Faisal Mehmood | Computer Vision | Best Researcher Award

Dr. Faisal Mehmood | Computer Vision | Best Researcher Award

Post Doctorate at Shenzhen University, China📖

Faisal Mehmood is a passionate PhD researcher at Zhengzhou University, specializing in Electrical and Information Engineering. With a strong academic background, including degrees in Computer Science, he has a diverse range of expertise in deep learning, computer vision, and human action recognition (HAR). Faisal has authored numerous research papers in prominent journals and conferences and has practical experience as a software developer, database developer, and lecturer. His contributions are recognized in academia, where he also actively reviews for esteemed journals. Faisal continues to focus on advancing technologies in machine learning and artificial intelligence.

Profile

Scopus Profile

Google Scholar Profile

Education Background🎓

  • Ph.D. in Electrical and Information Engineering (2019–2024), Zhengzhou University, Henan, China (1st Division).
  • MS in Computer Science (2015–2017), University of Agriculture Faisalabad (UAF), Punjab, Pakistan (1st Division).
  • MSc in Computer Science (2013–2015), University of Agriculture Faisalabad (UAF), Punjab, Pakistan (1st Division).
  • BSc (2011–2013), Islamia University Bahawalpur, Punjab, Pakistan (1st Division).
  • Intermediate (2008–2010), BISE Bahawalpur, Punjab, Pakistan (1st Division).
  • Matriculation (2006–2008), BISE Bahawalpur, Punjab, Pakistan (1st Division).

Professional Experience🌱

Faisal Mehmood has accumulated a wealth of teaching and industry experience over the years. He has served as a lecturer at institutions such as the University of Agriculture Faisalabad, University of Education Faisalabad, and GC University Faisalabad. Faisal has also gained industry experience as a Software Developer and Database Developer, working on various projects involving database management, web development, and system software design. He has supervised several undergraduate projects and contributed to academic workshops and seminars, fostering an environment of interactive learning and development.

Research Interests🔬

Faisal’s research interests include:

  • Deep Learning: Exploring advanced neural network architectures.
  • Computer Vision: Enhancing image and video processing for real-world applications.
  • Human Action Recognition (HAR): Developing systems for detecting and recognizing human actions through innovative algorithms.
  • Natural Language Processing: Applying machine learning techniques for language understanding and processing.

Author Metrics

Faisal Mehmood has published several research papers in reputed journals, such as IEEE Transactions on Consumer Electronics, Soft Computing, and Computers in Human Behavior, with numerous articles under review. His work has contributed significantly to advancements in the fields of human action recognition, machine learning, and data science. He has received merit scholarships throughout his academic career and has been recognized with awards such as the Chief Minister’s Laptop Scheme and various programming competition wins. Faisal actively contributes to the academic community as a reviewer for top journals and conferences, further enriching his research endeavors.

Publications Top Notes 📄

1. Human action recognition of spatiotemporal parameters for skeleton sequences using MTLN feature learning framework

  • Authors: F Mehmood, E Chen, MA Akbar, AA Alsanad
  • Journal: Electronics
  • Volume: 10
  • Issue: 21
  • Article: 2708
  • Year: 2021
  • Citations: 21

2. Three-dimensional agricultural land modeling using unmanned aerial system (UAS)

  • Authors: F Mahmood, K Abbas, A Raza, MA Khan, PW Khan
  • Journal: International Journal of Advanced Computer Science and Applications
  • Volume: 10
  • Issue: 1
  • Year: 2019
  • Citations: 18

3. Intelligent Transmission Control for Efficient Operations in SDN

  • Authors: R Alkanhel, A Ali, F Jamil, M Nawaz, F Mehmood, A Muthanna
  • Journal: Computers, Materials & Continua
  • Volume: 71
  • Issue: 2
  • Year: 2022
  • Citations: 11

4. Effect of human-related factors on requirements change management in offshore software development outsourcing: A theoretical framework

  • Author: FM Sukana Z
  • Journal: Soft Computing and Machine Intelligence
  • Volume: 1
  • Issue: 1
  • Pages: 36-52
  • Year: 2021
  • Citations: 11

5. Towards successful global software development

  • Authors: M Shafiq, Q Zhang, MA Akbar, T Kamal, F Mehmood, MT Riaz
  • Conference: Proceedings of the 24th International Conference on Evaluation and …
  • Year: 2020
  • Citations: 11

Conclusion

Dr. Faisal Mehmood is undoubtedly a highly deserving candidate for the Best Researcher Award due to his exceptional contributions to deep learning, computer vision, and human action recognition. His innovative frameworks, high-quality publications, and academic success distinguish him as a leader in his field. While there are areas for further improvement, particularly in expanding his research reach and increasing industrial collaborations, his continued growth and success make him a strong candidate for the award. His work, particularly in applying AI and deep learning for practical applications, has great potential to shape the future of technology.

Dr. Mehmood’s combination of academic rigor, technical expertise, and research impact make him a promising figure in the academic community and an excellent candidate for this prestigious recognition.

Sathishkumar Moorthy | Computer Vision | Best Researcher Award

Dr. Sathishkumar Moorthy | Computer Vision | Best Researcher Award

Post-Doctoral Researcher at Sejong University, South Korea📖

Dr. Sathishkumar Moorthy is an accomplished researcher specializing in artificial intelligence (AI), machine learning (ML), and deep learning (DL) with a focus on computer vision applications. With a proven track record in innovative research, he has developed cutting-edge techniques for video object detection, human emotion recognition, and intelligent surveillance systems. His expertise includes self-attention-based models, image processing, and multimodal data analysis. Dr. Moorthy has contributed to academia and industry through impactful publications and collaborative research projects, striving to advance computer vision and AI technology.

Profile

Google Scholar Profile

Education Background🎓

Dr. Sathishkumar Moorthy earned his Doctorate of Philosophy (Ph.D.) from Kunsan National University, South Korea (2017–2024), with a commendable CGPA of 4.16. His doctoral thesis focused on developing an enhanced self-attention-based Vision Transformer model for robust video object detection systems. He completed his Master of Engineering (M.E.) in 2013 from Karpagam Academy of Higher Education, Tamil Nadu, India, achieving an impressive CGPA of 9.05. His master’s thesis explored automatic diagnosis of breast cancer lesions using Gaussian Mixture Model and Expectation-Maximization algorithms. He holds a Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Tamil Nadu, India (2011), graduating with a CGPA of 7.87. His undergraduate thesis analyzed and compared parsing techniques for asynchronous messages.

Professional Experience🌱

Dr. Sathishkumar has accumulated extensive experience across academia, industry, and research roles. He is currently a Post-Doctoral Researcher at Sejong University, South Korea (2024–Present), focusing on multimodal human emotion recognition using advanced Transformer-based models. Prior to this, he served as Manager of the AI Research Team at Smart Vision Tech Inc., Seoul, where he specialized in developing advanced object detection and segmentation algorithms, leveraging frameworks such as YOLO and Faster R-CNN. His teaching experience includes roles as Assistant Professor at Karpagam College of Engineering (2017) and J.K.K. Munirajah College of Technology (2013–2016) in Tamil Nadu, India, where he delivered lectures on programming, data structures, and algorithms and conducted workshops on mobile application development and genetic algorithms.

Research Interests🔬

Dr. Moorthy’s research focuses on:

  • Computer Vision: Video object detection, intelligent surveillance systems, and multimodal emotion recognition.
  • Artificial Intelligence: Deep learning, Transformer models, and advanced neural network architectures.
  • Industry Applications: Real-time fault detection, anomaly tracking, and autonomous systems using AI/ML techniques.
  • Medical Imaging: Image segmentation and diagnosis using probabilistic and ML algorithms.

Author Metrics

Dr. Sathishkumar Moorthy has made significant contributions to the field of computer vision and artificial intelligence through his research and publications. His works focus on advanced AI/ML techniques, including Vision Transformers, multimodal emotion recognition, and object detection, particularly for real-world applications such as video surveillance and medical imaging.

He has authored several high-impact research papers in reputable journals and conferences, reflecting his expertise in image processing, deep learning, and robotics. His research output has garnered notable citations, showcasing the relevance and influence of his work in the academic and research communities. Dr. Sathishkumar’s Google Scholar profile highlights his active contributions to advancing AI-driven solutions for complex problems, affirming his position as a dedicated researcher in the field.

Publications Top Notes 📄

1. Distributed Leader-Following Formation Control for Multiple Nonholonomic Mobile Robots via Bioinspired Neurodynamic Approach

  • Authors: S. Moorthy, Y.H. Joo
  • Journal: Neurocomputing
  • Volume: 492
  • Pages: 308–321
  • Year: 2022
  • Citations: 43
  • DOI/Link: [Check Neurocomputing journal for more details]

2. Gaussian-Response Correlation Filter for Robust Visual Object Tracking

  • Authors: S. Moorthy, J.Y. Choi, Y.H. Joo
  • Journal: Neurocomputing
  • Volume: 411
  • Pages: 78–90
  • Year: 2020
  • Citations: 31
  • DOI/Link: [Check Neurocomputing journal for more details]

3. Adaptive Spatial-Temporal Surrounding-Aware Correlation Filter Tracking via Ensemble Learning

  • Authors: S. Moorthy, Y.H. Joo
  • Journal: Pattern Recognition
  • Volume: 139
  • Article Number: 109457
  • Year: 2023
  • Citations: 21
  • DOI/Link: [Check Pattern Recognition journal for more details]

4. Multi-Expert Visual Tracking Using Hierarchical Convolutional Feature Fusion via Contextual Information

  • Authors: S. Moorthy, Y.H. Joo
  • Journal: Information Sciences
  • Volume: 546
  • Pages: 996–1013
  • Year: 2021
  • Citations: 21
  • DOI/Link: [Check Information Sciences journal for more details]

5. Instinctive Classification of Alzheimer’s Disease Using fMRI, PET, and SPECT Images

  • Authors: E. Dinesh, M.S. Kumar, M. Vigneshwar, T. Mohanraj
  • Conference: 7th International Conference on Intelligent Systems and Control (ISCO)
  • Year: 2013
  • Citations: 15
  • Pages: Available in the ISCO conference proceedings.

Conclusion

Dr. Sathishkumar Moorthy is an exemplary researcher whose work significantly contributes to advancing AI, ML, and computer vision. His combination of academic rigor, industry experience, and impactful research publications makes him a strong candidate for the Best Researcher Award.