Farhan Hassan Khan | Artificial Intelligence | Best Researcher Award

Dr. Farhan Hassan Khan | Artificial Intelligence | Best Researcher Award

National University of Sciences & Technology, Pakistan

Author Profile

Early Academic Pursuits:

Dr. Farhan Hassan Khan began his academic journey with a Bachelor's degree in Software Engineering from UET Taxila, Pakistan, where he demonstrated exceptional academic prowess with an aggregate score of 86%, earning him distinction. He continued to excel in his studies, pursuing a Master's degree in Computer Software Engineering at NUST, Pakistan, where he achieved a remarkable CGPA of 3.90/4.00 and was awarded the prestigious Gold Medal. His thirst for knowledge and passion for research led him to pursue a Ph.D. in Software Engineering at NUST, where he further distinguished himself with a perfect CGPA of 4.00/4.00, earning him an Excellence Award.

Professional Endeavors:

Dr. Khan's professional journey is characterized by a diverse range of roles and responsibilities across various organizations. From his tenure as a Software Engineer at Advanced VoIP Pvt. Ltd., where he led product development and client interactions, to his role as a Project Director/General Manager at NESCOM, overseeing research, design, and development teams for mobile, web, and desktop applications, Dr. Khan has consistently demonstrated leadership and technical expertise. His contributions extend to academia, where he serves as a Visiting Faculty at multiple prestigious universities, teaching and mentoring both undergraduate and postgraduate students.

Contributions and Research Focus:

Dr. Khan's research interests span a wide array of domains within data science and software engineering, including natural language processing, machine learning, artificial intelligence, healthcare informatics, and bioinformatics. His groundbreaking work on sentiment analysis frameworks, semi-supervised feature weighting, and intelligent model selection has garnered significant attention and has been instrumental in advancing the field. Moreover, his active involvement in research funding initiatives underscores his commitment to pushing the boundaries of knowledge and innovation in his respective fields.

Accolades and Recognition:

Dr. Khan's contributions to research and academia have been recognized through numerous awards and distinctions, including the prestigious P@SHA Gold Award, APICTA Awards nomination, and the Hafeez Qureshi Excellence Award for Best Performance in Ph.D. His publications in top-tier international journals, resulting in an accumulated impact factor of 150+, further attest to the quality and significance of his work. Additionally, his academic achievements, such as receiving the President's Gold Medal and the Excellence Award for his Ph.D., highlight his exceptional dedication and scholarly contributions.

Impact and Influence:

Dr. Khan's influence extends beyond his individual accomplishments, shaping the landscape of data science and software engineering through his research, teaching, and mentorship. His innovative frameworks and methodologies have not only contributed to advancements in sentiment analysis and machine learning but have also inspired future generations of researchers and practitioners. Through his leadership roles in academia and industry, he continues to foster a culture of excellence and innovation, leaving a lasting impact on the fields he passionately serves.

Legacy and Future Contributions:

As Dr. Khan's career progresses, his legacy as a pioneering researcher and educator in data science and software engineering is poised to endure. His ongoing contributions to research, teaching, and mentorship promise to shape the future of these fields, inspiring new generations of scholars and practitioners to push the boundaries of knowledge and innovation. Dr. Khan's unwavering commitment to excellence and his dedication to making a meaningful difference ensure that his legacy will continue to resonate for years to come.

Citations

A total of 1387 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations        1387
  • h-index           50
  • i10-index        19

Notable Publications 

Hybrid machine learning model for malware analysis in android apps

Pervasive and Mobile Computing, Bashir, S., …, Abid, A.S.

Hardware Accelerators And Accelerators For Machine Learning

International Conference on IT and Industrial Technologies, ICIT. Ali, D., …, Khan, F.H.

A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches

Complexity, Bashir, S., …, Shiraz, M.

 

Chuen-Horng Lin | Computer Science and Information Engineering | Best Researcher Award

Prof. Chuen-Horng Lin | Computer Science and Information Engineering | Best Researcher Award

National Taichung University of Science and Technology, Taiwan

Author Profile

Early Academic Pursuits

Chuen-Horng Lin embarked on his academic journey with a focus on applied mathematics, earning his M.S. and Ph.D. degrees from National Chung-Hsing University in Taiwan. His early research delved into stress and strength analysis, particularly in composite materials, utilizing the Direct Boundary Element Method.

Professional Endeavors

Transitioning into computer science and engineering, Lin has made significant contributions to various fields, including computer vision, image processing, machine learning, deep learning, and pattern recognition. His work has encompassed automated image and video analysis, emphasizing detection, tracking, and segmentation methods.

Contributions and Research Focus

Lin's research has spanned several impactful areas, from the stress analysis of bolted composite joints to the development of fast image retrieval systems. His publications reflect a diverse range of interests, including repairable systems, fuzzy analysis of queueing systems, and parametric programming approaches for batch arrival queues. Notably, his work has been published in prestigious journals and conference proceedings, garnering citations and recognition within the scientific community.

Accolades and Recognition

Lin's contributions have not gone unnoticed, as evidenced by his publications in renowned journals and his citation impact. His research has been acknowledged for its innovation and relevance, earning him accolades within his field.

Impact and Influence

Through his interdisciplinary work, Lin has left a significant impact on the fields of computer science, engineering, and applied mathematics. His contributions have advanced methodologies in image analysis, system modeling, and optimization techniques, shaping the trajectory of research in these domains.

Legacy and Future Contributions

Lin's legacy lies in his multidisciplinary approach to problem-solving and his dedication to advancing knowledge at the intersection of computer science and engineering. As he continues his academic journey, his future contributions are poised to further enrich our understanding of complex systems and drive innovation in computational methods.

Citations

A total of 1715 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         1715
  • h-index            21
  • i10-index         36

Notable Publications 

Classification of the tree for aerial image using a deep convolution neural network and visual feature clustering

CH Lin, CC Yu, TY Wang, TY Chen
The Journal of Supercomputing
Multi-scale features fusion convolutional neural networks for Rice leaf disease identification

CL Wang, MW Li, YK Chan, SS Yu, JH Ou, CY Chen, MH Lee, CH Lin
J. Imag. Sci. Technol
Automatic object detection and direction prediction of unmanned vessels based on multiple convolutional neural network technology

CH Lin, XC Wang
International Journal of Pattern Recognition and Artificial Intelligence
Intelligent image analysis recognizes important orchid viral diseases

CF Tsai, CH Huang, YK Chan, FJ Jan
Frontiers in Plant Science
Identifying the occlusion of left subclavian artery with stent based on chest MRI images

YK Chan, YC Lin, WJ Wang, WT Hu, CH Lin, SS Yu
Multimedia Tools and Applications
Left ventricular hypertrophy detection using electrocardiographic signal

CW Liu, FH Wu, YL Hu, RH Pan, CH Lin, YF Chen, GS Tseng, YK Chan, ...
Scientific Reports
Dog nose-print recognition based on the shape and spatial features of scales

YK Chan, CH Lin, YR Ben, CL Wang, SC Yang, MH Tsai, SS Yu
Expert Systems with Applications