Filip Rękas | Computational Modeling | Best Researcher Award

Mr. Filip Rękas | Computational Modeling | Best Researcher Award

Rzeszów University of Technology, Poland

👨‍🎓Profiles

🎓 Early Academic Pursuits

Mr. Filip Rękas began his academic journey at the Rzeszów University of Technology in Poland, where he earned both his Bachelor of Engineering and Master of Science in Engineering in Chemical Technology. He graduated with the highest distinction (5.0 / A) for his master’s degree. His early interests centered on polymer synthesis, process modeling, and Monte Carlo simulations, which laid the groundwork for his computational research career.

🧪 Professional Endeavors

Currently a PhD student in Chemical Engineering, Mr. Rękas focuses on advanced computational techniques, particularly the integration of machine learning into chemical process modeling and optimization. A self-taught programmer, he independently develops customized simulation software and machine learning models that bridge the gap between chemical engineering and artificial intelligence. His research embodies an interdisciplinary approach, combining classical engineering, computer science, and applied mathematics.

🔬 Contributions and Research Focus

Mr. Rękas specializes in machine learning applications for chemical engineering, with a specific focus on physics-informed neural networks (PINNs) for solving complex partial differential equations. His models, named A1 and A2, have demonstrated the ability to predict concentration profiles in gradient liquid chromatography (GLC) under various elution conditions. These include nonlinear gradients, fast and slow gradient adjustments, and systems with mass transfer resistances. By embedding system dynamics into the loss functions of the neural networks, he achieved high prediction accuracy while reducing computation time by a factor of 272 compared to the OCFE method—highlighting his contributions to real-time process optimization.

🤝 Collaborations

Mr. Rękas collaborates with several prominent researchers. He works closely with Prof. Krzysztof Kaczmarski, an internationally recognized expert in chromatographic modeling and process scale-up, and with Dr. Eng. Marcin Chutkowski, a specialist in powder process modeling using the Discrete Element Method (DEM). Their joint research involves applying machine learning to enhance gradient liquid chromatography. Additionally, he collaborates with Prof. Jaromir Lechowicz on modeling polymerization and degradation phenomena, using Monte Carlo simulations and artificial intelligence for advanced material behavior predictions.

🌍 Impact and Influence

Although early in his research career, Mr. Rękas has already contributed to high-impact computational methods that address complex chemical systems. His innovative use of machine learning in chemical process engineering demonstrates potential for revolutionizing process design and optimization in industry and academia. His work significantly reduces simulation times and enhances accuracy, which is critical for scalable and sustainable chemical manufacturing.

📚 Academic Citations and Recognition

Mr. Rękas has published one peer-reviewed journal article and contributed a chapter to a scientific monograph (ISBN: 978-83-67881-52-4). While his citation count currently stands at 1, his work on PINNs and AI-driven chromatography modeling is rapidly gaining attention in specialized research communities.

🛠️ Technical Skills

He possesses extensive programming and modeling skills, with a focus on physics-informed neural networks, graph neural networks (GCNs, GATs), recurrent networks (RNNs, LSTMs, GRUs), XGBoost, and SVMs. His technical toolkit includes Monte Carlo simulations, process modeling frameworks, and custom algorithm development—demonstrating both depth and versatility in computational chemical engineering.

👨‍🏫 Teaching and Mentorship

Though not formally a lecturer, Mr. Rękas actively shares his expertise with peers and junior researchers in machine learning applications and scientific programming, contributing to knowledge exchange in research groups and seminars within his university.

🌟 Legacy and Future Contributions

With a strong foundation in both chemical engineering and artificial intelligence, Mr. Rękas is poised to become a leading figure in data-driven chemical process innovation. His future goals include expanding the use of neural networks in real-time industrial systems, enhancing predictive modeling in chromatography and polymer science, and contributing to the broader adoption of AI in engineering. His work exemplifies a new generation of scientists blending scientific rigor with computational agility.

📖Notable Publications

Application of physics-informed neural networks to predict concentration profiles in gradient liquid chromatography
Authors: Filip Rękas, Marcin Chutkowski, Krzysztof Kaczmarski
Journal: Journal of Chromatography A
Year: 2025

 

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