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.

 

Farhan Hassan Khan | Artificial Intelligence | Best Researcher Award

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