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

Orcid

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) 📚

Yunge Zou | Computer Science | Best Scholar Award

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Dr. Yunge Zou | Computer Science | Best Scholar Award

Dr. Yunge Zou, Chongqing University, China

Dr. Yunge Zou is a Ph.D. scholar at Chongqing University, specializing in hybrid powertrain design and battery degradation in the Department of Automotive Engineering. He is a talent under the Chongqing Excellence Program and a Shapingba Elite Talent (2023–2025). Dr. Zou has led key projects, including the National Key R&D Program, focusing on high-efficiency powertrain technologies. His contributions include innovative methods like Hyper-Rapid Dynamic Programming, which optimizes multi-mode hybrid powertrains. With multiple patents and high-impact publications, he collaborates with leading automotive firms like Chang’an New Energy, advancing sustainable transportation. 🚗🔋📚

 

Publication Profile

Orcid

Google Scholar

Academic and Professional Background 🔋

Dr. Yunge Zou earned his B.E. degree in Automotive Engineering from Chongqing University, China, in 2018. Currently, he is pursuing his Ph.D. in hybrid powertrain design and optimization at the Vehicle Power System Lab, Department of Automotive Engineering, Chongqing University. Recognized for his exceptional talent, Dr. Zou is part of the prestigious Chongqing Excellence Program and was honored as a Shapingba Elite Talent for 2023–2025. His research focuses on hybrid powertrain topology design, battery degradation, energy management systems (EMS), and enhancing battery life, contributing to sustainable transportation innovation. 📚🔧🌱

 

Research and Innovations 🚗

Dr. Yunge Zou is leading several groundbreaking research projects in the field of hybrid powertrain design and optimization. His work includes the National Key Research and Development Program of China on high-efficiency range extender assembly and electric vehicle integration (2022-2024), with a funding of 2.5 million yuan. He is also working on optimizing hybrid electric vehicle design through the National Science Fund for Excellent Young Scholars (2023-2025). Additionally, he contributes to various projects focusing on hybrid vehicle dynamics, energy efficiency, and low-emission technologies, backed by substantial funding from multiple prestigious organizations. 🛠️⚡

 

🛠️ Research Focus

Dr. Yunge Zou’s research primarily focuses on hybrid powertrain design and optimization for electric and range-extended vehicles. His work includes the development of control strategies and topology design for hybrid systems, aiming to improve fuel economy, efficiency, and reduce emissions. Dr. Zou has made significant advancements in aging-aware optimization and mode-switching mechanisms for multi-mode hybrid vehicles. His contributions also extend to battery degradation, energy management, and the computational efficiency of fuel economy assessment using innovative algorithms like Hyper Rapid Dynamic Programming (HR-DP). His work is instrumental in the evolution of transportation electrification. 🚗⚡

 

Publication Top Notes

  • “Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory” – Energy 242, 122944 (Cited by 14, 2022) 🔋
  • “Aging-aware co-optimization of topology, parameter and control for multi-mode input-and output-split hybrid electric powertrains” – Journal of Power Sources 624, 235564 (Cited by 1, 2024) ⚙️
  • “Design of optimal control strategy for range extended electric vehicles considering additional noise, vibration and harshness constraints” – Energy 310, 133287 (Cited by 1, 2024) 🚗
  • “Computationally efficient assessment of fuel economy of multi-modes and multi-gears hybrid electric vehicles: A Hyper Rapid Dynamic Programming Approach” – Energy, 133811 (Cited by 0, 2024) 🔧

Oussama Mounnan | Computer Science | Best Researcher Award

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Mr. Oussama Mounnan | Computer Science | Best Researcher Award

Mr. Oussama Mounnan, Paris 8 University, France

Based on the detailed information provided about Mr. Oussama Mounnan, he appears to be a strong candidate for the “Best Researcher Award” due to his extensive experience and achievements in the field of cybersecurity, deep learning, and biometric access control. Below is a summary of his qualifications and contributions:

Publication profile

Professional Experience

Mr. Mounnan has been working as a Security Engineer since October 2015 at Weberfly-group in Marrakech, Morocco. He is responsible for managing, administering, and configuring network security systems, including firewalls, routers, switches, and VPN access. His role also includes performing network traffic analysis, implementing security policies, conducting security audits, and managing incidents. Additionally, he has experience in ethical hacking and penetration testing using various tools. Previously, he co-founded OussamaWeb, where he focused on IT maintenance, web development, and application creation from 2007 to 2015.

Research and Academic Background

Mr. Mounnan is currently pursuing a PhD in Computer Science at Ibn Zohr University-Agadir, Morocco, in collaboration with Paris 8 University, France. His research focuses on speech recognition using deep learning for biometric access control, a field that intersects artificial intelligence and cybersecurity. He has previously conducted research at the Oscar laboratory of Cadi Ayyad University, where he designed and tested systems for access control within the context of Big Data.

Technical Skills and Certifications

He has a comprehensive skill set covering programming languages (HTML, C, Python, Java), network security, system administration, virtualization, and data management tools. His certifications include ITIL V4, Prince2 Foundation, and various cybersecurity and machine learning credentials from Google, Coursera, and Fortinet. These certifications underline his commitment to staying updated in the rapidly evolving fields of IT security and data science.

Education

Mr. Mounnan holds a Master’s degree in Services, System Security, and Networks from the University of Lorraine, France, and a Bachelor’s degree in Networks and Telecommunications from Université Littoral Côte d’Opale, France. He has also completed specialized training in software engineering and information systems.

Additional Skills and Interests

He is proficient in English, French, and German at an advanced level. His interests include swimming, martial arts, reading, music, and scientific research, reflecting a well-rounded personality committed to both personal and professional development.

Publication Top Notes

  • Privacy-aware and authentication based on blockchain with fault tolerance for IoT enabled fog computing 🌐🔐 | Cited by: 21 | Year: 2020
  • Decentralized access control infrastructure using blockchain for big data 📊🔗 | Cited by: 10 | Year: 2019
  • Using blockchain based authentication solution for the remote surgery in tactile internet 🏥🖥️ | Cited by: 5 | Year: 2021
  • Anomaly detection for big data security: a benchmark 🔍🔒 | Cited by: 3 | Year: 2021
  • Efficient Distributed Access Control using Blockchain for Big Data in Clouds ☁️📈 | Cited by: 3* | Year: 2019
  • A novel approach based on blockchain to enhance security with dynamic policy updating 🔄🔐 | Cited by: 1 | Year: 2020
  • A Review on Deep Anomaly Detection in Blockchain 📚🛡️  Year: 2024
  • Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control 🎤🧠  Year: 2023
  • Deep Learning-Based Speech Recognition System using Blockchain for Biometric Access Control 🧠🔗 Year: 2022
  • Towards a Privacy preserving Machine Learning based Access Control for the Internet of Things 🌐🤖  Year: 2022


Conclusion

Mr. Oussama Mounnan’s blend of practical experience, academic research, and extensive certifications make him a suitable candidate for the “Best Researcher Award.” His work in cybersecurity and deep learning, particularly in speech recognition for biometric access, highlights his significant contributions to these fields.