Samsil Arefin Mozumder | Machine Vision | Best Researcher Award

Samsil Arefin Mozumder | Machine Vision | Best Researcher Award

Mr. Samsil Arefin Mozumder, China University of Mining and Technology, China.

Samsil Arefin Mozumder is a dedicated Master’s student at China University of Mining and Technology (CUMT) in Xuzhou, China, specializing in mechanical engineering, embedded machine learning, and robotics. His research focuses on IoT, machine vision, and sensor integration for industrial applications such as derailment detection and mining infrastructure anomaly detection. With a strong background in electronics and embedded systems, Samsil has contributed to multiple publications and is actively involved in projects enhancing intelligent systems for automation. He is passionate about advancing technology for real-world impactย ๐ŸŒ๐Ÿ”ง๐Ÿค–.

Publication Profile

Orcid
Googlescholar

Education & Experience:

  • China University of Mining and Technology (CUMT), 2022โ€“2025 (CGPA: 4.5/5)
    ๐ŸŽ“ย Bachelor of Science in Electrical and Electronic Engineering
  • East Delta University (EDU), Bangladesh, 2018โ€“2020 (CGPA: 3.26/4)
    ๐ŸŽ“ย Diploma in Electronics Technology
  • Chattogram Polytechnic Institute (CPI), Bangladesh, 2013โ€“2017 (CGPA: 3.12/4)
    ๐Ÿ’ผย Research Assistant
  • China University of Mining and Technology (CUMT), 2022โ€“Present
    ๐Ÿ’ผย Deputy Field Controller
  • OPSEED CO., (BD) LTD, 2020โ€“2021

Suitability for the Award

Mr. Samsil Arefin Mozumder is an excellent candidate for the Best Researcher Award, with a strong academic background and impressive research contributions in electronics, embedded machine learning, IoT, and robotics. Currently pursuing a Master’s in Mechanical Engineering at China University of Mining and Technology, he has published impactful work on intelligent systems, such as mining derailment detection and IoT-based water management. His innovative projects, including machine vision applications and autonomous robots, showcase his ability to tackle complex real-world challenges. Samsil’s interdisciplinary approach and commitment to advancing technology make him a standout researcher deserving of this prestigious recognition.

Professional Development

Samsil Arefin Mozumder’s professional development is rooted in a strong commitment to expanding his expertise in mechanical engineering, electronics, and machine learningย ๐Ÿค–. He has been involved in several cutting-edge research projects, such as derailment detection using machine vision on edge devices and smart IoT systems. His industry experience as a deputy field controller sharpened his problem-solving and project management skillsย ๐Ÿ› ๏ธ. Through his research assistantship at CUMT, he has further honed his skills in robotics, IoT, and sensor integration, contributing to publications in top conferences and journalsย ๐Ÿ“š.

Research Focus

Samsil Arefin Mozumder’s research focus is at the intersection ofย electronics, machine learning (ML), IoT, andย roboticsย ๐Ÿ”ง๐Ÿค–. He investigates embedded ML systems, edge AI, and computer vision for real-time anomaly detection and intelligent automationย ๐Ÿง . His work includes developing smart systems for mining infrastructure, including derailment detection, vertical shaft detection, and IoT-based solutions for environmental monitoringย ๐ŸŒฑ. With a passion for exploring innovative solutions in industrial automation and machine vision, Samsil aims to bridge the gap between cutting-edge technologies and practical, impactful applicationsย ๐ŸŒ๐Ÿ“ก.

Publication Highlights

  • Smart IoT-Biofloc water management system using Decision regression tree,ย 2021ย ๐Ÿ“˜๐ŸŒŠย –ย Cited by 12
  • Research on Vertical Shaft Detection System Based on CMOS-Camera and Lidar,ย IEEE Access, 2024ย ๐Ÿ“˜๐Ÿ”
  • Derailment Detection of Mining Shaft’s Rail Vehicle Using Machine Vision on Edge Device, 2024ย ๐Ÿ“…๐Ÿš‚
  • IRHA: An Intelligent RSSI based Home automation System, ย 2022ย ๐Ÿ“˜๐Ÿ 

Mr. Hongwei Wang | Object Detection Award | Best Researcher Award

Mr. Hongwei Wang | Object Detection Award | Best Researcher Award

Mr. Hongwei Wang, North Minzu University, China

๐ŸŽ“ Hongwei Wang pursued his undergraduate studies in Computer Science and Technology at Harbin Institute of Information Engineering, excelling in courses such as Software Engineering and Operating Systems. Currently pursuing a Master’s degree in Computer Technology at North Minzu University, he focuses on Pattern Recognition and Semantic Networks. Recognized with scholarships and awards for academic excellence, including the “Learning Star” award, Hongwei’s analytical prowess shines through participation in competitions like the National Postgraduate Mathematical Modeling Competition. Proficient in both academic and practical domains, he holds a College English Test 4 certification and adeptly utilizes office-related software. ๐Ÿ…๐Ÿ†

๐ŸŒย Professional Profile:

Scopus

๐ŸŽ“ Education:

Mr. Hongwei Wang pursued his undergraduate studies in Computer Science and Technology at Harbin Institute of Information Engineering, where he excelled in major courses such as Software Engineering, Operating Systems, and Internet Programming. Currently, he is pursuing a Master’s degree in Computer Technology at North Minzu University, focusing on Pattern Recognition, Semantic Network, and Knowledge Graph.

๐Ÿ… Honors and Awards:

Mr. Hongwei Wang’s academic achievements have been recognized with scholarships, including a first-class scholarship from the postgraduate school. He has also received accolades such as the “Learning Star” award during his undergraduate studies, highlighting his consistent commitment to academic excellence.

๐Ÿ† Competition:

Participation in prestigious competitions like the National Postgraduate Mathematical Modeling Competitions demonstrates Hongwei Wang’s analytical and problem-solving skills, further complementing his academic endeavors.

๐Ÿ’ป Skills:

Proficient in both academic and practical domains, Hongwei Wang holds a College English Test 4 certification and is adept at using office-related software. His multifaceted skill set empowers him to excel in diverse settings.

Publications Top Notes :

CCGL-YOLOV5: A cross-modal cross-scale global-local attention YOLOV5 lung tumor detection model

  • Published in Computers in Biology and Medicine in 2023
  • 3 Citations