Mr. Md Abu Huraiya | Sensor Networking | Young Scientist Award

Mr. Md Abu Huraiya | Sensor Networking | Young Scientist Award

Mr. Md Abu Huraiya, BRAC University, Bangladesh

Md Abu Huraiya is a passionate researcher in Electrical and Electronic Engineering, with expertise in photonic crystal fibers (PCF), surface plasmon resonance (SPR), microelectromechanical systems (MEMS), and surface acoustic wave (SAW) sensors. He earned his B.Sc. from Rajshahi University of Engineering & Technology (RUET) and currently serves as a Research Assistant at BRAC University. His research focuses on developing high-sensitivity optical and MEMS-based sensors, integrating Machine Learning (ML) for enhanced performance. Proficient in COMSOL Multiphysics, he has contributed to cutting-edge simulations for perovskite solar cells and biosensors. Additionally, he leads Academia Research Group, mentoring students in computational modeling and sensor development. With a strong academic foundation, hands-on expertise, and multiple research publications, Md Abu Huraiya aims to revolutionize sensor networks and photonics with advanced data analytics. His dedication to scientific innovation and education makes him a promising young researcher in the field.

🌐 Professional Profile

Google Scholar

🏆 Suitability for Young Scientist Award 

Md Abu Huraiya is an excellent candidate for the Young Scientist Award, given his groundbreaking contributions to sensor networks, photonic crystal fibers (PCF), and MEMS-based sensors. His research in SPR-based biosensors for medical diagnostics and perovskite solar cells for renewable energy highlights his ability to tackle real-world problems with cutting-edge technology. His expertise in COMSOL Multiphysics simulations has led to significant advancements in sensor design, with a focus on enhanced sensitivity and efficiency. Additionally, his leadership as the founder of Academia Research Group demonstrates his commitment to knowledge sharing and mentorship. His interdisciplinary approach, incorporating Machine Learning (ML) into sensor technology, sets him apart as an innovative researcher. With a solid track record of academic excellence, hands-on research experience, and impactful publications, he exemplifies the qualities of a young scientist driving technological advancements for a sustainable future.

🎓 Education 

Md Abu Huraiya holds a B.Sc. in Electrical and Electronic Engineering from Rajshahi University of Engineering & Technology (RUET), Bangladesh, graduating in May 2024. During his academic journey, he developed a strong foundation in photonic sensors, MEMS, and renewable energy technologies. His coursework covered optical fiber communication, signal processing, semiconductor devices, and nanotechnology. He has actively participated in research on SPR-based biosensors, PCF designs, and perovskite solar cells, gaining hands-on experience with simulation tools like COMSOL Multiphysics and MATLAB. His ability to bridge theoretical knowledge with practical applications has enabled him to contribute to high-impact research. His continuous learning mindset is evident in his certifications in radar and satellite communication and electric machines, enhancing his expertise in electromagnetic wave propagation and sensor technologies. His strong academic background and research acumen position him as a rising star in the field of Electrical and Electronic Engineering.

👨‍🔬 Research & Professional Experience 

Md Abu Huraiya is a Research Assistant at BRAC University (2024 – Present), working on perovskite solar cells, PCF-based SPR sensors, MEMS-based SAW sensors, and optical switches. His role involves designing high-sensitivity biosensors, optimizing perovskite solar cell efficiency, and leveraging Machine Learning (ML) for sensor performance improvement. He is skilled in COMSOL Multiphysics for sensor simulation and analysis.

Additionally, he founded Academia Research Group (2024 – Present), where he mentors students in COMSOL-based simulations for PCF-based SPR sensors and solar cells. He also runs a YouTube channel that provides educational content on computational modeling.

His research expertise spans nanophotonics, sensor development, and MEMS. With his innovative mindset, hands-on experience, and leadership, he is making impactful contributions to the field of sensor networks and optoelectronic devices.

🏅 Awards & Honors 

Md Abu Huraiya has received several awards and recognitions for his academic excellence and extracurricular achievements:

  1. 🏆 Thana-Level Examination Winner – Secured first prize in a highly competitive academic examination.
  2. 🏏 Cricket Championship Winner – Demonstrated teamwork and leadership as part of the winning short-pitch cricket team.
  3. 📜 Radar and Satellite Communication Certificate – Certified in advanced radar and satellite communication techniques by RUET.
  4. ⚡ Electric Machines Certification – Completed a specialized course on transformers, DC machines, and AC machines, enhancing his technical knowledge.

His ability to balance academic excellence with leadership in sports and research makes him a well-rounded candidate for prestigious awards.

🔬 Research Focus 

Md Abu Huraiya’s research primarily revolves around sensor networks, photonic crystal fibers (PCF), surface plasmon resonance (SPR), microelectromechanical systems (MEMS), photonics, and machine learning applications.

  1. PCF-based SPR Sensors – Developing high-sensitivity biosensors for medical diagnostics and environmental monitoring.
  2. MEMS-based SAW Sensors – Innovating acoustic wave sensors for precise measurements in healthcare and industrial applications.
  3. Perovskite Solar Cells – Enhancing the efficiency of lead-free perovskite solar cells using COMSOL-based simulations.
  4. Machine Learning (ML) in Sensor Optimization – Integrating AI-driven data analysis to improve sensor accuracy.
  5. Optical Switches – Designing advanced optical switching mechanisms for next-generation photonics.

His interdisciplinary approach to sensor technology, photonics, and AI-driven optimizations is shaping the future of smart and efficient sensor networks.

Publication Top Notes:

  • Title: New Approach for a Highly Sensitive V-Shaped SPR Biosensor for a Wide Range of Analyte RI Detection
    • Year: 2024
    • Citations: 5
  • Title: Ultra-sensitive Refractive Index Detection with Gold-Coated PCF-Based SPR Sensor
    • Year: 2024
    • Citations: 4
  • Title: Highly Optimized and Sensitive Bowtie Shape-Based SPR Biosensor for Different Analyte Detection
    • Year: 2025
    • Citations: 2
  • Title: A Circular Shaped SPR PCF Biosensor Based on External Sensing Mechanism
    • Year: 2024
    • Citations: 2
  • Title: Highly Sensitive X-Shaped SPR Biosensor for a Wide Range of Detection
    • Year: 2024
    • Citations: 2

 

 

Mr. Muhammad Riaz | Efficient Networking | Best Researcher Award

Mr. Muhammad Riaz | Efficient Networking | Best Researcher Award

Mr. Muhammad Riaz, KP TEVTA, Pakistan

Mr. Muhammad Riaz is a dedicated educator and researcher with expertise in electrical engineering, specializing in power systems and sustainable energy solutions. He holds a Master’s in Electrical Engineering from the University of Wah, where his thesis focused on optimizing power flow in renewable energy-integrated systems. With extensive experience in teaching, laboratory management, and fieldwork, Mr. Riaz has a proven track record of mentoring students and advancing practical engineering solutions. Passionate about smart grids, artificial intelligence, and control systems, he is committed to shaping the next generation of engineers while contributing to innovative energy solutions.

Professional Profile

Orcid

Suitability for Best Researcher Award

Mr. Muhammad Riaz’s dedication to advancing sustainable energy solutions and his impactful contributions to electrical engineering make him a strong candidate for the Best Researcher Award. His research on optimal power flow and renewable energy integration addresses critical challenges in modern power systems. His academic achievements, teaching excellence, and commitment to mentoring future engineers highlight his multifaceted contributions to the field. Mr. Riaz’s innovative approach and focus on practical solutions align perfectly with the award’s vision of recognizing transformative research.

Education

Mr. Muhammad Riaz completed his Master’s in Electrical Engineering at Wah Engineering College, University of Wah, in 2021, specializing in Power Engineering. His thesis, “Optimal Power Flow Solution of Modified IEEE 30 Bus System Integrated with Renewable Energy Sources,” highlights his focus on integrating renewable energy into power systems. He earned his Bachelor’s in Electrical Engineering from Bahria University Islamabad in 2018, where he designed a battery-free MPPT solar inverter as his final year project. His academic journey reflects a strong foundation in electrical and electronics engineering, complemented by minors in computer and communication engineering.

Experience

As a Lecturer at the Govt. Technical & Vocational Training Authority KP since 2021, Mr. Riaz has designed comprehensive lesson plans and delivered engaging lectures on motors, generators, PLCs, and solar PV systems. He also mentors students, fostering innovation and critical thinking. Previously, as a Lab Engineer at Wah Engineering College, he developed and implemented laboratory experiments, collaborated with faculty to optimize resources, and maintained equipment for effective teaching. His hands-on experience and dedication to teaching underscore his commitment to advancing electrical engineering education.

Awards and Honors

  • Fully Funded Scholarship: Secured a scholarship for BEE from the ICT R&D Fund, Government of Pakistan.
  • Rector’s Honor List: Recognized with Cum Laude distinction at Bahria University Islamabad.
  • Prime Minister Laptop Scheme: Awarded under the national initiative for academic excellence.
    These accolades reflect Mr. Riaz’s academic excellence and commitment to professional growth.

Research Focus

Mr. Muhammad Riaz’s research focuses on smart grids, optimal power flow, and the application of artificial intelligence in power systems. His work emphasizes sustainable energy solutions, including the integration of renewable energy into existing grids. His interests extend to control systems and optimization algorithms, aiming to enhance energy efficiency and reliability. His research aligns with global efforts to address energy challenges through innovative and intelligent systems.

Publication Top Notes

  • Article: An Optimal Power Flow Solution of a System Integrated with Renewable Sources Using a Hybrid Optimizer
    • Year: 2021
  • Article: An Optimization-Based Strategy for Solving Optimal Power Flow Problems in a Power System Integrated with Stochastic Solar and Wind Power Energy
    • Year: 2021
  • Conference Paper: An Innovative Model Based on FCRBM for Load Forecasting in the Smart Grid
    • Year: 2020
  • Conference Paper: Day Ahead Electric Load Forecasting by an Intelligent Hybrid Model Based on Deep Learning for Smart Grid
    • Year: 2020