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:

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🔹 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.

Yun Zhao | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Yun Zhao | Engineering | Best Researcher Award

Yun Zhao at Northwest Normal University, China

Dr. Yun Zhao 🎓 is an Associate Professor at the College of Physics and Electronic Engineering, Northwest Normal University 🏫, since 2020. He earned his Ph.D. in Materials Science and Engineering 🧪 from the Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences 🇨🇳, in 2020. Shortly after, he joined the Ningbo Institute of Materials Technology and Engineering 🔬 as a postdoctoral researcher. His work focuses on thin film photodetectors 📸 and semiconductor devices 💡. Dr. Zhao is passionate about next-gen optoelectronics and is actively contributing to innovation in functional materials and device engineering 🚀.

Professional Profile:

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🎓 Education & Experience 

  • 📚 Ph.D. in Materials Science and Engineering, Lanzhou Institute of Chemical Physics, CAS – 2020

  • 🧑‍🏫 Postdoctoral Researcher, Ningbo Institute of Materials Technology and Engineering, CAS

  • 👨‍🏫 Associate Professor, College of Physics and Electronic Engineering, Northwest Normal University – Since 2020

📈 Professional Development 

Dr. Yun Zhao continuously engages in academic and research development through national and institutional collaborations 🤝. His postdoctoral work at the prestigious Ningbo Institute of CAS sharpened his experimental techniques and deepened his expertise in advanced semiconductors ⚙️. As an associate professor, he mentors young researchers 👨‍🔬 and collaborates on interdisciplinary projects across optics, electronics, and nanotechnology 🔍. He regularly attends academic conferences, publishes in reputed journals 📄, and reviews scientific manuscripts. His dedication to professional growth ensures he stays at the forefront of innovation in functional materials and optoelectronic devices 🌐.

🔬 Research Focus 

Dr. Yun Zhao’s research primarily revolves around thin film photodetectors 📸 and semiconductor devices ⚡. His focus lies in designing and fabricating new materials with enhanced sensitivity, stability, and performance for light-sensing technologies 🌞. He explores emerging materials such as perovskites and nanostructures 🌱 for integration into flexible and wearable electronics 🧤. His work bridges the gap between material science and applied electronics, aiming to revolutionize future optoelectronic systems 🔋. The end goal of his research is to contribute to high-performance, low-cost, and energy-efficient devices for real-world applications 🚗📱.

🏆 Awards and Honors 

  • 🎖️ Ph.D. fellowship from the Chinese Academy of Sciences

  • 🏅 Postdoctoral appointment at Ningbo Institute of Materials Technology and Engineering (CAS)

  • 🏆 Recognized for outstanding research contributions in thin film photodetectors

  • 📜 Multiple peer-reviewed publications in reputed international journals

Publication Top Notes

1. Understanding Proton Radiation-Induced Degradation Mechanisms in Cu₂ZnSn(S,Se)₄ Kesterite Thin-Film Solar Cells

Journal: Solar Energy
Date: May 2025
DOI: 10.1016/j.solener.2025.113450
Summary:
This study investigates how proton radiation affects the stability and performance of Cu₂ZnSn(S,Se)₄ (CZTSSe) thin-film solar cells. Proton radiation is relevant for space applications where solar cells are exposed to high-energy particles. The paper likely explores:

  • Changes in carrier lifetimes and defect states post-irradiation.

  • Structural or compositional changes in the absorber layer.

  • Strategies to mitigate degradation for improved radiation tolerance.

2. Multifunctional Artificial Electric Synapse of MoSe₂-Based Memristor toward Neuromorphic Application

Journal: The Journal of Physical Chemistry Letters
Date: February 6, 2025
DOI: 10.1021/acs.jpclett.4c03353
Summary:
This article presents a MoSe₂-based memristor designed to emulate biological synapses. The work focuses on neuromorphic computing, highlighting:

  • Synaptic plasticity behaviors (e.g., potentiation/depression).

  • Multifunctionality (possibly electrical + optical control).

  • Performance metrics like switching speed, retention, and endurance.

3. Exploring the Promoting Effect of Lanthanum Passivation on the Photovoltaic Performance of CZTSSe Solar Cells

Journal: The Journal of Chemical Physics
Date: December 21, 2024
DOI: 10.1063/5.0244645
Summary:
This paper studies how lanthanum (La) passivation enhances CZTSSe solar cell efficiency. Key aspects likely include:

  • Reduction in defect densities at grain boundaries or interfaces.

  • Improvements in open-circuit voltage and fill factor.

  • Insights into La’s role in modifying electronic structure or surface chemistry.

4. Electrical-Light Coordinately Modulated Synaptic Memristor Based on Ti₃C₂ MXene for Near-Infrared Artificial Vision Applications

Journal: The Journal of Physical Chemistry Letters
Date: August 29, 2024
DOI: 10.1021/acs.jpclett.4c02281
Summary:
This research showcases a Ti₃C₂ MXene-based memristor that responds to both electrical and light inputs, mimicking the retina for near-infrared vision. Highlights include:

  • Dual-mode modulation (electrical and optical).

  • Application in neuromorphic visual systems.

  • Spectral response analysis and synaptic behavior simulation.

5. Multicolor Fully Light-Modulated Artificial Synapse Based on P-MoSe₂/PxOy Heterostructured Memristor

Journal: The Journal of Physical Chemistry Letters
Date: August 29, 2024
DOI: 10.1021/acs.jpclett.4c01980
Summary:
This study introduces a heterostructured memristor combining P-doped MoSe₂ and PxOy, enabling light-tuned synaptic responses. Likely contributions:

  • Multicolor light sensitivity for multi-channel processing.

  • Photonic modulation of conductance states.

  • Integration prospects for optical neuromorphic systems.

Conclusion

Dr. Yun Zhao is highly suitable for the Best Researcher Award, particularly in categories related to emerging materials, device physics, or engineering sciences. His rapid academic progression, focused and relevant research in photodetectors and semiconductors, and training at top-tier institutions within the Chinese Academy of Sciences establish him as a promising and impactful researcher. Recognition through such an award would be both meritorious and motivating for his continued contributions to the field.