Md Ibrahim Shikder Mahin | Computational Modeling | Best Researcher Award-1831

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Mr. Md Ibrahim Shikder Mahin | Computational Modeling | Best Researcher Award

Bangladesh University of Business and Technology (BUBT), Bangladesh

👨‍🎓Profile

🎓 Early Academic Pursuits

Md. Ibrahim Shikder Mahin began his academic journey with a strong foundation in science at Gandaria High School. His passion for technology and engineering led him to Government Shaheed Suhrawardy College, where he pursued the Higher Secondary School Certificate (HSC) in Science. Recognizing the significance of electrical and electronics engineering in shaping the future of robotics, AI, and blockchain technology, he enrolled at the Bangladesh University of Business & Technology (BUBT) for a Bachelor of Science (B.Sc.) in Electrical and Electronics Engineering (EEE), equipping himself with the necessary knowledge to contribute to advanced research and industry developments.

💼 Professional Endeavors

Md. Ibrahim Shikder Mahin has built a diverse professional career spanning multiple industries, including robotics, AI, blockchain, and electrical engineering. He is currently serving as a Research Assistant at Bangladesh University of Business & Technology (BUBT) since January 2025, where he is involved in cutting-edge research in AI, blockchain, and robotics. Prior to this role, he gained hands-on experience as a Supply Chain Management Intern at Vivo, where he worked on logistics optimization, inventory management, and supply chain automation.

🔬 Contributions and Research Focus

Md. Ibrahim Shikder Mahin is dedicated to advancing AI-driven systems, blockchain security, and IoT-enabled automation. His research focuses on integrating deep learning, image processing, and decentralized finance (DeFi) technologies into real-world applications. One of his key contributions is the Crypto Payment & NFT Minting System in Hitmakr, where he developed a blockchain-based payment solution integrating ERC-20 token transfers and ERC-1155 NFT subscriptions.

Another innovative project he led is the AI-Based Fire Resistance System, which utilizes OpenCV, YoloV11, Google Speech Recognizer, and Raspberry Pi to detect and suppress fires efficiently. His work on Weather Forecasting for Farming demonstrates the use of deep-learning time series models to assist farmers in predicting the best crops for specific climatic conditions. Additionally, his project on Forecasting Total Cloud Coverage in the Sky implements hybrid AI models to enhance solar farm efficiency by predicting cloud coverage. His research and development efforts continue to push the boundaries of technology and automation.

🌍 Impact and Influence

Through his extensive work in academic research, industrial projects, and blockchain innovations, Md. Ibrahim Shikder Mahin has significantly contributed to the advancement of AI, IoT, and decentralized applications. His projects aim to bridge the gap between cutting-edge technology and practical implementation, particularly in areas such as agriculture, energy, and finance. His innovations in automation, AI-driven robotics, and deep learning applications are shaping the future of smart technology and digital transformation.

📑 Academic Cites

As a researcher with a focus on AI, blockchain, and robotics, his contributions have the potential to be widely cited in academic research related to AI-driven automation, electrical engineering advancements, and blockchain applications. His work in integrating AI into power systems, security protocols, and sustainable energy solutions paves the way for future academic studies and industrial applications.

🛠️ Technical Skills

Md. Ibrahim Shikder Mahin possesses a broad range of technical skills that allow him to excel in AI development, blockchain programming, and IoT system integration. His programming expertise includes Python, C, and Solidity, which he applies in deep learning, smart contract development, and embedded system programming. He has extensive experience with AI frameworks such as TensorFlow, OpenCV, and YOLO, enabling him to develop computer vision applications and predictive analytics models.

His blockchain development experience includes smart contract deployment, Ethereum-based applications, and NFT development. In the IoT and robotics domain, he has worked with Raspberry Pi, Arduino, and embedded systems, focusing on automation and industrial robotics. Additionally, his background in electrical engineering includes power distribution, circuit design, and renewable energy integration, making him a well-rounded technology professional.

👨‍🏫 Teaching Experience

As a Research Assistant at BUBT, Md. Ibrahim Shikder Mahin has been actively involved in mentoring students and guiding research projects in blockchain applications, AI modeling, and robotics innovations. His passion for teaching and knowledge sharing has enabled him to train students in emerging technologies, helping them develop hands-on experience with real-world applications. His ability to simplify complex technical concepts makes him a valuable mentor for aspiring engineers and researchers.

🚀 Legacy and Future Contributions

Md. Ibrahim Shikder Mahin is committed to pioneering technological advancements in AI-driven robotics, blockchain security, and sustainable energy solutions. His long-term vision is to develop intelligent automation systems that contribute to smart city initiatives, energy-efficient solutions, and decentralized financial systems. He aspires to revolutionize the field of AI and blockchain by integrating automation, security, and scalability into real-world applications.

📖Notable Publication

Real-Time Rapid Accident Detection for Optimizing Road Safety in Bangladesh
  • Authors: Md Shamsul Arefin, Md Ibrahim Shikder Mahin, Farzana Akter Mily
  • Journal: Heliyon
  • Year: 2025

Yang Yang | Computational Modeling | Best Researcher Award

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Mr. Yang Yang | Computational Modeling | Best Researcher Award

National University of Sciences & Technology (NUST), China

👨‍🎓Profiles

🌱 Early Academic Pursuits

Yang Yang's academic journey began with a strong foundation in artificial intelligence and data mining. His keen interest in open-world data mining led him to explore innovative methods for handling complex, evolving datasets. As a student, he displayed exceptional analytical abilities and a deep curiosity for AI-driven solutions. This early dedication laid the groundwork for his later contributions to AI research and interdisciplinary applications.

💼 Professional Endeavors

Currently a professor at Nanjing University of Science and Technology, Yang Yang has established himself as a leading researcher in artificial intelligence. His professional journey includes significant contributions to theoretical and applied AI, particularly in the fields of smart agriculture and smart education. As an active member of the IEEE, he has engaged in numerous high-impact projects, shaping the landscape of AI research and its real-world implementations.

🔬 Contributions and Research Focus

Yang Yang specializes in open-environment data mining, addressing key challenges such as modal interaction, decision adaptation, and model evolution. His work has resulted in groundbreaking solutions for reliable multi-modal representation, robust inference decision-making, and continuous evolution modeling. These advancements have significantly improved the robustness of AI models in dynamic environments, making them more adaptable to changes in data features, labels, and content across various tasks. His research has played a pivotal role in enhancing AI-driven decision-making in practical applications.

🌍 Impact and Influence

With an impressive citation index of 1,289, Yang Yang's research has been widely recognized and referenced by esteemed academicians and Fellows of globally renowned societies such as IEEE, ACM, and AAAS. His innovative methodologies have influenced AI research and have been successfully implemented in smart agriculture and smart education, contributing to advancements in precision farming and intelligent learning systems.

📚 Academic Citations and Recognitions

Yang Yang has published 22 papers in top-tier SCI, IEEE, and ACM journals, many of which are considered foundational in open-world data mining. His outstanding contributions earned him the Best Paper Award at ACML 2017, highlighting his excellence in AI research. Additionally, his papers have been referenced in prestigious international journals and conferences, further establishing his authority in the field.

🛠️ Technical Skills

Yang Yang possesses expertise in:
✅ Open-world data mining
✅ AI-driven decision-making models
✅ Multi-modal representation learning
✅ Continuous evolution modeling
✅ Smart agriculture and education applications

His ability to bridge AI theory with practical applications has set new benchmarks in interdisciplinary AI research.

🎓 Teaching Experience

As a professor, Yang Yang is deeply committed to mentoring and guiding students in the fields of AI and data science. His expertise has helped shape the next generation of AI researchers by providing them with a strong foundation in theoretical and applied AI. His involvement in prestigious AI competitions, where he has won 20 championships, further demonstrates his dedication to both learning and teaching.

🔍 Research Projects and Patents

Yang Yang has led several high-profile research projects, including the Young Scientists Project of the National Key Research and Development Program on Autonomous Software for the Application of Scientific Data in Agricultural Breeding. His research has resulted in three patents, showcasing his ability to transform theoretical AI advancements into tangible, real-world innovations.

🚀 Legacy and Future Contributions

Yang Yang’s research continues to push the boundaries of AI by focusing on the development of more adaptive and resilient AI models. His contributions to smart agriculture and smart education are paving the way for future innovations in AI-driven industries. His legacy will be defined by his ability to bridge the gap between theoretical AI research and its practical, real-world applications. Moving forward, he aims to expand his research into more interdisciplinary fields, further enhancing AI's impact on society.

📖Notable Publications

Adaptive deep models for incremental learning: Considering capacity scalability and sustainability
Authors: Y. Yang, D.W. Zhou, D.C. Zhan, H. Xiong, Y. Jiang
Journal/Conference: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
Year: 2019

Complex object classification: A multi-modal multi-instance multi-label deep network with optimal transport
Authors: Y. Yang, Y.F. Wu, D.C. Zhan, Z.B. Liu, Y. Jiang
Journal/Conference: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
Year: 2018

Learning to classify with incremental new class
Authors: D.W. Zhou, Y. Yang, D.C. Zhan
Journal/Conference: IEEE Transactions on Neural Networks and Learning Systems
Year: 2021

Deep learning for fixed model reuse
Authors: Y. Yang, D.C. Zhan, Y. Fan, Y. Jiang, Z.H. Zhou
Journal/Conference: Proceedings of the AAAI Conference on Artificial Intelligence
Year: 2017

Semi-supervised multi-modal multi-instance multi-label deep network with optimal transport
Authors: Y. Yang, Z.Y. Fu, D.C. Zhan, Z.B. Liu, Y. Jiang
Journal/Conference: IEEE Transactions on Knowledge and Data Engineering
Year: 2019