Ehsan Adibnia | Engineering | Best Academic Researcher Award

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.

Muhammad Umar Khan | Engineering | Best Researcher Award

Dr. Muhammad Umar Khan | Engineering | Best Researcher Award

Chairman at Qurtuba University of Science and Information Technology, Pakistan

Dr. Muhammad Umar Khan is a distinguished scholar and leader in civil engineering, serving as the Chairman of the Department of Civil Engineering and Technology at Qurtuba University of Science and Information Technology, Pakistan. With a career spanning over a decade, he has made significant contributions to the fields of structural engineering and advanced construction materials. Dr. Khan’s work in ultra-high-performance concrete (UHPC) has garnered international recognition, particularly for its innovative applications in harsh environmental conditions. His research reflects a blend of academic excellence and practical relevance, making him a key contributor to advancements in engineering technology.

Professional Profile

Education

Dr. Muhammad Umar Khan holds a Ph.D. in Civil Engineering (Structures) from King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, completed in April 2019. His academic journey reflects consistent excellence, as he earned distinctions in his Bachelor’s and Master’s degrees in Structural Engineering. He was awarded fully funded scholarships for his MS and Ph.D. studies due to exceptional academic performance. During his doctoral studies, Dr. Khan focused on the development and characterization of ultra-high-performance concrete (UHPC), pioneering its application using locally sourced materials in the Gulf region.

Professional Experience

Dr. Khan is the Chairman of the Department of Civil Engineering and Technology at Qurtuba University of Science and Information Technology, Pakistan. With over 10 years of university-level teaching and research experience, he has contributed significantly to the academic and professional development of his field. Dr. Khan has led multiple consultancy and industry projects, collaborating with prestigious organizations such as Saudi Aramco and the Royal Commission of Jubail. His work spans the design and analysis of reinforced concrete structures, finite element modeling, and the application of advanced materials in construction.

Research Interests

Dr. Khan’s research interests focus on advanced construction materials, particularly UHPC, high-performance hybrid materials, and nuclear radiation shielding concrete. He is also deeply involved in finite element analysis, structural damage modeling, and service life prediction of reinforced concrete structures. His pioneering work in UHPC has resulted in innovations applicable to futuristic construction challenges, including durability, resilience, and environmental adaptability.

Awards and Honors

Dr. Khan has earned numerous accolades throughout his career. He was a recipient of a prestigious fellowship at KFUPM and has been recognized for his groundbreaking research in UHPC, including three US patents under development. With over 280 citations, his research has gained international recognition. As a team leader, he has driven projects addressing industry challenges, showcasing his ability to blend academic rigor with practical application. His contributions continue to make an impact on structural engineering and advanced material research worldwide.

Conclusion

Dr. Muhammad Umar Khan is a strong contender for the Best Researcher Award. His pioneering work in advanced construction materials and substantial academic achievements make him highly suitable for the recognition. However, to solidify his position as a global leader, he could focus on enhancing his research’s societal impact, broader outreach, and professional engagements. Overall, his contributions signify exceptional innovation and dedication to advancing civil and structural engineering.

Publications Top Noted

📄 Effect of Fiber Content on the Performance of UHPC Slabs Under Impact Loading – Experimental and Analytical Investigation

  • Authors: Khan, M.U., Ahmad, S., Al-Osta, M.A., Algadhib, A.H., Al-Gahtani, H.J.
  • Year: 2023
  • Citations: 3

📄 Role of Casting and Curing Conditions on the Strength and Drying Shrinkage of Greener Concrete

  • Authors: Nasir, M., Adesina, A., Ibrahim, M., Maslehuddin, M., Alotaibi, K.S.
  • Year: 2022
  • Citations: 0

📄 Prediction of Strength of Plain and Blended Cement Concretes Cured Under Hot Weather Using Quadratic Regression and ANN Tools

  • Authors: Nasir, M., Gazder, U., Khan, M.U., Maslehuddin, M., Al-Amoudi, O.S.B.
  • Year: 2022
  • Citations: 5

📄 Properties of High-Density Ultra-High-Performance Concrete Containing Hematite Powder as a Partial Replacement of Sand

  • Authors: Ahmad, S., Khan, M.U., Al-Gahtani, H.J., Al-Dulaijan, S.U.
  • Year: 2022
  • Citations: 3

📄 Shielding Performance of Heavy-Weight Ultra-High-Performance Concrete Against Nuclear Radiation

  • Authors: Khan, M.U., Ahmad, S., Naqvi, A.A., Al-Gahtani, H.J.
  • Year: 2020
  • Citations: 54

📄 Chloride-Induced Corrosion of Steel in Concrete: An Overview on Chloride Diffusion and Prediction of Corrosion Initiation Time

  • Authors: Khan, M.U., Ahmad, S., Al-Gahtani, H.J.
  • Year: 2017
  • Citations: 116