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

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

Md Ibrahim Shikder Mahin | Computational Modeling | Best Researcher Award

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

Bangladesh University of Business and Technology (BUBT), Bangladesh

👨‍🎓Profiles

🎓 Academic Background

Md Ibrahim Shikder Mahin is a Bachelor of Science (B.S.) graduate in Electrical and Electronics Engineering from Bangladesh University of Business and Technology (BUBT), where he maintained a CGPA of 3.41/4.0 (2019-2024). His earlier academic journey includes:  Higher Secondary School Certificate (HSC) – Science from Government Shaheed Suhrawardy College (2017-2019), with a GPA of 3.75/5.0. Secondary School Certificate (SSC) – Science from Gandaria High School (2005-2017).

🚀 Passion for Technology & Innovation

As a passionate technophile, Mr. Mahin specializes in:
✔️ Computational Modeling & Image Processing 🖥️ – Applying advanced algorithms for visual data analysis.
✔️ Machine Learning & Deep Learning 🧠 – Developing intelligent systems for automation and decision-making.
✔️ Robotics & AI 🤖 – Exploring automation, smart systems, and industrial robotics.
✔️ Blockchain Technology 🔗 – Investigating decentralized applications and cryptographic security.

His strong foundation in Python programming allows him to implement innovative AI and image processing solutions, contributing to cutting-edge research and real-world applications.

📊 Technical Expertise

Mr. Mahin has hands-on experience in various AI and computational technologies, including:
✔️ Programming Languages: Python, MATLAB
✔️ Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-learn
✔️ Image Processing: OpenCV, Computer Vision Techniques
✔️ Robotics & AI: Embedded Systems, IoT Integration
✔️ Blockchain & Cryptography: Smart Contracts, Decentralized Systems

🎯 Research & Career Aspirations

Mr. Mahin is committed to driving innovation and fostering collaboration in the tech community. His future goals include:
🔹 Developing intelligent automation systems using AI & robotics.
🔹 Advancing deep learning applications for medical and industrial imaging.
🔹 Exploring the intersection of blockchain and AI for secure, decentralized solutions.
🔹 Contributing to open-source projects and global research communities.

🏆 Conclusion

Md Ibrahim Shikder Mahin is a highly motivated researcher and engineer in the fields of AI, deep learning, and computational modeling. His passion for technology, robotics, and blockchain continues to shape his journey toward innovation and impactful contributions in the digital era.

📖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

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

 

Hang Xie | Computational Modeling | Best Researcher Award

Assist. Prof. Dr. Hang Xie | Computational Modeling | Best Researcher Award

Huanghuai University, China

👨‍🎓Profiles

🎓 Early Academic Pursuits

Dr. Hang Xie’s academic journey began with a strong foundation in ocean engineering, focusing on ship slamming loads and fluid physics. His early research delved into computational fluid dynamics (CFD) algorithms, allowing him to explore the complexities of fluid-structure interactions. His passion for maritime engineering led him to investigate asymmetric water entry phenomena, contributing to the understanding of slamming loads on ships. Through rigorous experimentation and numerical analysis, he developed a keen interest in hydrodynamic impact analysis, which later became the cornerstone of his research career.

💼 Professional Endeavors

Currently serving as an Assistant Professor at Huanghuai University, Dr. Xie is a dedicated researcher in marine hydrodynamics and impact loads. Over the years, he has secured multiple research grants, including funding from the National Natural Science Foundation of China, the Science and Technology Innovation Youth Project of Zhumadian City, and the Project of Science and Technology of Henan Province of China. His expertise in fluid physics and ship slamming has positioned him as a key figure in the field of computational marine engineering. With an emphasis on solving practical engineering problems, his research has provided valuable insights into the behavior of fluid forces acting on ships and offshore structures.

🔬 Contributions and Research Focus

Dr. Xie has made significant contributions to the development of asymmetric slamming theory by combining experimental studies and numerical simulations. His research has led to the discovery of flow separation mechanisms, jet flow formation, and bubble evolution in asymmetric water entry. By incorporating the Volume of Fluid (VOF) method and introducing artificial convection terms, he has established a high-fidelity solver for simulating two-dimensional multiphase flows, marking a significant theoretical breakthrough. These advancements have enhanced the accuracy of maritime impact load simulations and influenced both theoretical research and practical ship design applications. His work has contributed to improving computational methods that predict the structural response of vessels subjected to extreme slamming events.

🌍 Impact and Influence

Dr. Xie’s research has gained widespread recognition, accumulating over 300 citations in leading journals such as Physics of Fluids (POF), International Journal of Marine Science (IJMS), China Shipbuilding (CS), Marine Structures (MS), and Advances in Ocean Physics (AOP). His findings have been instrumental in improving ship safety, reducing structural damage from slamming loads, and enhancing computational models for fluid-structure interactions. His work has been widely referenced by researchers and engineers working on marine structure optimization, further establishing his reputation as a prominent scholar in the field.

📖 Academic Citations and Publications

With 24 published research papers in prestigious SCI and Scopus-indexed journals, Dr. Xie has established himself as a leading scholar in marine engineering and computational fluid dynamics. His research findings have been frequently referenced by experts in ocean engineering, naval architecture, and hydrodynamics. His studies have contributed to a deeper understanding of how ships and offshore structures interact with turbulent and high-impact marine environments.

🛠️ Technical Skills

Dr. Xie possesses expertise in CFD simulations, numerical modeling, and high-fidelity solvers for multiphase flows. His technical skills include computational fluid dynamics (CFD), the Volume of Fluid (VOF) method for multiphase flow modeling, hydrodynamic impact analysis, ship slamming load simulations, and experimental and numerical fluid mechanics. His deep understanding of numerical algorithms and experimental methodologies allows him to develop advanced computational tools that improve the accuracy of ship hydrodynamic analyses.

🎓 Teaching Experience

As an Assistant Professor, Dr. Xie actively engages in teaching marine hydrodynamics, computational modeling, and ship structure analysis. His mentorship has inspired students to explore fluid-structure interactions and advanced computational methods, fostering the next generation of ocean engineers and researchers. He has played a crucial role in guiding students through complex hydrodynamic simulations and experimental studies, ensuring they develop the technical skills required for cutting-edge marine research.

🏆 Legacy and Future Contributions

Dr. Xie’s pioneering work in asymmetric slamming phenomena and high-fidelity flow solvers continues to shape the field of marine engineering. With four patents under process and ongoing collaborations with Huilong Ren, Jialong Jiao, and Hui Li, his research is expected to advance maritime safety, enhance numerical modeling accuracy, and influence future ship designs. His dedication to ship slamming physics and fluid-structure coupling ensures that his legacy will endure as a foundation for next-generation hydrodynamic studies. Moving forward, he aims to expand his research into innovative computational techniques that will further refine our understanding of complex maritime environments.

📖Notable Publications

Experimental and CFD analysis: Effects of bottom appendages on the slamming characteristics of rigid hull structures during water entry

Authors: Y. Ping, Yanna; J. Wang, Jingzhi; H. Xie, Hang; F. Liu, Fang; X. Liu, Xinyu

Journal: Ocean Engineering

Year: 2025

Numerical investigation on the slamming loads of a truncated trimaran hull entering regular waves

Authors: P. Yu, Pengyao; S. Qu, Song; Q. Wang, Qiang; H. Xie, Hang

Journal: Applied Ocean Research

Year: 2024

Characterization on the impact load of a local corner region of a liquid tank entering water

Authors: H. Xie, Hang; J. Li, Jiawang; S. Guijie, Shi; Deyu Wang; H. Tang, Haoyun

Journal: Ocean Engineering

Year: 2024

 

Sung Woo Moon | Computational Modeling | Best Researcher Award

Assoc. Prof. Dr. Sung Woo Moon | Computational Modeling | Best Researcher Award

Nazarbayev University, Kazakhstan

👨‍🎓Profiles

🌱 Early Academic Pursuits

He began his academic journey with a passion for engineering and sustainable development. He pursued a Ph.D. in Civil Engineering at the University of Illinois at Urbana-Champaign, focusing on seismic hazard analysis and sustainable soil stabilization. His academic foundation, paired with rigorous training in geotechnical engineering, laid the groundwork for a distinguished career in research and teaching.

🛠️ Professional Endeavors

As an Associate Professor at Nazarbayev University, Kazakhstan, He has over two decades of professional experience in seismic hazard analysis, geophysical site investigations, and sustainable infrastructure development. He has actively engaged in cross-disciplinary collaborations with prestigious institutions, including the University of Illinois, Hanyang University, and Purdue University, to address complex environmental and engineering challenges.

🔬 Contributions and Research Focus

His research centers on innovative and sustainable solutions in geotechnical engineering. He has made significant contributions to the development of eco-friendly materials, such as utilizing industrial byproducts like Phosphogypsum, GGBFS, and BOF slag for soil stabilization. His work on carbon capture and storage (CCS) using serpentinite rocks is a testament to his commitment to combating industrial CO₂ emissions. These efforts align with global climate goals and exemplify his dedication to environmental sustainability.

🌍 Impact and Influence

His pioneering research has garnered significant recognition, with over 50 publications in SCI and Scopus-indexed journals. His contributions have advanced the fields of geotechnical engineering and environmental sustainability, providing scalable solutions for resilient infrastructure and climate change mitigation. His projects, funded by competitive grants such as the NU Faculty-Development Competitive Research Grants, underscore his influence in academia and industry.

📚 Academic Citations and Publications

His extensive body of work includes over 50 published papers and a book (ISBN: 978-3-031-43454-9). His research is widely cited by peers, reflecting his impact in the academic community. He has also served on editorial boards, contributing to the advancement of scientific discourse in his field.

🧰 Technical Skills

He possesses expertise in geophysical site investigations, seismic hazard analysis, sustainable soil stabilization, and advanced CCS technologies. His ability to integrate traditional engineering principles with modern technologies demonstrates his technical acumen and innovative approach to problem-solving.

🎓 Teaching Experience

As an educator, He is committed to inspiring the next generation of engineers. At Nazarbayev University, he has designed and taught courses in civil and environmental engineering, emphasizing hands-on learning and practical applications. His mentorship has guided students toward success in research and industry.

🌟 Legacy and Future Contributions

He envisions a future where engineering solutions are both innovative and sustainable. He aims to continue his work on developing eco-friendly construction materials and advancing CCS technologies, contributing to global sustainability efforts. His legacy lies in his ability to blend interdisciplinary research with practical applications, leaving a lasting impact on the fields of engineering and environmental science.

📖Notable Publications

 

Sicong Ma | Theoretical and Computational Chemistry | Best Researcher Award

Assoc. Prof. Dr. Sicong Ma | Theoretical and Computational Chemistry | Best Researcher Award

Shanghai Institute of Organic Chemistry, China

👨‍🎓Profiles

🎓 Early Academic Pursuits

Dr. Sicong Ma, born in March 1992, began his academic journey with a strong foundation in applied chemistry at the China University of Petroleum (Beijing), where he completed his Bachelor of Science in 2013. He continued at the same institution for a Master's degree in Chemistry, working under the guidance of Professor Zhen Zhao until 2016. His academic path led him to Fudan University, where he earned his Ph.D. in Physical Chemistry in 2019 under Professor Zhi-Pan Liu. Here, he developed his expertise in theoretical and computational chemistry, laying the groundwork for his future contributions to catalysis and machine learning.

🏢 Professional Endeavors

After completing his Ph.D., He joined Fudan University as a postdoctoral researcher, continuing his work with Professor Zhi-Pan Liu until 2021. In August 2021, he joined the Shanghai Institute of Organic Chemistry as an Assistant Researcher. Recently promoted to Associate Professor, He has led several projects funded by prestigious institutions, including the National Natural Science Excellent Youth Fund, Shanghai Municipal Science and Technology Commission, and the China Postdoctoral Fund.

🔍 Contributions and Research Focus

His research interests span a unique blend of machine learning and catalysis. His expertise extends across both homogeneous and heterogeneous catalysis, with a particular focus on: Machine Learning and Heterogeneous Catalysis: He has conducted research on syngas-to-olefins conversions on OX-ZEO catalysts, propane hydrogenation, and similar transformations, Machine Learning and Homogeneous Catalysis: His work includes studies on the carbonylation of olefins and the development of a metal-phosphine ligand catalyst database, Zeolite Chemistry: He is also active in studying the mechanisms of zeolite formation and their applications in catalysis, contributing significantly to zeolite-related database construction.

📈 Impact and Influence

He has made substantial contributions to the field, publishing more than 20 papers in renowned journals such as Nature Catalysis, Nature Communications, and ACS Catalysis. Notably, he has served as first or corresponding author on 15 of these publications, solidifying his role as a leader in his field. His work has garnered attention and citations, reflecting his influence within theoretical and computational chemistry.

📚 Academic Achievements and Honors

Recognized for his academic excellence, He has received numerous awards and honors. He was honored with the Excellent Doctoral Dissertation Award from Fudan University in 2019, recognized as an Academic Star of Fudan University the same year, and awarded a Shanghai Super Postdoctoral Fellowship. Recently, he was inducted as a member of the Youth Innovation Promotion Association by the Chinese Academy of Sciences in 2023.

🛠️ Technical Skills

His technical expertise includes advanced machine learning algorithms for catalysis, computational modeling in chemistry, and extensive knowledge of catalysis mechanisms in both homogeneous and heterogeneous systems. His computational skills and programming knowledge enable him to create and manage large databases, crucial for his projects on zeolite and catalyst-related data.

📖 Teaching and Mentoring Experience

While focused primarily on research, He has also contributed to the academic community by mentoring postdocs and junior researchers in his lab. His guidance fosters a collaborative environment, ensuring that emerging researchers develop the skills necessary to advance in computational chemistry and catalysis.

🌐 Legacy and Future Contributions

His ongoing work promises to deepen the integration of machine learning in catalysis, with potential implications for sustainable energy solutions and efficient industrial chemical processes. As a young innovator and leader in his field, he is set to make lasting contributions, furthering both academic knowledge and practical applications in computational chemistry.

📖Notable Publications