Debajyoti Dhar | Computer Science | Best Researcher Award

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Mr. Debajyoti Dhar | Computer Science | Best Researcher Award

Mr. Debajyoti Dhar, Atal Bihari Vajpayee Indian Institute of Information Technology and Management Gwalior, India

Debajyoti Dhar is an ambitious B.Tech student with a CGPA of 7.67/10, specializing in Computer Science. He has honed his skills through impactful internships, including as a Software Development Engineer at Defence Research and Development Establishment and a Full Stack Developer at Edilitics Private Limited. Debajyoti has contributed to projects like a Decentralized FPS Game with NFT Marketplace and a Ticket Management Platform, showcasing his expertise in blockchain, cloud systems, and machine learning. He has co-authored IEEE conference papers and a journal paper, demonstrating his strong research capabilities. 💻📊🔗

 

Publication Profile

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Education Background

Debajyoti Dhar is currently pursuing a Bachelor of Technology in Computer Science at the Indian Institute of Information Technology and Management Gwalior. He started his academic journey in December 2021 and is expected to graduate in July 2025. With a CGPA of 7.67/10.00, Debajyoti has demonstrated a strong academic performance, excelling in his coursework. His education has equipped him with a solid foundation in computer science, preparing him for advanced projects and research in areas such as software development, machine learning, and blockchain technology. 📚💻🚀

 

Professional Experience

Debajyoti Dhar has gained valuable experience through multiple internships, showcasing his expertise in software development. At Defence Research and Development Establishment (Dec 2022–Oct 2023), he developed a heavy gas detection model in Java and created a 2D plotter in Python for data visualization. During his time at Edilitics Private Limited (Apr–Jun 2023), he built a robust backend using FastAPI and enhanced development efficiency with CI/CD pipelines and Docker. At Mak Design Private Limited (May–Jul 2024), he created a real-time chat module with Django and ReactJS, ensuring end-to-end encryption. 💻🔧🚀

 

Achievements

Debajyoti Dhar has demonstrated exceptional skills through various achievements. As a freelance developer for Metarootz, he built a full-stack blockchain social media project using NodeJS, ExpressJS, and MongoDB for the backend, and NextJS with TailwindCSS for the frontend. He delivered a comprehensive 5-day training bootcamp on web app deployment automation with Docker, Kubernetes, and Github Actions for industry professionals. Debajyoti has also co-authored two IEEE conference papers on computer vision and deep learning and contributed to a machine learning paper in MDPI Sensors journal. Additionally, he solved 300+ DSA questions on GFG and LeetCode. 📈💻📚

 

Research Focus

Mr. Debajyoti Dhar has contributed significantly to machine learning and optimization techniques, particularly in the context of environmental prediction. His recent work, “Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale”, published in Sensors, demonstrates his expertise in applying advanced algorithms to solve agricultural and environmental challenges. The research focuses on soil organic carbon prediction using machine learning models, emphasizing scalability and efficiency. This aligns with his broader focus on data science, AI-driven predictions, and sustainable technologies to address complex real-world problems in various domains. 🌍🤖📊

 

Publication Top Notes  

  • Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale (2024) 📚

Imtiaz Ahmad | Computer Science | Best Researcher Award

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Imtiaz Ahmad | Computer Science | Best Researcher Award

Mr Imtiaz Ahmad, Hazara University Mansehra, Pakistan

Based on the provided information, Mr. Imtiaz Ahmad demonstrates significant potential as a candidate for the “Best Researcher Award.” Here’s an assessment of his qualifications:

Publication profile

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Educational Background

Mr. Imtiaz Ahmad holds a Master of Science in Computer Science from Hazara University Mansehra, graduating with an impressive CGPA of 3.71/4.00. His thesis focused on developing an adaptive and priority-based data aggregation and scheduling model for wireless sensor networks, showcasing his ability to tackle complex problems in this area. His Bachelor’s degree in Information Technology from the University of Malakand further laid the foundation for his technical expertise, although his CGPA of 2.95/4.00 was more modest. Nonetheless, his final year project on an online hospital management system reflects his ability to apply academic knowledge to real-world problems.

Research Contributions

Mr. Ahmad has made meaningful contributions to the field of computer science, particularly in wireless sensor networks and mobile edge computing. His publication in the Knowledge-Based Systems journal on adaptive and priority-based data aggregation and scheduling for wireless sensor networks is a strong indicator of his research capabilities. Additionally, his work on mobility prediction-based adaptive task migration in mobile edge computing, published in VFAST Transactions on Software Engineering, highlights his focus on cutting-edge issues in computer science. These publications in reputable journals underline his research aptitude and commitment to advancing the field.

Professional Experience

Mr. Ahmad has accumulated valuable teaching and technical experience through various roles. As a visiting lecturer at Hazara University and a computer science lecturer at other institutions, he has been responsible for planning and delivering lectures, assessing student work, and supervising final year projects. His involvement in these educational roles suggests a deep engagement with the academic community and a commitment to nurturing future researchers. His previous internship at Hazara University, where he addressed technical issues and assisted in setting up multimedia for conferences, adds to his practical experience.

Awards and Certifications

Mr. Ahmad has been recognized for his research potential early in his academic career, receiving the Best Student Researcher Award from the Department of Computer Science at Hazara University in 2020. Additionally, he was awarded a laptop through the Prime Minister’s Laptop Scheme for high achievers, which is a testament to his academic excellence. His professional certifications, including Microsoft Office Specialist and vocational training in computers, further bolster his technical skill set.

Conclusion

In conclusion, Mr. Imtiaz Ahmad’s solid academic background, impactful research publications, teaching experience, and recognized achievements make him a strong candidate for the “Best Researcher Award.” His work in wireless sensor networks and mobile edge computing is both relevant and innovative, positioning him well for continued contributions to the field of computer science. Therefore, he is indeed suitable for consideration for this prestigious award.

Publication top notes

Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Network

A Mobility Prediction Based Adaptive Task Migration in Mobile Edge Computing

 

 

Huilong Fan | Computer Science | Best Researcher Award

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Dr Huilong Fan |  Computer Science |  Best Researcher Award

assistant researcher at  University of Electronic Science and Technology of China

Huilong Fan is a research assistant at the University of Electronic Science and Technology of China, born in December 1992, and residing in Changsha, Hunan. He specializes in Edge Computing and Artificial Intelligence.

profile

Academic Background:

  • Ph.D. in Computer Science and Technology, Central South University (2019-2023)
    • Major: Satellite multi-intelligence collaborative computing, digital twins, swarm intelligence negotiation, multi-intelligence deep reinforcement learning, online scheduling, artificial intelligence, machine learning.
  • Master in Computer Science and Technology, Guizhou University (2015-2018)
    • Major: Medical big data, big data analysis and prediction, deep learning, multi-label data classification, natural language processing.
  • Bachelor in Network Engineering, Nanyang Institute of Technology (2010-2014)
    • Major: Computer Networks, Principles of Computer Composition, Operating Systems, Algorithm Design.

Professional Experience:

  • Data Analyst, Beijing Ark Hospital (June 2014-Sept 2015; Dec. 2023-Present)
    • Responsibilities: Data cleaning, analysis, and visualization, system development and maintenance, research on satellite networks, collaborative computing, and edge computing.
  • R&D Engineer, Hunan Lisen Data Technology Co Ltd (June 2018-Sept 2019)
    • Responsibilities: Algorithm design, multi-platform software architecture design, software development, database management, interface development and design.

Projects and Leadership:

  • Led projects on mixed integer programming for multi-process production scheduling, satellite and management software R&D, and real-time analysis methods for large-scale multi-source data based on supercomputing.
  • Participated in significant research such as intelligent analysis technology for TFDS images and resource allocation technology based on collaborative perception.

Awards and Patents:

  • Second prize in scientific and technological progress (2020)
  • First prize in the Guizhou Province Innovation and Entrepreneurship Competition (2016)
  • National third prize in the ‘Internet +’ College Students Innovation and Entrepreneurship Competition (2016)
  • Invention Patents: Multi-agent Space-based Information Network Task Scheduling Method (2021), Dynamic Reconfigurable Space-based Information Network Simulation and Computing System (2022).

Skills:

  • Proficient in software architecture design, Java, Python, C, and other programming languages.
  • Experienced in leading R&D teams and writing research project applications.

Research Focus in Computer Science:

Huilong Fan’s research in Computer Science spans several advanced and interdisciplinary areas, primarily focusing on:

  1. Satellite Multi-Intelligence Collaborative Computing:
    • Developing systems that allow multiple intelligent agents to work together effectively in satellite networks.
    • Utilizing collaborative algorithms to improve the efficiency and reliability of satellite communications and operations.
  2. Digital Twins:
    • Creating digital replicas of physical systems to simulate and analyze their real-world counterparts.
    • Applying digital twin technology to monitor, diagnose, and optimize satellite and network operations.
  3. Swarm Intelligence Negotiation:
    • Investigating algorithms that enable decentralized agents to coordinate and negotiate within a swarm.
    • Using swarm intelligence for tasks such as resource allocation and scheduling in dynamic environments.
  4. Multi-Intelligence Deep Reinforcement Learning:
    • Developing deep learning models that enable multiple intelligent agents to learn and adapt to complex environments.
    • Applying these models to solve problems in satellite networks and edge computing.
  5. Online Scheduling:
    • Researching methods for real-time scheduling of tasks and resources in dynamic and distributed systems.
    • Focusing on optimizing the allocation of contact windows in satellite communication networks.
  6. Artificial Intelligence and Machine Learning:
    • Applying AI and ML techniques to solve complex problems in big data analysis, prediction, and decision-making.
    • Emphasizing multi-label data classification and natural language processing for diverse applications.
  7. Medical Big Data:
    • Analyzing and predicting trends in medical data using big data technologies.
    • Developing models for deep learning and multi-label classification to enhance medical data interpretation and application.
  8. Graph-Driven Resource Allocation:
    • Utilizing graph theory and cooperative game theory to optimize resource allocation in Internet of Things (IoT) and satellite networks.
    • Developing adaptive scheduling algorithms for real-time and dynamic environments.

Through his extensive research, Huilong Fan aims to push the boundaries of what is possible in satellite communication, edge computing, and AI, contributing significantly to advancements in these fields.

Publication Top Notes:

  • Dynamic Network Resource Autonomy Management and Task Scheduling Method Li, X., Yang, J., Fan, H.
    Mathematics, 2023, 11(5), 1232. Citations: 6
  • A novel multi-satellite and multi-task scheduling method based on task network graph aggregation Fan, H., Yang, Z., Zhang, X., Long, J., Liu, L.
    Expert Systems with Applications, 2022, 205, 117565. Citations: 15
  • A Spatio-Temporal Graph Neural Network Approach for Traffic Flow Prediction Li, Y., Zhao, W., Fan, H.
    Mathematics, 2022, 10(10), 1754. Citations: 6
  • Quantum Digital Signature with Continuous-Variable Deng, X., Zhao, W., Shi, R., Ding, C., Fan, H.
    International Journal of Theoretical Physics, 2022, 61(5), 144. Citations: 3