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.

Ali Darvish Falehi | Engineering | Excellence in Researcher Award

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Assoc. Prof. Dr. Ali Darvish Falehi | Engineering | Excellence in Researcher Award

Dr. Darvish Falehi at Islamic Azad University, Iran

Ali Darvish Falehi is a distinguished academic and professional in the field of Electrical Power Engineering. With a Ph.D. and Post-Ph.D. from Shahid Beheshti University, he ranks among the world’s top 2% scientists as listed by Stanford University in 2020. He is currently an Assistant Professor at Iran Islamic Azad University, a technical expert at Iran North Drilling Company, and the Chairman of the R&D Board at HICOBI Company. He has delivered keynote speeches at several international conferences and holds numerous patents. His contributions extend to supervising over 50 theses and reviewing for prestigious journals. 🌟🔬📚

Professional Profile:

Google Scholar

Education and Experience:

  • Post-Ph.D. & Ph.D. in Electrical Power Engineering, Shahid Beheshti University (First Class Honors) 🎓

  • Ranked among the world’s top 2% scientists by Stanford University in 2020 🌍

  • Chairman of R&D Board at HICOBI Company 🏢

  • Assistant Professor at Iran Islamic Azad University 👨‍🏫

  • Technical Expert at Iran North Drilling Company ⚙️

  • Main Speaker at national and international conferences 🎤

  • Reviewer for prestigious journals (IEEE, Elsevier, Springer) 📖

  • Supervisor & Adviser for 50+ M.Sc. and Ph.D. theses 📝

  • TOEFL-PBT score: 630 (Writing Score: 6) 🏆

  • Patents and medals at invention festivals in Iran, South Korea, and Romania 🏅

Professional Development: 

Ali Darvish Falehi has continuously developed his professional expertise by participating in global conferences and providing thought leadership as a main speaker and reviewer for high-impact journals such as IEEE and Elsevier. His dedication to research has led him to supervise over 50 graduate and doctoral theses, contributing to the academic growth of the next generation of engineers. He is also deeply involved in the industrial sector, where he serves as a technical expert for Iran North Drilling Company and leads the R&D board at HICOBI Company, driving innovation and technology forward. His work bridges academia and industry, enhancing both fields. 🔧🌐📊

Research Focus:

Ali Darvish Falehi’s research is centered around Electrical Power Engineering, with particular attention to energy systems, power distribution, and renewable energy solutions. His work aims to optimize power engineering technologies, focusing on improving energy efficiency and sustainability. He is known for his contributions to the development of advanced electrical systems and has been actively involved in creating patented innovations. His expertise in power engineering is complemented by his role as a technical expert, where he advises on industrial applications of electrical power systems. His research seeks to solve complex energy challenges, aligning with global sustainability goals. ⚡🌱🔋

Awards and Honors:

  • Ranked among the world’s top 2% scientists by Stanford University (2020) 🌍

  • Chairman of the R&D Board at HICOBI Company 🏢

  • Main Speaker at several international conferences 🎤

  • Reviewer for leading ISI journals like IEEE, Elsevier, Springer 📚

  • Supervisor & Adviser for 50+ M.Sc. and Ph.D. theses 📝

  • TOEFL-PBT Score: 630 🏆

  • Patents and medals from invention festivals in Iran, South Korea, and Romania 🏅

Publication Top Notes

  1. “An innovative optimal RPO-FOSMC based on multi-objective grasshopper optimization algorithm for DFIG-based wind turbine to augment MPPT and FRT capabilities” (2020)

    • Authors: A.D. Falehi

    • Journal: Chaos, Solitons & Fractals

    • Summary: This paper proposes an innovative control strategy using a multi-objective Grasshopper Optimization Algorithm (GOA) to enhance the MPPT and Fault Ride Through (FRT) capabilities of DFIG-based wind turbines. The use of Fractional-Order Sliding Mode Control (FOSMC) is central to this work.

  2. “Promoted supercapacitor control scheme based on robust fractional-order super-twisting sliding mode control for dynamic voltage restorer to enhance FRT and PQ capabilities of DFIG-based wind turbines” (2021)

    • Authors: A.D. Falehi, H. Torkaman

    • Journal: Journal of Energy Storage

    • Summary: This paper focuses on enhancing the FRT and Power Quality (PQ) capabilities of DFIG-based wind turbines. The authors propose a robust fractional-order control scheme for supercapacitors integrated with a Dynamic Voltage Restorer (DVR).

  3. “LVRT/HVRT capability enhancement of DFIG wind turbine using optimal design and control of novel PIλDμ-AMLI based DVR” (2018)

    • Authors: A.D. Falehi, M. Rafiee

    • Journal: Sustainable Energy, Grids and Networks

    • Summary: This work aims to enhance the Low Voltage Ride Through (LVRT) and High Voltage Ride Through (HVRT) capabilities of DFIG wind turbines by optimizing the design and control of a novel DVR based on a PIλDμ-AMLI (Proportional-Integral-Derivative) controller.

  4. “Enhancement of DFIG-wind turbine’s LVRT capability using novel DVR based odd-nary cascaded asymmetric multi-level inverter” (2017)

    • Authors: A.D. Falehi, M. Rafiee

    • Journal: Engineering Science and Technology, an International Journal

    • Summary: This paper explores improving the LVRT capability of DFIG wind turbines by integrating a novel Dynamic Voltage Restorer (DVR) system with an odd-nary cascaded asymmetric multi-level inverter.

  5. “Neoteric HANFISC–SSSC based on MOPSO technique aimed at oscillation suppression of interconnected multi-source power systems” (2016)

    • Authors: A.D. Falehi, A. Mosallanejad

    • Journal: IET Generation, Transmission & Distribution

    • Summary: This paper addresses the oscillation suppression in interconnected multi-source power systems using a Hybrid Active Networked Flexible Integrated Supply Chain (HANFISC)-Static Synchronous Series Compensator (SSSC) controlled by the Multi-Objective Particle Swarm Optimization (MOPSO) technique.

Conclusion:

Ali Darvish Falehi is undoubtedly a deserving candidate for the Excellence in Researcher Award. His combination of academic excellence, significant contributions to electrical power engineering, leadership in both academia and industry, and his global recognition positions him as a standout figure in his field. His ability to balance research with innovation, along with his dedication to mentoring future researchers, makes him an exemplary choice for this prestigious award.

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:

Orcid

Scopus

🎓 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.

Shirko Faroughi | Engineering | Best Researcher Award

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Prof. Shirko Faroughi | Engineering | Best Researcher Award

Academic at Urmia University of Technoloy, Iran

Dr. Shirko Faroughi, an esteemed Professor of Mechanical Engineering at Urmia University of Technology, Iran, specializes in Computational Mechanics, Isogeometric Analysis, and Finite Element Methods. With a Ph.D. from Iran University of Science and Technology, he has held research positions at KTH University (Sweden), Swansea University (UK), and Bauhaus University Weimar (Germany). His work spans fracture mechanics, machine learning, and 3D printing simulations. As a CICOPS Scholar at the University of Pavia, Italy, Dr. Faroughi actively collaborates on international research projects, contributing significantly to advanced numerical methods. 📚🌍

Professional Profile:

Scopus

Google Scholar

Education & Experience 🎓📜

  • Ph.D. in Mechanical Engineering (2010) – Iran University of Science and Technology 🏛️

  • M.S. in Mechanical Engineering (2005) – Iran University of Science and Technology 🏗️

  • B.S. in Mechanical Engineering (2003) – Tabriz University 🚗

🔹 Academic Roles

  • Professor (2020 – Present) – Urmia University of Technology 👨‍🏫

  • Associate Professor (2015 – 2020) – Urmia University of Technology 🔬

  • Assistant Professor (2011 – 2015) – Urmia University of Technology 📖

  • Visiting Researcher (2008 – 2009) – KTH University, Sweden 🇸🇪

🔹 Administrative & International Positions

  • Dean of Mechanical Engineering Department (2022 – Present) 🏢

  • CICOPS Scholar – University of Pavia, Italy (2022) 🇮🇹

  • Research Collaborator – Swansea University, UK (2015 – Present) 🇬🇧

  • Research Collaborator – New Mexico State University, USA (2016 – Present) 🇺🇸

  • Research Collaborator – Bauhaus University Weimar, Germany (2017 – Present) 🇩🇪

Professional Development 🌍📚

Dr. Shirko Faroughi has made remarkable contributions to mechanical engineering through computational mechanics, finite element analysis, and machine learning. His research advances superconvergent mass and stiffness matrices, isogeometric methods, phase-field methods, and energy harvesting. He also integrates AI-driven techniques to enhance engineering simulations. His collaborations span Europe and the U.S., working with top researchers on thin structures, 3D printing, and structural dynamics. As a department dean and international collaborator, he plays a pivotal role in engineering education and research innovations, fostering global academic partnerships. 🌎💡

Research Focus 🔍🧠

Dr. Faroughi’s research primarily revolves around Computational Mechanics and Advanced Numerical Methods, integrating Artificial Intelligence and Machine Learning for engineering applications. His work focuses on:

  • Superconvergent mass and stiffness matrices 📐🔬

  • Isogeometric and finite element methods 🏗️📊

  • Fracture mechanics and phase-field modeling 🏚️💥

  • Tensegrity structures and energy harvesting ⚡🔩

  • Machine learning and transfer learning in mechanical simulations 🤖📈

  • 3D printing simulations and advanced material modeling 🖨️🧩

His research bridges traditional mechanical engineering with AI and computational techniques, pushing engineering boundaries through innovative numerical simulations. 🚀🔢

Awards & Honors 🏆🎖️

  • CICOPS Scholarship – University of Pavia, Italy (2022) 🇮🇹

  • Visiting Researcher – KTH University, Sweden (2008-2009) 🇸🇪

  • Research Collaborator – Swansea University, UK (2015-Present) 🇬🇧

  • Research Collaborator – Bauhaus University Weimar, Germany (2017-Present) 🇩🇪

  • Research Collaborator – New Mexico State University, USA (2016-Present) 🇺🇸

  • Dean of Mechanical Engineering Department – Urmia University of Technology (2022-Present) 🏛️

  • Multiple Grants for Advanced Computational Mechanics Research 🎓🔍

Publication Top Notes

  1. Wave Propagation in 2D Functionally Graded Porous Rotating Nano-Beams

    • Authors: S. Faroughi, A. Rahmani, M.I. Friswell

    • Published in Applied Mathematical Modelling (2020)

    • Citations: 71

    • Focus: Investigates wave propagation in porous nano-beams using a general nonlocal higher-order beam theory, considering functionally graded materials and rotation effects.

  2. Vibration of 2D Imperfect Functionally Graded Porous Rotating Nanobeams

    • Authors: A. Rahmani, S. Faroughi, M.I. Friswell

    • Published in Mechanical Systems and Signal Processing (2020)

    • Citations: 54

    • Focus: Examines vibration behavior of imperfect functionally graded porous rotating nanobeams based on a generalized nonlocal theory.

  3. Non-linear Dynamic Analysis of Tensegrity Structures Using a Co-Rotational Method

    • Authors: S. Faroughi, H.H. Khodaparast, M.I. Friswell

    • Published in International Journal of Non-Linear Mechanics (2015)

    • Citations: 47

    • Focus: Develops a co-rotational method for analyzing nonlinear dynamics of tensegrity structures.

  4. Physics-Informed Neural Networks for Solute Transport in Heterogeneous Porous Media

    • Authors: S.A. Faroughi, R. Soltanmohammadi, P. Datta, S.K. Mahjour, S. Faroughi

    • Published in Mathematics (2023)

    • Citations: 40

    • Focus: Uses physics-informed neural networks (PINNs) with periodic activation functions to model solute transport in heterogeneous porous media.

  5. Nonlinear Transient Vibration of Viscoelastic Plates Using a NURBS-Based Isogeometric HSDT Approach

    • Authors: E. Shafei, S. Faroughi, T. Rabczuk

    • Published in Computers & Mathematics with Applications (2021)

    • Citations: 30

    • Focus: Investigates nonlinear transient vibrations of viscoelastic plates using an isogeometric high-order shear deformation theory (HSDT) approach.

Shakil Ahmed | Engineering | Best Researcher Award

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Prof. Shakil Ahmed | Engineering | Best Researcher Award

Assistant Processor, Term at Iowa State University, United States

Shakil Ahmed is an Assistant Teaching Professor in Computer Engineering at Iowa State University (ISU), specializing in AI/ML, cybersecurity, IoT, cloud computing, and advanced networking. With a Ph.D. in Computer Engineering from ISU (2023) and over 2,000 citations across 35+ publications, he leads cutting-edge research on AI-driven solutions, digital twins, and quantum networks. As a principal investigator (PI), he mentors undergraduate, MS, and Ph.D. students while actively securing external grants. His expertise spans reinforcement learning, large language models, explainable AI, and meta-learning, contributing to pioneering advancements in next-gen networking and intelligent systems. 🚀🔍

Professional Profile

Education & Experience 📚👨‍🏫

  • Ph.D. in Computer Engineering – Iowa State University (2023) 🎓
  • M.S. in Electrical Engineering – Utah State University (2019) ⚡
  • B.S. in Electrical and Electronic Engineering – Khulna University of Engineering & Technology, Bangladesh (2014) 🏅
  • Assistant Teaching Professor – Iowa State University (2024–Present) 🎓
  • Researcher & PI – Leading projects on AI, 6G, cybersecurity, IoT, and digital twins 🔬
  • Advisor & Mentor – Supervising undergraduate, MS, and Ph.D. students in advanced networking and AI 🧑‍🎓

Professional Development 📈🧠

Shakil Ahmed actively contributes to AI-driven networking, secure systems, and IoT advancements. He plays a vital role in research funding, securing grants exceeding millions of dollars. As a guest editor at MDPI and reviewer for 150+ articles, he ensures high research standards. His teaching experience spans multiple STEM courses, where he integrates hands-on learning tools like Zybooks and Canvas. He has delivered invited talks on next-gen wireless technologies and collaborates with multidisciplinary teams to shape the future of AI, cloud computing, and quantum networking. His work has significantly impacted academia, research, and industry. 🚀🔬📡

Research Focus 🏆🔍

Shakil Ahmed’s research is at the intersection of AI, networking, and cybersecurity, with a focus on:

  • AI/ML & Deep Learning – Reinforcement Learning (RL), Large Language Models (LLM), Explainable AI (XAI) 🤖
  • Cybersecurity & Quantum Networking – Secure network protocols, quantum neural networks (QNN) 🔒
  • IoT & Cloud Computing – System design for connected environments, mobile edge computing ☁️
  • Digital Twin & 6G+ Networks – AI-driven tactile internet, smart infrastructure, and futuristic networking 🌍📡
    His work integrates cutting-edge AI techniques, optimization frameworks, and network simulations to solve real-world challenges.

Awards & Honors 🏅🎖️

  • Professional Development Fund – Iowa State University ($10,000) 💰
  • Presidential Fellowship – Utah State University ($90,000) 🏆
  • Best Paper Award – IEEE International Conference on Informatics, Electronics, and Vision (2016) 🥇
  • Graduate & Professional Student Senate Research Award – ISU ($700) 📜
  • ECpE Department Support Grant – ISU ($600) 🎓
  • Professional Advancement Grant (PAG) – ISU ($400) 🎖️
  • Military Communications Conference Student Travel Grants – 2021 & 2022 ($1,000) ✈️
  • Graduate & Professional Student Council Grant – ISU ($750) 🏅
  • ECE Department Support Grant – Utah State University ($1,000) 🏆

Publication Top Notes

  1. 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions

    • Authors: Mostafa Zaman Chowdhury, Md. Shahjalal, Shakil Ahmed, Yeong Min Jang
    • Journal: IEEE Open Journal of the Communications Society
    • Year: 2020
    • Citation: Chowdhury, M. Z., Shahjalal, M., Ahmed, S., & Jang, Y. M. (2020). 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions. IEEE Open Journal of the Communications Society, 1, 957–975.

  2. Energy-Efficient UAV-to-User Scheduling to Maximize Throughput in Wireless Networks

    • Authors: Shakil Ahmed, Mostafa Zaman Chowdhury, Yeong Min Jang
    • Journal: IEEE Access
    • Year: 2020
    • Citation: Ahmed, S., Chowdhury, M. Z., & Jang, Y. M. (2020). Energy-Efficient UAV-to-User Scheduling to Maximize Throughput in Wireless Networks. IEEE Access, 8, 21215–21225.

  3. Energy-Efficient UAV Relaying Communications to Serve Ground Nodes

    • Authors: Shakil Ahmed, Mostafa Zaman Chowdhury, Yeong Min Jang
    • Journal: IEEE Communications Letters
    • Year: 2020
    • Citation: Ahmed, S., Chowdhury, M. Z., & Jang, Y. M. (2020). Energy-Efficient UAV Relaying Communications to Serve Ground Nodes. IEEE Communications Letters, 24(4), 849–852.

  4. Non-Orthogonal Multiple Access in a mmWave Based IoT Wireless System with SWIPT

    • Authors: Hao Sun, Qiang Wang, Shakil Ahmed, Rose Hu
    • Conference: IEEE Vehicular Technology Conference (VTC Spring)
    • Year: 2017
    • Citation: Sun, H., Wang, Q., Ahmed, S., & Hu, R. (2017). Non-Orthogonal Multiple Access in a mmWave Based IoT Wireless System with SWIPT. In 2017 IEEE 85th Vehicular Technology Conference (VTC Spring) (pp. 1–5).

  5. A Disaster Response Framework Based on IoT and D2D Communication Under 5G Network Technology

    • Authors: Shakil Ahmed, Md Rashid, Farzana Alam, B. Fakhruddin
    • Conference: 2019 29th International Telecommunication Networks and Applications Conference (ITNAC)
    • Year: 2019
    • Citation: Ahmed, S., Rashid, M., Alam, F., & Fakhruddin, B. (2019). A Disaster Response Framework Based on IoT and D2D Communication Under 5G Network Technology. In 2019 29th International Telecommunication Networks and Applications Conference (ITNAC) (pp. 20–25).

 

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.