Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

Mr. Asif Mehmood, National university of technology, Pakistan

Asif Mehmood is a dedicated professional with a strong academic background and diverse expertise in computer sciences. Currently pursuing a PhD in Computer Sciences at COMSATS University Islamabad, Wah Campus, he holds a Master’s degree and a Bachelor’s degree in the same field. With a keen interest in machine learning and deep learning, Asif has contributed to notable publications in prestigious journals, focusing on human gait recognition and biometric techniques. His experience spans from research associate roles to lecturing positions at HITEC University Taxila, showcasing his commitment to academia and research. Asif’s technical proficiency includes programming languages such as MATLAB, JavaScript, and Java, along with extensive experience in project development and academic projects. He resides in Attock, Punjab, Pakistan, and is open to providing references upon request.

Professional Profile:

Scopus

🎓 Education:

Asif Mehmood has pursued a remarkable academic journey, demonstrating consistent excellence in his educational endeavors. He commenced his formal education with a Bachelor of Science in Computer Sciences (BSCS) from the University of Wah, spanning from 2013 to 2017, where he attained a commendable CGPA of 3.46 out of 4.0. Building upon this foundation, he pursued a Master of Science in Computer Sciences (MSCS) at COMSATS University Islamabad, Wah Campus, from 2018 to 2020, achieving an impressive CGPA of 3.84. Asif further advanced his academic pursuits by undertaking a PhD in Computer Sciences at the same institution, currently in progress, with an outstanding CGPA of 3.94 thus far.

💼 Experience:

Asif Mehmood has enriched his professional experience through roles at HITEC University Taxila. He commenced as a Research Associate in January 2022, where he actively contributed to research endeavors until June 2022. Building upon his expertise, Asif transitioned into the role of Lecturer in Computer Science at the same institution in September 2022, a position he currently holds. These roles have allowed Asif to apply his academic knowledge and research skills in a practical setting while also nurturing the next generation of computer science professionals through teaching and mentorship.

📝 Projects:

Asif Mehmood has demonstrated his proficiency in software development and research through various notable projects. Among these, he developed a Document Clustering Search Engine using Java and MySQL, showcasing his skills in both programming and database management. Additionally, his thesis focused on Prosperous Human Gait Recognition, employing Machine Learning techniques within MATLAB, highlighting his expertise in this advanced field. Furthermore, Asif has undertaken diverse academic projects encompassing Assembly Language programming, Android app development, and web development, reflecting his versatility and innovative approach to problem-solving in the realm of computer science.

Publication Top Notes:

Human Gait Recognition by using Two Stream Neural Network along with Spatial and Temporal Features
- Authors: Mehmood, A.; Amin, J.; Sharif, M.; Kadry, S.
- Journal: Pattern Recognition Letters, 2024, 180, pp. 16–25
- Citations: 0
Prosperous Human Gait Recognition: an end-to-end system based on pre-trained CNN features selection
- Authors: Mehmood, A.; Khan, M.A.; Sharif, M.; Riaz, N.; Ashraf, I.
- Journal: Multimedia Tools and Applications, 2024, 83(5), pp. 14979–14999
- Citations: 24
TS2HGRNet: A paradigm of two stream best deep learning feature fusion assisted framework for human gait analysis using controlled environment in smart cities
- Authors: Khan, M.A.; Mehmood, A.; Kadry, S.; Alsubai, S.; Alqatani, A.
- Journal: Future Generation Computer Systems, 2023, 147, pp. 292–303
- Citations: 3
Human gait analysis for osteoarthritis prediction: a framework of deep learning and kernel extreme learning machine
- Authors: Khan, M.A.; Kadry, S.; Parwekar, P.; Khan, J.A.; Naqvi, S.R.
- Journal: Complex and Intelligent Systems, 2023, 9(3), pp. 2665–2683
- Citations: 23
Human gait recognition: A deep learning and best feature selection framework
- Authors: Mehmood, A.; Khan, M.A.; Tariq, U.; Mostafa, R.R.; ElZeiny, A.
- Journal: Computers, Materials and Continua, 2021, 70(1), pp. 343–360
- Citations: 8

Mr Farshad Bolouri: Artificial Intelligence | Best Researcher Award

Research Associate at Texas Tech University, United States

Farshad Bolouri is an accomplished researcher with a Master’s degree in Electrical Engineering from Texas Tech University, specializing in Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing. His research interests focus on Agricultural Robotics, Precision Farming, and Machine Learning in Digital Agriculture.

🎓 Education :

Farshad Bolouri, a mastermind in Electrical Engineering, graduated with a Master of Science from Texas Tech University in August ’23 🎓. His stellar GPA of 3.86 reflects his dedication to his studies, with a focus on cutting-edge fields like Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing 🌐🤖.

Prior to his master’s journey, Farshad excelled in his Bachelor’s in Computer Engineering, graduating Summa Cum Laude with a perfect GPA of 4.0 in May ’21 🏆. He added a touch of diversity with a minor in Mathematics and Computer Science, earning accolades such as the Highest Ranking Graduate from the College of Engineering and the ‘Outstanding Design Project’ award from ECE 🏅🔧.

Farshad’s academic journey is not just about grades; it’s a testament to his passion for pushing boundaries and achieving excellence in the realm of technology and engineering 🚀.

🔍 Research Interests :

Farshad Bolouri’s research interests are a captivating blend of technology and agriculture 🌾. In the realm of Agricultural Robotics and Precision Farming, he’s delving into the development of custom robotic solutions. His focus lies on intelligent multi-sensor integration, aiming to optimize in-field plant phenotyping specifically for specialty crops 🤖🌱. Venturing into the realm of Machine Learning in Digital Agriculture, Farshad applies cutting-edge AI/ML techniques for data interpretation. His goal is to enable accurate high-throughput phenotyping and precise yield estimation, revolutionizing the way we approach modern farming practices 📊🌾. In the domain of 3D Computer Vision for Field Mapping, Farshad employs advanced techniques for accurate and real-time field mapping. By integrating 3D computer vision, he aims to enhance the precision and efficiency of agricultural decision-making processes 🌐🚜.

Research Focus:

Farshad Bolouri’s research focus spans across Agricultural Robotics and Precision Farming 🌾, as evident in his groundbreaking work on “CottonSense.” This High-Throughput Field Phenotyping System leverages intelligent multi-sensor integration for optimized cotton fruit segmentation and enumeration on edge devices, revolutionizing cotton farming practices 🤖🌱. Additionally, his contribution to improving short-term multiphase production forecasts in unconventional tight oil reservoirs showcases a keen interest in merging technology with geoenergy science and engineering ⛽🔍. Farshad’s commitment to advancing phenotyping for flower abortion in soybeans through image analysis and machine learning demonstrates a versatile expertise in the intersection of agriculture, computer vision, and AI 🌺🔬.

Publications Top Notes :

CottonSense: A high-throughput field phenotyping system for cotton fruit segmentation and enumeration on edge devices