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
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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.