Mr. Muhammad Tauqeer Iqbal | Machine Learning | Best Researcher Award

Posted on by Computer Scientists Awards

Mr. Muhammad Tauqeer Iqbal | Machine Learning | Best Researcher Award

Mr. Muhammad Tauqeer Iqbal , Yangzhou University, China

Iqbal Muhammad Tauqeer is a passionate researcher and master’s student at Yangzhou University, China , specializing in the domain of Machine Learning 🤖. With a solid foundation in both industry and academia, he has combined practical management experience with cutting-edge AI research. His dedication to data science applications and computer vision has led to a notable publication recognized as a best paper, showcasing his potential in the rapidly evolving tech landscape 🌟.

Professional Profile

ORCID

🎓 Education Background

Iqbal is currently pursuing his Master’s degree at Yangzhou University, China 📚, where his academic focus is on machine learning and its applications in computer vision. His academic pursuits have been driven by a commitment to advancing AI-driven solutions in environmental monitoring and digital recognition systems.

💼 Professional Experience

Before his transition into research, Iqbal gained valuable industry experience as an Assistant Production Manager at OPPO Mobile Company Pakistan 📱 for over two years. This role provided him with deep insights into production workflows and industry standards, bridging the gap between theoretical learning and practical application.

🏆 Awards and Honors

Iqbal’s research has already earned accolades, with his paper titled “A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy” being recognized as a Best Paper 🥇. This early recognition is a testament to the impact and novelty of his contributions to AI-powered environmental diagnostics.

🔬 Research Focus

His research interests lie primarily in Machine Learning, Deep Learning, Transfer Learning, and Computer Vision 🧠📊. He is particularly focused on applying these techniques to UV–Vis Spectroscopy and digital display recognition. He is currently working on a second research project that extends his work in pattern recognition and visual AI.

🔚 Conclusion

With a unique blend of industrial management experience and academic rigor, Iqbal Muhammad Tauqeer is emerging as a promising contributor to the field of Artificial Intelligence. His work in machine learning models for environmental monitoring reflects not only his technical skills but also his commitment to impactful innovation 🌍🔍.

📚 Publication Top Note

  1. Title: A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy
    Journal: Journal of Imaging
    Publisher: MDPI
    Published Year: 2025

 

Avirup Roy | Machine Learning |Machine Learning Research Award

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Mr. Avirup Roy | Machine Learning |Machine Learning Research Award

PhD Student, Michigan State University, United States

Dr. Avirup Roy is a dedicated researcher and engineer specializing in networked embedded and wireless systems. Currently pursuing his PhD at Michigan State University, his work focuses on developing self-learning mechanisms for embedded hardware systems with limited computational resources. With a solid foundation in electronics and communication engineering, Avirup has gained extensive experience in both academia and industry, contributing to projects ranging from smart malaria detection to automated power management systems. His technical skills span machine learning, embedded systems, cloud computing, and web development. Beyond his professional life, Avirup is passionate about Indian classical music, photography, and swimming. 🌟📚🎵📷🏊‍♂️

Profile

ORCID

 

Education🎓

Michigan State University, East Lansing, MI, US PhD in Electrical and Computer Engineering (2020-Present). Dissertation: Self-learning mechanisms for Embedded hardware systems with limited computational resources. GPA: 3.75/4Maulana Abul Kalam Azad University of Technology, Kolkata, WB, India Bachelor of Technology (BTech) in Electronics and Communication Engineering (2013-2017)

Experience💼

Graduate Research Assistant, Michigan State University (Sep 2020 – Jul 2023),Developed an android and website application for smart malaria detection involving cloud database integration. Graduate Teaching Assistant, Michigan State University (Aug 2023 – Present), Instructed and graded labs for Embedded Cyber-physical Systems, VLSI Systems, and Digital Control courses. ICER Cloud Computing Fellow, Michigan State University (Sep 2023 – Present), Implemented Azure cloud resources in semi-supervised federated learning for embedded devices. Programmer Analyst, Cognizant Technology Solutions (Dec 2017 – Jul 2020), Developer and support analyst for ASP.NET based applications of MetLife Inc. Intern, Calcutta Electric Supply Corporation (CESC) Limited (Jul 2016 – Aug 2016), Worked on automated power management systems using SCADA communication. Intern, Bharat Sanchar Nigam Limited (BSNL) (Jun 2015 – Aug 2015), Explored general trends in wireless communication. Undergraduate Researcher, Maulana Abul Kalam Azad University of Technology (2015-2016), Presented research at various international conferences and served as the vice-president of SPIE Student Chapter.

Research Interests🔍

Embedded Machine Learning: Focused on developing efficient learning algorithms for resource-constrained devices.
Networked Embedded Systems: Exploring self-learning mechanisms and their applications in real-world scenarios.
Cloud Computing: Leveraging cloud resources for semi-supervised federated learning.
VLSI Systems: In-depth study and teaching of Very-Large-Scale Integration systems.
Cyber-Physical Systems: Research on embedded systems interacting with physical processes.

Awards🏆

National Social Entrepreneurship Programme (2014): Secured 2nd position for the ‘Hand-Made Paper Industry’ project.
SPIE Smart Structures and Non-destructive Evaluation Conference (2016): Presented research in Las Vegas, Nevada.
EAPE Conference (2015): Presented research on emerging areas of photonics and electronics.
Graduate Fellowships: Awarded multiple fellowships during PhD for research and teaching excellence.

Publications

Semi-Supervised Learning Using Sparsely Labelled Sip Events for Online Hydration Tracking Systems
A. Roy, H. Dutta, A. K. Bhuyan, and S. K. Biswas, 2023, International Conference on Machine Learning and Applications (ICMLA).
Cited by: 3 articles.

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation
Roy, A., Dutta, H., Griffith, H., & Biswas, S., 2022, Sensors.
Cited by: 5 articles.