Ehsan Adibnia | Engineering | Best Academic Researcher Award

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Dr. Ehsan Adibnia | Engineering | Best Academic Researcher Award

Dr. Ehsan Adibnia at University of Sistan and Baluchestan, Iran

Dr. Ehsan Adibnia 🎓 is a dedicated academic researcher in electrical engineering ⚡, specializing in cutting-edge fields such as artificial intelligence 🤖, machine learning 📊, deep learning 🧠, nanophotonics 💡, optics 🔬, and plasmonics ✨. He is proficient in Python 🐍, MATLAB 🧮, and Visual Basic, and utilizes simulation tools like Lumerical 📈, COMSOL 🧪, and RSoft 🔧 to drive innovative research. Fluent in English 🇬🇧 and Persian 🇮🇷, Dr. Adibnia contributes to academic conferences and peer-reviewed journals 📚. He is currently pursuing his Ph.D. and actively engaged in interdisciplinary scientific exploration 🌐.

Professional Profile:

Orcid

Scopus

Google Scholar

🔹 Education & Experience 

🎓 Ph.D. in Electrical Engineering – University of Sistan and Baluchestan, Zahedan, Iran (Expected 2025)
🎓 B.S. in Electrical Engineering – University of Sistan and Baluchestan, Zahedan, Iran (2014)
🧑‍💼 Executive Committee Member – 27th Iranian Conference on Optics and Photonics & 13th Conference on Photonic Engineering and Technology
🖋️ Assistant Editor – International Journal (Name not specified)
🔍 Researcher – Actively engaged in interdisciplinary AI & photonics research projects

🔹 Professional Development 

Dr. Ehsan Adibnia continually enhances his professional growth through active participation in conferences 🧑‍🏫, committee leadership 🗂️, and editorial work 📑. He develops algorithms and conducts simulations using advanced tools such as Lumerical 🔬, COMSOL 🧪, and RSoft 💻. His expertise in AI and photonics drives innovative research and collaboration 🌍. He also hones his programming skills in MATLAB 🧮, Python 🐍, and VBA 🧠, ensuring precision in modeling and data analysis. His hands-on knowledge in PLC systems 🤖 and industrial automation makes him versatile across both academic and applied research settings 🏭.

🔹 Research Focus 

Dr. Adibnia’s research focuses on the fusion of artificial intelligence 🤖 and photonics 💡. His work explores machine learning 📊, deep learning 🧠, nanophotonics 🔬, plasmonics ✨, optical switching 🔁, and slow light 🐢 technologies. He is particularly interested in leveraging these technologies in biosensors 🧫, metamaterials 🔷, and quantum optics ⚛️. Through simulation and algorithm development, he aims to optimize performance in optoelectronic and photonic systems 🔍. His interdisciplinary research bridges electrical engineering with physics and AI, creating advanced systems for diagnostics, sensing, and smart environments 🌐.

🔹 Awards & Honors 

🏅 Executive Committee Role – 27th Iranian Conference on Optics and Photonics
🏅 Executive Committee Role – 13th Iranian Conference on Photonic Engineering and Technology
📜 Assistant Editor – International scientific journal (name not specified)
🧠 Scopus-indexed Researcher – Scopus ID: 58485414000

Publication Top Notes

🔹 High-performance and compact photonic crystal channel drop filter using P-shaped ring resonator

  • Journal: Results in Optics

  • Date: Dec 2025

  • DOI: 10.1016/j.rio.2025.100817

  • Summary: Proposes a novel P-shaped ring resonator design for channel drop filters in photonic crystal structures. Focuses on achieving high performance in terms of compactness and spectral selectivity for integrated optical circuits.

🔹 Optimizing Few-Mode Erbium-Doped Fiber Amplifiers for high-capacity optical networks using a multi-objective optimization algorithm

  • Journal: Optical Fiber Technology

  • Date: Sep 2025

  • DOI: 10.1016/j.yofte.2025.104186

  • Summary: Introduces a multi-objective optimization approach for designing few-mode EDFAs, targeting performance improvements in next-gen high-capacity optical networks.

🔹 Inverse design of octagonal plasmonic structure for switching using deep learning

  • Journal: Results in Physics

  • Date: Apr 2025

  • DOI: 10.1016/j.rinp.2025.108197

  • Summary: Utilizes deep learning for the inverse design of an octagonal plasmonic structure used in optical switching, demonstrating enhanced precision and compact design capability.

🔹 Chirped apodized fiber Bragg gratings inverse design via deep learning

  • Journal: Optics & Laser Technology

  • Date: 2025

  • DOI: 10.1016/J.OPTLASTEC.2024.111766

  • WOS UID: WOS:001311493000001

  • Summary: Applies deep learning to the inverse design of chirped apodized fiber Bragg gratings, optimizing the spectral characteristics for filtering and sensing applications.

🔹 Inverse Design of FBG-Based Optical Filters Using Deep Learning: A Hybrid CNN-MLP Approach

  • Journal: Journal of Lightwave Technology

  • Date: 2025

  • DOI: 10.1109/JLT.2025.3534275

  • Summary: Proposes a hybrid CNN-MLP architecture to design fiber Bragg grating (FBG) optical filters, improving accuracy and speed in the inverse design process using deep learning techniques.

Conclusion

Dr. Adibnia is still in the process of completing his Ph.D., his broad technical expertise, multidisciplinary research focus, early academic leadership roles, and active participation in both national and international platforms make him a highly promising candidate for the Best Academic Researcher Award in the early-career researcher or emerging researcher category.

Shengnan Zhang | Engineering | Best Researcher Award

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Dr. Shengnan Zhang | Engineering | Best Researcher Award

None  at School of Mechatronic Engineering and Automation, Shanghai University

Short Bio

  • shengnan zhang is a Ph.D. researcher at Shanghai University specializing in electromagnetic flowmeters, signal processing, and mathematical modeling for industrial processes. With experience in engineering and automation, she integrates theoretical and applied research to enhance industrial measurement accuracy and efficiency.

Professional Profile

Educational Background

  • shengnan zhang is currently pursuing a Ph.D. in the School of Mechatronic Engineering and Automation at Shanghai University (2021–2024). She earned her master’s degree in Control Science and Engineering (Automation) from Inner Mongolia University of Science and Technology in 2020.

Professional Experience

  • shengnan zhang has gained diverse experience in both industry and academia. She worked as a junior engineer in the Mechanical and Electrical Department at State Grid Xinyuan Chifeng Company, Inner Mongolia (2020–2021). She later transitioned into roles as a Hardware R&D Engineer at JiDan Biotechnology Co., Ltd. and a High School Mathematics Teacher at Nanjing Yunjushi Education Co., Ltd. in 2021.

Research Interests

    • Her research focuses on electromagnetic flowmeters, signal processing, and mathematical modeling of complex industrial processes. She is particularly interested in developing advanced computational techniques for industrial automation and measurement systems.

Author Metrics

  • Currently, shengnan zhang is actively engaged in research and has contributed to scholarly publications in her field. Her work includes studies on signal processing applications in industrial automation and measurement technologies.

Publication Top Noted

  • Study on the Match-Filtering Ability of the Electromagnetic Flowmeter Signals Based on the Generalized Dual-Frequency Walsh Transform
    Flow Measurement and Instrumentation, March 2025
    DOI: 10.1016/j.flowmeasinst.2024.102767
  • Generalized Walsh Transform Sequency-Domain-Based Match Filtering for Electromagnetic Flowmeter Signal Measurement
    IEEE Sensors Journal, April 2024
    DOI: 10.1109/JSEN.2024.3366238
  • A Sequency Match Filtering Algorithm Based on the Generalized Walsh Transform for Processing Rectangular Wave Signals
    Review of Scientific Instruments, February 2024
    DOI: 10.1063/5.0175079
  • Study on Match Filtering Based on Sequency Spectrum Characteristics of the Walsh Transform for Electromagnetic Flowmeter Signal Measurement
    Measurement, February 2024
    DOI: 10.1016/j.measurement.2023.114021

Conclusion

  • Dr. shengnan zhang is a highly qualified researcher with notable contributions to signal processing and industrial measurement systems. Her innovative approaches using Generalized Walsh Transform have the potential to improve electromagnetic flowmeter accuracy significantly. With further collaboration, higher citation impact, and real-world application of her research, she would be an excellent candidate for the Best Researcher Award.

Arjun Sil | Civil | Best Researcher Award

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Assoc. Prof. Dr. Arjun Sil | Civil | Best Researcher Award 

Associate professor, at NIT Silchar Assam, India.

Dr. Arjun Sil is an Associate Professor in the Department of Civil Engineering at the National Institute of Technology (NIT), Silchar, Assam, India. With a passion for teaching and research, he specializes in earthquake-resistant design, seismic hazard analysis, structural health monitoring, and applied elasticity. Dr. Sil has over 15 years of experience in academia and research, contributing significantly to civil engineering through numerous publications and collaborative projects. His work aims to address critical challenges in infrastructure resilience, environmental hazards, and innovative retrofitting techniques. Beyond academia, he is an advocate for interdisciplinary approaches to solving real-world problems.

Professional Profile

Scopus

Google Scholar 

ORCID

Education

🎓 Dr. Sil’s academic journey is a testament to his dedication to civil engineering:

  • Ph.D. in Civil Engineering (2014) from the prestigious Indian Institute of Science (IISc), Bangalore, India.
  • M.Tech in Earthquake Engineering (2010) from National Institute of Technology (NIT), Silchar, Assam, India.
  • B.Tech in Civil Engineering (2002) from North Eastern Regional Institute of Science and Technology (NERIST), Arunachal Pradesh, India.

His academic credentials reflect his strong foundation and specialization in earthquake engineering and geotechnical studies.

Experience

💼 Dr. Sil brings over 15 years of professional experience:

  • Associate Professor (since July 2022) at NIT Silchar, focusing on advanced civil engineering research and teaching.
  • Assistant Professor (2012–2022) at NIT Silchar, contributing to undergraduate and postgraduate education.
  • Research Fellow (2008–2012), where he conducted groundbreaking studies in seismic vulnerability.
  • Engineering Officer (Civil) (2003–2008) in the Government of Tripura, overseeing infrastructure development and maintenance projects.

Research Interests

🔍 Dr. Sil’s research spans a diverse range of critical topics in civil engineering:

  • Earthquake-resistant design and geotechnical earthquake engineering.
  • Seismic hazard analysis, seismic microzonation, and site response studies.
  • Structural health monitoring, condition assessment, and retrofitting techniques.
  • Application of GIS, remote sensing, and probabilistic modeling in civil engineering.
  • Air pollution modeling, landslide hazard evaluation, and corrosion studies.

Awards

🏆 Dr. Sil’s contributions have earned him numerous accolades:

  • Recognized for his outstanding research in seismic vulnerability and hazard analysis.
  • Awards for excellence in teaching and mentoring graduate students.
  • Honored for his work on integrated GIS-based hazard mapping and applied engineering studies.

Publications

📚 Dr. Sil has published extensively in high-impact journals, contributing significantly to civil engineering research:

2024

  1. Tsunami Vulnerability Assessment Using GIS and AHP Technique”
    • Journal: Natural Hazards Review, ASCE
    • Focus: Assessing tsunami vulnerability using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP).
    • Scope: Framework for identifying high-risk zones and mitigation strategies.
    • Significance: Useful for coastal planning and disaster risk reduction.
  2. “Seismic Hazards in Bhubaneswar City, India”
    • Journal: Indian Geotechnical Journal, Springer
    • Focus: Evaluating seismic risks specific to Bhubaneswar using geotechnical and seismological data.
    • Scope: Recommendations for urban planning and infrastructure resilience.
    • Significance: First detailed seismic hazard study for this city.

2023

  1. “Application of ANN for Time-Variant Structural Reliability”
    • Journal: Practice Periodical on Structural Design and Construction, ASCE
    • Focus: Leveraging Artificial Neural Networks (ANN) to model and predict structural reliability over time.
    • Scope: Applied to structures facing varying environmental and load conditions.
    • Significance: Advances computational methods in structural engineering.
  2. “Service Life Estimation of RC Bridge Structures”
    • Journal: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems
    • Focus: Estimating the remaining service life of reinforced concrete (RC) bridge structures under deterioration.
    • Scope: Models incorporating uncertainties like corrosion and traffic loads.
    • Significance: Critical for prioritizing bridge maintenance and rehabilitation.
  3. “Comprehensive Seismic Hazard Assessment for Guwahati City”
    • Journal: Natural Hazards Research, Elsevier
    • Focus: Detailed seismic hazard mapping for Guwahati city, North East India.
    • Scope: Includes microzonation and implications for disaster preparedness.
    • Significance: A critical contribution to urban safety in a high-risk zone.
  4. “Report on the 2018 Indonesian Tsunami Causes”
    • Journal: Natural Hazards Research, Elsevier
    • Focus: Investigating geological and environmental factors leading to the 2018 Indonesian tsunami.
    • Scope: Post-event analysis highlighting lessons for future disaster management.
    • Significance: Provides insights for global tsunami risk mitigation.
  5. “Seismic Hazard Analysis of North East India”
    • Journal: International Journal of Reliability and Safety, Inderscience
    • Focus: Comprehensive analysis of seismic hazards in the North East region of India.
    • Scope: Includes probabilistic seismic hazard assessment (PSHA) and vulnerability indices.
    • Significance: Enhances understanding of the region’s seismic risks for infrastructure planning.

Conclusion

Dr. Arjun Sil is a highly accomplished researcher with a prolific publication record and deep expertise in civil and geotechnical engineering. His contributions to earthquake-resistant design, seismic hazard analysis, and structural health monitoring are significant and impactful. While he could benefit from expanded global collaborations and broader public engagement, his achievements make him a strong contender for the Research for Best Researcher Award. His work addresses both academic excellence and practical societal challenges, aligning well with the award’s objectives.