Fawwad Hassan Jaskani | Computer Science | Best Researcher Award

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Dr. Fawwad Hassan Jaskani | Computer Science | Best Researcher Award

Doctor at The Islamia University of Bahawalpur | Pakistan

Dr. Fawwad Hassan Jaskani is a distinguished researcher and leader specializing in machine learning, robotics, and advanced data-driven applications. As the Chief Executive Officer of FHJ Complex Infinite Solutions, he has guided teams in delivering high-quality research assistance and innovative technical solutions tailored to the needs of scholars and professionals. His expertise spans Microsoft Azure, Power BI, and Robotic Process Automation, which he effectively integrates into projects to enhance efficiency and impact. With an academic foundation rooted in The Islamia University of Bahawalpur and Universiti Tun Hussein Onn Malaysia, Dr. Jaskani has produced influential publications addressing diverse fields, including artificial neural networks, digital protection systems, Internet of Things, and medical data analysis. His contributions as a peer reviewer for international journals further underscore his dedication to advancing knowledge and ensuring quality in research. Combining academic rigor with practical application, he continues to shape the research landscape with innovation and leadership.

Professional Profile 

Google Scholar | Scopus Profile

Education

Dr. Fawwad Hassan Jaskani holds a strong academic background in machine learning and robotics, having pursued advanced studies at The Islamia University of Bahawalpur, where he completed his Master of Engineering with a focus on machine learning and robotics. He further enhanced his expertise by earning a Doctor of Philosophy in Machine Learning from Universiti Tun Hussein Onn Malaysia. His educational journey has provided him with a deep understanding of artificial intelligence, data analysis, and automation technologies, which he has effectively applied in his professional and research career. Through his academic training, he has developed a robust foundation in both theoretical concepts and practical implementations, enabling him to bridge the gap between innovation and application. His educational achievements have not only fueled his research pursuits but also established his credibility as a thought leader in the domains of artificial intelligence, data-driven technologies, and computational research methodologies.

Experience

Dr. Fawwad Hassan Jaskani brings extensive professional experience spanning leadership, research, and technical consultancy. As Chief Executive Officer of FHJ Complex Infinite Solutions, he has successfully led teams in providing tailored research assistance, technical simulations, and high-quality solutions for academic and professional clients. His experience as a peer reviewer for international journals with TechScience Press reflects his role in maintaining scholarly standards and contributing to the global research community. Over the years, he has also worked as a professional freelancer, collaborating with diverse clients on projects requiring specialized expertise in artificial intelligence, automation, and data science. These experiences have honed his project management, communication, and problem-solving skills, positioning him as both a leader and an innovator. His diverse career reflects a unique ability to merge academic insights with industry requirements, demonstrating his effectiveness in driving impactful outcomes while fostering research excellence and applied technological advancements.

Research Focus

Dr. Fawwad Hassan Jaskani’s research primarily focuses on machine learning, artificial intelligence, robotics, and their applications across interdisciplinary fields. His publications showcase a wide array of studies, including neural networks, digital differential protection schemes, operating systems for the Internet of Things, and predictive modeling for healthcare, particularly early detection of diseases. He also explores visualization techniques for complex biological datasets and comparative analyses of classification models, reflecting his commitment to advancing both theoretical and applied dimensions of research. His work emphasizes the integration of AI-driven solutions into real-world challenges, bridging the gap between academia and practical implementation. By combining algorithmic efficiency with innovation, Dr. Jaskani’s research contributes to fields as diverse as bioinformatics, automation, energy systems, and digital security. His ability to explore multiple disciplines through the lens of machine learning makes his research not only impactful but also forward-looking, contributing to global technological and scientific progress.

Award and Honor

Dr. Fawwad Hassan Jaskani has earned recognition for his contributions as a researcher, innovator, and academic leader. His role as a peer reviewer for international journals highlights the trust placed in his expertise and his influence within the scholarly community. His academic achievements, including successful completion of advanced degrees in machine learning and robotics, further underscore his dedication and excellence. In his professional career, he has been acknowledged for leading FHJ Complex Infinite Solutions, where his efforts in transforming research assistance into high-impact, customized solutions have been highly valued. Additionally, his publications across diverse areas of artificial intelligence and automation demonstrate his contribution to knowledge creation, which is itself a mark of distinction. While his recognitions are rooted in his academic and professional excellence, his ongoing commitment to innovation, mentorship, and applied research continues to elevate his profile as an accomplished researcher deserving of honors and awards.

Publication Top Notes

  • Title: Time-Series Prediction of Cryptocurrency Market using Machine Learning Techniques
    Year: 2021
    Citations: 73

  • Title: Comparison of classification models for early prediction of breast cancer
    Year: 2019
    Citations: 73

  • Title: ICC T20 Cricket World Cup 2020 winner prediction using machine learning techniques
    Year: 2020
    Citations: 38

  • Title: Prediction of Cardiovascular Disease on Self‐Augmented Datasets of Heart Patients Using Multiple Machine Learning Models
    Year: 2022
    Citations: 37

  • Title: IOTA‐Based Mobile Crowd Sensing: Detection of Fake Sensing Using Logit‐Boosted Machine Learning Algorithms
    Year: 2022
    Citations: 21

  • Title: An Investigation on Several Operating Systems for Internet of Things
    Year: 2019
    Citations: 17

  • Title: Lungs nodule cancer detection using statistical techniques
    Year: 2020
    Citations: 16

  • Title: Convolutional Autoencoder‐Based Deep Learning Approach for Aerosol Emission Detection Using LiDAR Dataset
    Year: 2022
    Citations: 15

  • Title: Urbanization Detection Using LiDAR‐Based Remote Sensing Images of Azad Kashmir Using Novel 3D CNNs
    Year: 2022
    Citations: 15

  • Title: Short-Term Prediction Model for Multi-Currency Exchange Using Artificial Neural Network
    Year: 2020
    Citations: 12

  • Title: Detection of Uterine Fibroids in Medical Images Using Deep Neural Networks
    Year: 2022
    Citations: 11

  • Title: Hybrid machine learning techniques to detect real time human activity using UCI dataset
    Year: 2021
    Citations: 9

  • Title: Detection of anomaly in videos using convolutional autoencoder and generative adversarial network model
    Year: 2020
    Citations: 9

  • Title: Comparative Analysis of Face Detection Using Linear Binary Techniques and Neural Network Approaches
    Year: 2018
    Citations: 7

  • Title: Karachi Stock Exchange Price Prediction using Machine Learning Regression Techniques
    Year: 2021
    Citations: 6

Conclusion

Dr. Fawwad Hassan Jaskani has established himself as a prolific researcher with impactful contributions across diverse domains, including machine learning, healthcare analytics, IoT systems, financial forecasting, and computer vision. His publications reflect a consistent effort to bridge academic theory with real-world applications, often addressing socially and technologically significant challenges such as disease prediction, urbanization monitoring, and market forecasting. The steady citation record of his work demonstrates both relevance and influence within the global research community. His ability to collaborate across disciplines, produce high-quality research outputs, and contribute to advancing modern computational techniques highlights his position as a strong candidate for recognition. With continued focus on interdisciplinary innovation and global engagement, he is well-poised to make even greater contributions to the fields of artificial intelligence and applied research.

Baha Ihnaini | Computer Science | Outstanding Contribution Award

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Dr. Baha Ihnaini | Computer Science | Outstanding Contribution Award

Assistant Professor at Wenzhou-Kean University, China

Dr. Baha Ihnaini is an accomplished academic and researcher in computer science with expertise spanning artificial intelligence, data science, machine learning, and natural language processing. His scholarly work has addressed significant challenges in sentiment analysis, medical diagnostics, disease prediction, and misinformation detection, with publications in respected journals and international conferences. Notably, he has contributed to developing Arabic lexicons for sentiment analysis, enhancing AI-driven healthcare solutions, and advancing transfer learning models for predictive analytics. Alongside his research, Dr. Ihnaini has demonstrated a strong commitment to teaching, covering a wide range of computer science courses and mentoring students in senior projects. His service on academic committees and involvement in curriculum development highlight his leadership and dedication to institutional growth. With a record of impactful research, effective teaching, and professional service, Dr. Ihnaini stands out as a valuable contributor to his field and a strong candidate for academic recognition.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Baha Ihnaini holds a Ph.D. in Computer Science with a specialization in Data Science from Universiti Utara Malaysia, where his research focused on developing an expandable Arabic lexicon and sentiment analysis rules for social media text. He also earned a Master of Science in Management Information Systems from The Arab Academy for Banking and Financial Sciences, equipping him with a strong foundation in both technical and managerial aspects of information technology. His academic journey began with a Bachelor’s degree in Computer Engineering from Philadelphia University in Jordan, providing him with comprehensive knowledge of hardware, software, and systems engineering. This multidisciplinary educational background has enabled Dr. Ihnaini to integrate advanced computational methods with practical problem-solving approaches, particularly in the areas of machine learning, natural language processing, and data-driven applications. His academic credentials reflect a balance between rigorous technical expertise and applied research in emerging fields of computing.

Experience

Dr. Ihnaini has accumulated rich professional experience as an educator, researcher, and academic leader across several institutions. He currently serves as an Assistant Professor of Computer Science at Wenzhou-Kean University, where he teaches a broad range of courses, from foundational programming and systems to advanced research in computer science. His roles extend beyond teaching, as he actively contributes to academic committees focused on curriculum development, faculty hiring, and student support. Prior to this, he served as an Adjunct Professor at Al Ain University and BTEC Abu Dhabi, as well as a Lecturer at Al Khawarizmi International College, where he guided student projects and curriculum design. Earlier in his career, he worked as a Research Officer at Universiti Utara Malaysia’s InterNetWorks Research Lab, where he played a pivotal role in advancing sentiment analysis for Arabic text. Collectively, his experience reflects a strong commitment to research, teaching excellence, and academic service.

Research Focus

Dr. Ihnaini’s research focuses on artificial intelligence, machine learning, data science, and natural language processing, with an emphasis on solving real-world problems through intelligent systems. A significant part of his work has concentrated on Arabic sentiment analysis, where he developed innovative linguistic resources and computational models to improve text classification accuracy. His recent research extends to medical AI, including predictive modeling for diseases such as diabetic retinopathy, Alzheimer’s disease, and vitamin D deficiency, showcasing his ability to merge computer science with healthcare applications. He has also contributed to the advancement of fake news detection, stock market prediction using sentiment data, and multimodal semantic similarity. His interdisciplinary approach highlights the versatility of data-driven methods and their societal impact, from enhancing healthcare systems to improving digital communication analysis. Through these diverse but interconnected research directions, Dr. Ihnaini continues to contribute to both theoretical advancements and practical innovations in computer science.

Award and Honor

Dr. Ihnaini has earned recognition for his scholarly contributions through research publications in reputable international journals and conferences, with several works indexed in Scopus and well-regarded platforms. His achievements include developing novel computational methods for sentiment analysis, interdisciplinary research in healthcare prediction models, and the application of advanced machine learning techniques to real-world problems. His role as a key contributor to collaborative projects with international researchers further reflects the recognition of his expertise and the impact of his work. Beyond research, his commitment to education and service has been acknowledged within the institutions he has served, particularly through his involvement in curriculum innovation and student mentorship. While formal distinctions are highlighted through his publication record and conference participation, his career trajectory itself demonstrates consistent recognition as a capable scholar and educator. His growing research visibility and international collaborations continue to strengthen his candidacy for prestigious awards and honors.

Publication Top Notes

  • Title: A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learning
    Authors: B Ihnaini, MA Khan, TA Khan, S Abbas, MS Daoud, M Ahmad, MA Khan
    Year: 2021
    Citations: 158

  • Title: Machine Learning Empowered Software Defect Prediction System
    Authors: MS Daoud, S Aftab, M Ahmad, MA Khan, A Iqbal, S Abbas, M Iqbal, B Ihnaini
    Year: 2022
    Citations: 37

  • Title: Stock trend prediction using sentiment analysis
    Authors: Q Xiao, B Ihnaini
    Year: 2023
    Citations: 35

  • Title: Joint channel and multi-user detection empowered with machine learning
    Authors: MS Daoud, A Fatima, WA Khan, MA Khan, S Abbas, B Ihnaini, M Ahmad
    Year: 2021
    Citations: 31

  • Title: Real-time shill bidding fraud detection empowered with fussed machine learning
    Authors: WUH Abidi, MS Daoud, B Ihnaini, MA Khan, T Alyas, A Fatima, M Ahmad
    Year: 2021
    Citations: 28

  • Title: Rider weed deep residual network-based incremental model for text classification using multidimensional features and MapReduce
    Authors: HB Abdalla, AM Ahmed, SRM Zeebaree, A Alkhayyat, B Ihnaini
    Year: 2022
    Citations: 18

  • Title: Presenting and evaluating scaled extreme programming process model
    Authors: M Ibrahim, S Aftab, M Ahmad, A Iqbal, BS Khan, M Iqbal, BNS Ihnaini
    Year: 2020
    Citations: 13

  • Title: Exploring the agile family: A survey
    Authors: M Ibrahim, S Aftab, B Bakhtawar, M Ahmad, A Iqbal, N Aziz, MS Javeid, B Ihnaini
    Year: 2020
    Citations: 12

  • Title: Predicting vitamin D deficiency using optimized random forest classifier
    Authors: A Alloubani, B Abuhaija, M Almatari, G Jaradat, B Ihnaini
    Year: 2024
    Citations: 9

  • Title: Lexicon-based sentiment analysis of Arabic tweets: A survey
    Authors: B Ihnaini, M Mahmuddin
    Year: 2018
    Citations: 9

  • Title: A Severity Grading Framework for Diabetic Retinopathy Detection using Transfer Learning
    Authors: S Akhtar, S Aftab, S Kousar, A Rehman, M Ahmad, AQ Saeed, B Ihnaini
    Year: 2024
    Citations: 8

  • Title: Improving the Quality of e-Commerce Service by Implementing Combination Models with Step-by-Step, Bottom-Up Approach
    Authors: BA Hemn, G Chengwei, B Ihnaini
    Year: 2021
    Citations: 6

  • Title: Sentiment analysis of Song Dynasty classical poetry using fine-tuned large language models: a study with LLMs
    Authors: B Ihnaini, W Sun, Y Cai, Z Xu, R Sangi
    Year: 2024
    Citations: 5

  • Title: A transfer learning based framework for diabetic retinopathy detection using data fusion
    Authors: S Akhtar, S Aftab, M Ahmad, B Ihnaini
    Year: 2024
    Citations: 4

  • Title: Semantic similarity on multimodal data: A comprehensive survey with applications
    Authors: B Ihnaini, B Abuhaija, EA Mills, M Mahmuddin
    Year: 2024
    Citations: 3

Conclusion

Dr. Baha Ihnaini’s publication record reflects a strong and steadily growing research trajectory across diverse yet interconnected fields of computer science, including artificial intelligence, data science, natural language processing, and medical informatics. His works demonstrate both theoretical depth and practical applications, ranging from healthcare prediction models and fraud detection to sentiment analysis and software engineering. The high citation impact of certain publications highlights the relevance and influence of his research in the academic community, while his more recent works indicate an expanding focus on interdisciplinary applications such as healthcare and cultural text analysis using advanced AI techniques. Collectively, his contributions showcase a balance of innovation, collaboration, and societal relevance, positioning him as a researcher whose work is not only academically significant but also impactful in addressing real-world challenges. This combination of influence, diversity, and practical value strengthens his candidacy for recognition through awards and honors.

Sun Park | Computer Science | Best Research Article Award

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Dr. Sun Park | Computer Science | Best Research Article Award

Research Associate Professor at, Gwangju Institute of Science and Technology, South Korea

Sun Park is a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, a position held since 2013. Her research focuses on data mining, information retrieval, information summarization, convergent marine ICT, smart farming, and IoT-cloud & AI computing. Prior to this role, she served as a Research Professor at Mokpo National University’s Information Industry Research Institute from 2010 to 2013. She also worked as a Full-time Lecturer at Honam University from 2008 to 2010 and as an Adjunct Professor at Hanseo University from 2002 to 2007. Sun Park holds a Ph.D. in Computer Information Engineering from Inha University (2007), a Master’s degree in Information and Communication Engineering from Hannam University (2001), and a Bachelor’s degree in Computer Science from Jeonju University (1996). References are available upon request.

Publication Profile

Strengths for the Award

  1. Extensive Experience in Research and Teaching: Sun Park has over a decade of research and teaching experience, with key positions at prestigious institutions like the Gwangju Institute of Science and Technology, Mokpo National University, Honam University, and Hanseo University. This variety of roles highlights a significant breadth and depth of expertise in the field of Computer Science and Engineering.
  2. Specialized Research Focus: Their research areas, including Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm, align well with current and emerging technological trends. This suggests that Sun Park is contributing to forward-thinking, impactful research.
  3. AI and Converging Technologies: As a Research Associate Professor at the Graduate School of AI, Sun Park is in a prime position to lead interdisciplinary projects, bringing together fields like AI, IoT, and smart technologies. These areas are critical for innovation, making their work relevant for contemporary challenges.
  4. Strong Academic Background: Holding a Ph.D. in Computer Information Engineering and advanced degrees in Information and Communication Engineering, Sun Park’s academic credentials demonstrate a high level of expertise. The progression from a Bachelor’s to a Ph.D. showcases a long-standing commitment to the field.
  5. Institutional Impact: Serving in high-ranking academic roles implies that Sun Park has contributed to shaping research strategies, mentoring students, and advancing their institution’s academic reputation, which is a critical factor for awards that recognize leadership in research.

Areas for Improvement

  1. Lack of Specific Research Achievements: The provided profile does not detail significant publications, patents, or specific innovations. A more robust record of high-impact publications or citations would strengthen Sun Park’s candidacy for the Best Researcher Award. Highlighting specific projects or research grants won would also add weight.
  2. Global Collaboration and Visibility: While the candidate is clearly well-established in South Korea, a stronger record of international collaborations, keynote speeches, or participation in global conferences would further elevate their profile. Visibility in international research communities is often crucial for award considerations.
  3. Applied Outcomes or Industry Impact: While the research areas are impressive, the profile does not specify applied outcomes or how these research fields have impacted industries or society. Showcasing tangible applications of research (e.g., how IoT solutions have benefited smart farms or marine industries) would demonstrate real-world influence.

Education:

Sun Park holds a Ph.D. in Computer Information Engineering from Inha University, earned between 2002 and 2007, which forms the foundation of their advanced expertise in computer science. Prior to this, they completed a Master’s degree in Information and Communication Engineering at Hannam University from 1997 to 2001. This followed a Bachelor’s degree in Computer Science from Jeonju University, obtained between 1992 and 1996. This strong academic background, progressing from undergraduate to doctoral levels, demonstrates a deep and comprehensive education in computing and engineering disciplines.

Experience:

Sun Park has over two decades of academic and research experience, spanning various prestigious roles in South Korea. Currently serving as a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, they focus on cutting-edge research in areas like Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm technologies. Previously, they held positions as a Research Professor at Mokpo National University and a Full-time Lecturer at Honam University. Sun Park’s academic journey, from earning a Ph.D. in Computer Information Engineering to holding multiple teaching and research roles, reflects a deep and broad expertise in computer science, with a strong commitment to innovation in AI and emerging technologies.

Research Focus:

Sun Park’s research focuses on several cutting-edge fields, including Data Mining, Information Retrieval, Information Summarization, Convergent Marine ICT, Smart Farming, and IoT-Cloud & AI Computing. This diverse range of interests demonstrates a commitment to advancing both theoretical and practical applications in technology. Their work bridges multiple domains, with a particular emphasis on integrating AI and IoT for innovative solutions in areas like agriculture and marine industries. By focusing on emerging technologies and their real-world implications, Sun Park’s research contributes to solving contemporary challenges in information management and intelligent systems.

Awards and Honors:

Sun Park’s awards and honors are not specifically listed in the provided profile. However, their notable academic positions, such as Research Associate Professor at the Graduate School of AI, Gwangju Institute of Science and Technology, and past roles at Mokpo National University and Honam University, suggest recognition of their expertise and leadership in their field. These roles reflect a high level of academic and research achievement, although further details on specific awards, honors, or recognitions would provide a clearer understanding of their accolades. Highlighting any formal awards or distinctions would strengthen their profile for the Best Researcher Award.

Publication Top Notes:

  • Design of Vessel Data Lakehouse with Big Data and AI Analysis Technology for Vessel Monitoring System
    • Authors: Park, S., Yang, C.-S., Kim, J.
    • Year: 2023
    • Citations: 6
  • Design and Implementation of Data Concentrator Unit supported with Multiple Synchronized Cameras for Object-Detection
    • Authors: Anvarjon, Y., Park, S., Kim, J.
    • Year: 2023
    • Citations: 0
  • Concept Design of Intelligent BoP Based on Slot-/Rack-type Fuel Cell for Integrated Management of Hydrogen Fuel Cells
    • Authors: Park, S., Chung, B.-J., Kim, J.
    • Year: 2023
    • Citations: 1
  • Correction to: Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 1
  • Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 3

Conclusion:

Sun Park’s extensive academic experience, specialized focus in key technological areas, and position within a prominent research institution make them a strong candidate for a research award. However, to be highly competitive for a Best Researcher Award, it would be beneficial for them to highlight specific high-impact research achievements, international collaborations, and real-world applications of their work. These additions would showcase a broader influence in both academic and industrial sectors, further solidifying their candidacy for this prestigious recognition.