Iqbal completed his Master’s degree in Electronics Engineering at the Ghulam Ishaq Khan Institute in Topi, Swabi, Pakistan, graduating with a remarkable GPA of 3.88/4 and securing the top position in his class. His academic journey began with a Bachelor’s degree in Electrical Engineering from the University of Engineering & Technology in Peshawar, Pakistan, where he was recognized as an outstanding student. Dr. Iqbal’s educational background reflects his dedication and expertise in his field, laying a strong foundation for his professional career.

Professional Experience

Dr. Abid Iqbal is an accomplished electrical engineer currently serving as an Assistant Professor at the University of Engineering and Technology Peshawar since August 2019. In this role, he has been instrumental in teaching undergraduate courses in Electrical Engineering, developing innovative teaching methods, and mentoring students on research projects. Prior to this position, he worked as an Electrical Design Engineer at Alliance Power and Data in Australia, focusing on ERGON and NBN projects. He also contributed to the development of embedded systems for individuals with disabilities while employed as an Electronic Engineer at Community Lifestyle Support. His research experience includes a significant role as a Research Assistant at Griffith University, where he worked on piezoelectric devices for harsh environments and gained expertise in various semiconductor fabrication processes. Additionally, he has served as a lecturer at Comsat Institute of Information Technology and worked as a research associate at the City University of Hong Kong, demonstrating a robust and diverse professional background in academia and industry.

Research Interest

Dr. Abid Iqbal’s research interests lie at the intersection of electrical engineering and artificial intelligence, focusing on the development of innovative technologies that enhance energy efficiency and improve healthcare outcomes. His work includes designing and fabricating advanced piezoelectric energy harvesters using AlN/SiC materials, aimed at harnessing renewable energy sources. Additionally, Dr. Iqbal is deeply involved in projects utilizing artificial intelligence for agricultural applications, such as real-time disease detection in crops, and developing telehealth systems that leverage IoT technology to monitor patient health remotely. He has a keen interest in embedded systems and the design of hardware for assistive technologies, including portable ventilators and muscle sensors for individuals with disabilities. Through his research, Dr. Iqbal aims to contribute to sustainable energy solutions and advancements in healthcare technology, fostering a multidisciplinary approach that integrates engineering principles with artificial intelligence for practical applications.

Research Skills

Dr. Abid Iqbal possesses a robust set of research skills that underscore his expertise in Electrical Engineering and artificial intelligence. His extensive experience in designing and fabricating piezoelectric energy harvesters highlights his proficiency in materials science and device characterization. Dr. Iqbal is adept at using advanced simulation tools such as COMSOL, Ansys, and Coventorware, which facilitate in-depth analysis and optimization of microelectromechanical systems (MEMS). His work on artificial intelligence applications in telehealth and agricultural systems showcases his ability to integrate machine learning techniques with practical engineering solutions. Additionally, Dr. Iqbal has a strong background in programming languages such as Python and MATLAB, enhancing his capability to develop innovative software solutions for complex engineering problems. His involvement in funded projects and numerous publications further illustrates his commitment to advancing research and contributing to knowledge in his field. Overall, Dr. Iqbal’s diverse skills position him as a valuable asset to any research team.

Award and Recognition

Dr. Abid Iqbal is a distinguished electrical engineer and academic known for his significant contributions to the field of electrical and electronics engineering. He has received multiple accolades for his research and academic excellence, including the IGNITE funding for four innovative projects focused on machine learning applications in health and agriculture. Dr. Iqbal was awarded publication scholarships and prestigious Griffith University PhD scholarships, recognizing his outstanding academic performance during his doctoral studies. Additionally, he ranked first among his peers in the Master’s program at Ghulam Ishaq Khan Institute, further demonstrating his commitment to excellence in engineering. His dedication to teaching and mentoring future engineers is evident in his role as an Assistant Professor at the University of Engineering and Technology Peshawar, where he has developed innovative curricula and guided numerous student research projects. Dr. Iqbal’s work has been widely published, contributing significantly to advancements in artificial intelligence, embedded systems, and renewable energy technologies.

Conclusion

Dr. Abid Iqbal is a highly qualified candidate for the Best Researcher Award, demonstrating exceptional expertise in Electrical Engineering and a strong commitment to research and education. His accomplishments in renewable energy research, successful project management, and dedication to mentoring future engineers make him a standout choice. While he has areas for growth, particularly in expanding collaborative networks and enhancing commercialization efforts, his current achievements and potential for future contributions position him as an inspiring figure in his field. This award would not only recognize his past efforts but also encourage his continued pursuit of excellence in research and education.

Publication Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Year: 2024
    • Journal: Results in Engineering
    • Volume/Page: 24, 102994
  2. Novel dual absorber configuration for eco-friendly perovskite solar cells: design, numerical investigations and performance of ITO-C60-MASnI3-RbGeI3-Cu2O-Au
    • Authors: Hasnain, S.M., Qasim, I., Iqbal, A., Amin Mir, M., Abu-Libdeh, N.
    • Year: 2024
    • Journal: Solar Energy
    • Volume/Page: 278, 112788

 

 

 

Mona Jamjoom | AI | Best Researcher Award

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Assoc Prof Dr. Mona Jamjoom | AI | Best Researcher Award

Assoc Prof Dr. Mona Jamjoom, Princess Nourah bint Abdulrahman University, Saudi Arabia

Assoc Prof Dr. Mona Jamjoom is an accomplished researcher in the field of artificial intelligence, recognized for her innovative contributions and impactful studies. With a strong focus on machine learning and data analytics, she has published numerous papers in leading journals and has been awarded the Best Researcher Award for her groundbreaking work. Mona is passionate about harnessing AI to solve complex problems and improve decision-making processes across various industries. Her commitment to advancing technology while addressing ethical considerations makes her a prominent figure in the AI community.

Profile:

Scholar

Academics:

Assoc Prof Dr. Mona Jamjoom holds a PhD in Artificial Intelligence from King Saud University, awarded in May 2016. She also earned her Master’s degree in Computer Science from the same institution in 2004, following her Bachelor’s degree in Computer Science, which she completed in 1992. Her academic background provides a strong foundation for her research and contributions to the field of AI.

Professional Experiences:

Assoc Prof Dr. Mona Jamjoom has extensive professional experience in academia. Since 2021, she has served as an Associate Professor at Princess Nourah bint Abdulrahman University in Riyadh, Saudi Arabia. Prior to this, she was an Assistant Professor at the same institution from 2017 to 2021. Mona began her academic career as a Lecturer at Princess Nourah bint Abdulrahman University from 2007 to 2016, and before that, she worked as a Teaching Assistant from 1998 to 2007. Her career in the field began in 1993, when she provided technical support at the university, further solidifying her commitment to education and technology.

Activities:

Assoc Prof Dr. Mona Jamjoom is actively engaged in various professional activities that enhance her contributions to the field of artificial intelligence. In 2024, she joined the work team at the Center for Advanced Studies in Artificial Intelligence at King Saud University, collaborating on the KSU AI Satellite Lab project with SDAIA. She served as an external examiner for a doctoral thesis on deep learning applications for visual pollution detection in Riyadh. Additionally, she reviewed applications for the Apple Developer Academy’s second challenge for female students and participated in consulting sessions during the Gulf Hackathon Program focused on AI in public education. Mona also acted as a consultant for the UNESCO project “AI Capacity Building in Arabic-speaking Countries,” supported by Huawei Technologies. She has reviewed numerous papers for ISI journals and attended the research day at Princess Nourah bint Abdulrahman University. Furthermore, she co-supervised a PhD student specializing in Cognitive Computing at Universiti Kuala Lumpur, Malaysia.

Publication Top Notes:

M. Adil, Z. Yinjun, M. M. Jamjoom, and Z. Ullah. “OptDevNet: An Optimized Deep Event-Based Network Framework for Credit Card Fraud Detection.” IEEE Access, vol. 12, pp. 132421-132433, 2024. doi: 10.1109/ACCESS.2024.3458944.

Rabbani, H., Shahid, M. F., Khanzada, T. J. S., Siddiqui, S., Jamjoom, M. M., Ashari, R. B., Ullah, Z., Mukati, M. U., and Nooruddin, M. “Enhancing Security in Financial Transactions: A Novel Blockchain-Based Federated Learning Framework for Detecting Counterfeit Data in Fintech.” PeerJ Computer Science, vol. 10, e2280, 2024.

Malik, M. S. I., Nawaz, A., and Jamjoom, M. M. “Hate Speech and Target Community Detection in Nastaliq Urdu Using Transfer Learning Techniques.” IEEE Access, 2024.

Kurtoğlu, A., Eken, Ö., Çiftçi, R., Çar, B., Dönmez, E., Kılıçarslan, S., Jamjoom, M. M., Abdel Samee, N., Hassan, D. S. M., and Mahmoud, N. F. “The Role of Morphometric Characteristics in Predicting 20-Meter Sprint Performance Through Machine Learning.” Scientific Reports, vol. 14, no. 1, 16593, 2024.

Shah, S. M. A. H., Khan, M. Q., Rizwan, A., Jan, S. U., Samee, N. A., and Jamjoom, M. M. “Computer-Aided Diagnosis of Alzheimer’s Disease and Neurocognitive Disorders with Multimodal Bi-Vision Transformer (BiViT).” Pattern Analysis and Applications, vol. 27, no. 3, 76, 2024.

Ishtiaq, A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Product Helpfulness Detection with Novel Transformer Based BERT Embedding and Class Probability Features.” IEEE Access, 2024.

Abbas, M. A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection from Social Media.” IEEE Access, 2024.

Elhadad, A., Jamjoom, M., and Abulkasim, H. “Reduction of NIFTI Files Storage and Compression to Facilitate Telemedicine Services Based on Quantization Hiding of Downsampling Approach.” Scientific Reports, vol. 14, no. 1, 5168, 2024.

Malik, M. S. I., Younas, M. Z., Jamjoom, M. M., and Ignatov, D. I. “Categorization of Tweets for Damages: Infrastructure and Human Damage Assessment Using Fine-Tuned BERT Model.” PeerJ Computer Science, vol. 10, e1859, 2024.

Malik, M. S. I., Nawaz, A., Jamjoom, M. M., and Ignatov, D. I. “Effectiveness of ELMo Embeddings and Semantic Models in Predicting Review Helpfulness.” Intelligent Data Analysis, (Preprint), 1-21, 2023.