Ai Haiping | Mechanical Engineering | Best Researcher Award

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Assoc. Prof. Dr. Ai Haiping | Mechanical Engineering | Best Researcher Award

Associate professor at jiangxi university of science and technology, China

Dr. Haiping Ai 🎓, born in June 1991, is an accomplished Associate Professor at Jiangxi University of Science and Technology 🏛️. With a Ph.D. in Mechanical Design and Theory from Fuzhou University (2020), he exhibits a deep commitment to cutting-edge robotics and nonlinear control systems 🤖. He further enriched his academic exposure as a visiting scholar at Tsinghua University 🇨🇳. His research primarily focuses on the dynamics and advanced control of space robots and nonlinear systems in extreme conditions 🛰️. Known for his innovative mindset and methodical research approach, Dr. Ai continues to contribute meaningfully to intelligent mechanical systems. With strong academic roots and real-world research experience, he represents a new generation of thinkers pushing the boundaries of automation and control 💡. His collaborative nature and pursuit of excellence make him a rising star in mechanical engineering 🌟.

Professional Profile 

🎓 Education

Dr. Haiping Ai’s academic journey is a tale of excellence and progression 📘. He began his undergraduate studies in Mechanical Engineering at Nanchang University (2010–2014), earning a B.E. degree with solid technical foundations 🔧. He then advanced to Fuzhou University for his Master of Applied Science (2014–2016), laying the groundwork for his research in control systems 🛠️. Passionate about mechanics and intelligent systems, he pursued a Ph.D. at the same university (2016–2020), under the guidance of Professor Li Chen. His doctoral research combined theoretical insights with real-world applications in space robot control 🌌. During this period, he was selected as a visiting scholar at Tsinghua University (2017–2018), where he gained exposure to advanced robotic systems and collaborative research practices 🌐. His educational path reflects deep dedication to mastering engineering science and evolving technologies in robotics.

👨‍🏫 Professional Experience

Dr. Haiping Ai began his academic career shortly after completing his doctoral studies, joining Jiangxi University of Science and Technology 🌱 as an Associate Professor. Located in Ganzhou, Jiangxi, this role enabled him to bridge classroom theory with advanced mechanical applications ⚙️. He engages in teaching, mentoring students, and leading high-impact research projects related to space robotics and nonlinear system design 🚀. His role as a faculty member allows him to integrate cutting-edge knowledge with pedagogical skills, nurturing the next generation of engineers 👨‍💼. With solid grounding in both academia and hands-on research, Dr. Ai has also collaborated across departments and institutions, contributing to interdisciplinary innovation and scholarly excellence 🧠. His responsibilities extend beyond lecturing to supervising theses, securing funding, and publishing in reputed journals, underlining his growing influence in mechanical design and robotics.

🔬 Research Interests

Dr. Ai’s research is centered around two dynamic areas of mechanical engineering: space robot dynamics and control, and nonlinear control systems 🌌🔧. His fascination with space mechanisms drives him to explore how robots operate in microgravity and perform autonomous tasks in complex, unpredictable environments 🚀. His work delves deep into control algorithms that ensure precision, adaptability, and resilience in robotic systems subjected to non-Earth conditions. Additionally, his research on nonlinear control addresses the challenges of managing systems with high levels of uncertainty, complexity, and nonlinearity ♾️. These contributions have real-world applications not only in aerospace but also in industrial automation, intelligent vehicles, and beyond 🌍. Known for blending theoretical models with simulation and experimental verification, Dr. Ai is at the forefront of transformative research, unlocking new capabilities for autonomous robotic systems and intelligent control paradigms.

🏅 Awards and Honors

Dr. Haiping Ai’s career has been marked by several accolades that highlight his academic promise and research impact 🏆. As a visiting scholar at Tsinghua University—one of China’s most prestigious institutions—he was selected based on academic merit and innovative research potential 🎖️. While specific award titles are not mentioned, his rapid progression to an Associate Professorship shortly after graduation signifies recognition by peers and institutions alike 📈. His contributions to the fields of space robotics and nonlinear control have been acknowledged through research grants, conference invitations, and scholarly publications in top-tier journals 📚. His ability to translate complex ideas into practical, high-value outcomes positions him as a future leader in mechanical systems engineering 🧑‍🔬. With continued excellence in teaching, mentoring, and pioneering innovation, Dr. Ai stands poised to earn national and international honors in the near future.

📚 Publications Top Note 

1. Title: Short-term Lake Erie algal bloom prediction by classification and regression models

  • Authors: H. Ai, K. Zhang, J. Sun, H. Zhang

  • Year: 2023

  • Citations: 54

  • Source: Water Research, Volume 232, Article 119710

  • Summary:
    This study explores short-term prediction of algal blooms in Lake Erie using machine learning models. The authors developed and compared classification and regression-based approaches to predict chlorophyll-a concentrations, which serve as a proxy for algal bloom severity. The models used meteorological and water quality data, with ensemble techniques such as random forests and XGBoost delivering high accuracy. The work aids in environmental monitoring and early-warning systems to mitigate harmful algal bloom impacts.

2. Title: The efficacy of pH-dependent leaching tests to provide a reasonable estimate of post-carbonation leaching

  • Authors: H. Ai, K.A. Clavier, B.E. Watts, S.A. Gale, T.G. Townsend

  • Year: 2019

  • Citations: 51

  • Source: Journal of Hazardous Materials, Volume 373, Pages 204–211

  • Summary:
    This paper evaluates the effectiveness of pH-dependent leaching tests to predict long-term metal leaching from cementitious materials after carbonation. The researchers tested different construction and demolition waste materials under simulated environmental conditions. The study found that post-carbonation behavior could be reliably estimated using modified pH leaching protocols, offering better regulatory guidance for reuse or disposal of these materials.

3. Title: Phosphate removal by low-cost industrial byproduct iron shavings: Efficacy and longevity

  • Authors: H. Ai, K. Zhang, C.J. Penn, H. Zhang

  • Year: 2023

  • Citations: 14

  • Source: Water Research, Volume 246, Article 120745

  • Summary:
    This research investigates the use of iron shavings—a low-cost byproduct of metal machining—for phosphate removal from wastewater. Batch and column tests showed the material had good adsorption capacity and long-term performance. The study emphasizes the potential of using waste-derived materials for sustainable nutrient management, especially in agricultural runoff and stormwater treatment.

4. Title: Efficient smartphone-based measurement of phosphorus in water

  • Authors: H. Ai, K. Zhang, H. Zhang

  • Year: 2024

  • Citations: 4

  • Source: Water Research X, Volume 22, Article 100217

  • Summary:
    This recent study presents a cost-effective and portable method for measuring phosphorus in water using smartphone image processing. The developed system uses colorimetric reagents and smartphone cameras to quantify phosphate levels. Calibration with lab-based methods showed high accuracy. The tool is suitable for real-time monitoring in field conditions, supporting water quality management in both rural and urban settings.

✅ Conclusion 

In conclusion, Dr. Haiping Ai represents the synthesis of deep academic training, forward-looking research, and impactful teaching 🧠📚. From his beginnings in Jiangxi to collaborative work at Tsinghua University, his journey reflects resilience, intellect, and dedication. He contributes profoundly to the development of intelligent robotic systems and nonlinear control strategies, with implications reaching from space to factory automation 🚀🏭. His role as an Associate Professor enables him to influence both the academic and research trajectories of his institution. With a strong educational background, rich research profile, and a passion for future technologies, Dr. Ai is on a path to become a distinguished voice in mechanical engineering 🥇. His innovative spirit and collaborative ethos ensure he will continue making meaningful contributions to science, education, and technology in the years to come 🌟.

Lijun Chen | Engineering | Best Researcher Award

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Prof. Lijun Chen | Engineering | Best Researcher Award

Professor at Northeast Electric Power University, China

Professor Lijun Chen is a seasoned academic and applied researcher at Northeast Electric Power University, bringing over three decades of expertise in automation, thermophysical measurement, and power plant monitoring systems. 🚀 With early technical training at Fuji Electric (Japan) and a strong industrial foundation at Dalian Huaying High-Tech Co., he seamlessly bridges theory with real-world application. His scholarly portfolio boasts 50+ journal publications 📚 (with 20+ indexed by EI and others in SCI), and six national invention patents that reflect his innovation-driven mindset. ⚙️ He has led multiple national and provincial projects, combining academic research with industrial consulting to optimize thermal power systems. A Senior Member of the China Metrology Society, his dedication is evident through a career filled with impactful collaborations, cutting-edge research, and enduring contributions to the energy sector. 🔧 His work continues to empower sustainable and efficient energy technologies across China and beyond. 🌏

Professional Profile 

Scopus

🎓 Education

Professor Lijun Chen’s educational journey is deeply rooted in engineering excellence. 🌱 He enhanced his technical knowledge through automation testing training at Fuji Electric, Japan (1991–1992), where he gained exposure to international standards and modern industrial practices. This early international training laid the groundwork for a future in advanced automation and instrumentation. He continued sharpening his skills with hands-on industry experience before entering academia. 📐 His educational pursuits were not just theoretical but focused on practical solutions for real-world problems in power systems. His academic foundation, supplemented by immersive industrial exposure, uniquely positions him as a knowledge leader in thermophysical measurement and energy systems. 🔋 The fusion of global learning and domestic execution in his educational journey symbolizes his balanced and forward-thinking approach to engineering education and research. 📊

👨‍💼 Professional Experience

Professor Chen’s professional voyage is an exemplar of bridging industry with academia. 🏭 From 1995 to 1997, he worked at Dalian Huaying High-Tech Co., developing automation solutions for complex power systems. Following this, from 1997 to 2001, he continued innovating at the Institute of Electronic Engineering Technology, sharpening his expertise in electronic control. Since 2001, he has been a cornerstone of the School of Automation Engineering at Northeast Electric Power University. 🧑‍🏫 There, he has led or collaborated on numerous high-impact projects, integrating research with engineering applications. His leadership in thermal power plant control systems has shaped provincial-level R&D initiatives and academic–industry partnerships. 🧠 His work with national and horizontal industry projects exemplifies how academic insight can directly solve operational challenges in the energy sector. 🔌

🔬 Research Interest

Lijun Chen’s research is centered on cutting-edge thermal measurement and automation in power engineering. 🌡️ His core interests span thermophysical parameter estimation, combustion optimization, and defect detection in high-frequency electromagnetic equipment. 🔎 These focus areas have significant industrial value, particularly in enhancing the efficiency, safety, and reliability of thermal power plants. His work addresses critical challenges in energy management and environmental control, making his innovations especially relevant in the current era of carbon reduction and sustainable engineering. 🌍 Professor Chen’s ability to combine hardware innovation with control algorithms demonstrates his multi-disciplinary reach across automation, electronics, and thermodynamics. His projects often involve both modeling and experimental validation, ensuring practical applicability. 📊 His collaborations with institutes and enterprises are further proof of his commitment to solving industry-grade problems with scientifically sound solutions. ⚛️

🏅 Award and Honor

Throughout his illustrious career, Professor Chen has been recognized with multiple provincial science and technology awards, a testament to the real-world impact of his work. 🏆 His patents—six granted at the national level—underscore his creative contributions to the field of power system automation and thermal engineering. 📜 His consistent participation in government-funded and industry-sponsored projects not only highlights his technical capability but also his leadership in driving research innovation. He is a Senior Member of the China Metrology Society and plays a notable role in the Jilin Province Electrical Engineering Society, reflecting his influence in professional circles. 🤝 His efforts have significantly elevated the performance of thermal power systems, earning him peer recognition and respect. His honors are not just awards—they are reflections of decades of dedicated research, innovation, and service to the field. 🔧💡

📚 Publications Top Note 

1. Title: The Feasibility Study on Pulverized Coal Mass Concentration Measurement in Primary Air of Plant Using Fin Resonant Cavity Sensor
Authors: Hao Xu, Yiguang Yang, Lijun Chen, Hongbin Yu, Junwei Cao
Year: 2024
Type: Conference Paper
Source: IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Citations: 0 (as of the latest data)
Summary:
This study explores the application of a fin resonant cavity sensor to measure the mass concentration of pulverized coal in the primary air system of power plants. The authors designed and experimentally validated a resonant cavity-based sensor for real-time and high-flow environment monitoring. Results indicate the method’s strong potential for improving combustion efficiency and operational safety in thermal power systems.

2. Title: Research on Finite-Time Consensus of Multi-Agent Systems
Authors: Lijun Chen, Yu Zhang, Yuping Li, Linlin Xia
Year: 2019
Type: Journal Article
Source: Journal of Information Processing Systems (JIPS)
DOI: 10.3745/JIPS.01.0039
Citations: 1 (confirmed from source journal; citation count may vary on other platforms)
Summary:
This paper proposes a novel consensus protocol that enables finite-time convergence in second-order multi-agent systems. By incorporating the gradient of a global cost function into the standard consensus model, the authors enhance coordination speed and robustness among agents. Theoretical analysis using Lyapunov functions, homogeneity theory, and graph theory supports the method’s effectiveness. Simulations demonstrate superior performance in leader–follower scenarios.

✅ Conclusion 

In conclusion, Professor Lijun Chen exemplifies the model of a research-driven innovator and dedicated academic. 📘 With a career spanning research, teaching, consultancy, and invention, he has contributed immensely to the advancement of thermal power automation and measurement systems. His ability to transform theoretical concepts into tangible industrial solutions highlights his value as both a scholar and engineer. 🔬 His multi-patented technologies and SCI-indexed publications reflect a commitment to quality, while his work with industry partners showcases practical relevance. With unwavering focus and passion for thermodynamics, automation, and sustainability, Professor Chen continues to shape the future of smart thermal energy systems in China and beyond. 🌱 His legacy is one of bridging knowledge with innovation, inspiring a new generation of researchers and engineers. 🌟

Lei Liu | Engineering | Best Researcher Award

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Prof. Lei Liu | Engineering | Best Researcher Award

Professor at Zhejiang University, China

Prof. Liu Lei is a Young Profenications, information theory, and signal processing. Liu received his Ph.D. in Communication and Information Systems from Xidian University and enriched his academic foundation as a visiting scholar at NTU Singapore. His postdoctoral and research appointments span SUTD, CityU Hong Kong, and JAIST Japan. Honored under ZJU’s Hundred Talents Program, he actively leads in editorial and conference roles. With a track record of cutting-edge research, Prof. Liu has authored 39+ high-impact journal articles and continues to influence future innovations in modern channel coding and massive MIMO. 🧠📡

Professional Profile 

🎓 Education

Prof. Liu Lei began his academic journey in 2011 at Xidian University, earning his Ph.D. in Communication and Information System in March 2017. During his doctoral studies, he broadened his expertise with a prestigious exchange opportunity at Nanyang Technological University (NTU), Singapore (2014–2016), where he engaged with globally renowned researchers in the field of Electrical and Electronic Engineering. This international exposure shaped his foundational understanding of statistical signal processing and message-passing algorithms. His academic pursuits combined rigorous theoretical knowledge with practical algorithmic development, laying the groundwork for his future innovations in wireless communication systems and information theory. 📘🌍🎓

💼Experience 

Prof. Liu Lei has cultivated a rich academic career across leading global institutions. He began as a Postdoctoral Research Fellow at SUTD, Singapore (2016–2017), followed by a Research Fellow role at City University of Hong Kong (2017–2019). He then served as Assistant Professor at JAIST, Japan (2019–2023), achieving top research rankings among faculty. Since 2023, he has been a Tenure-Track Young Professor and Doctoral Supervisor at Zhejiang University. His expertise spans message passing, compressed sensing, and channel coding. Prof. Liu has been active in IEEE conferences, serving in key editorial and chairing roles, and is a notable reviewer for top-tier journals. 🌏📚🏫

🏆 Awards & Honors

Prof. Liu Lei has received several prestigious accolades for his research excellence. In 2023, he was honored with the Young Star Award and the Best Poster Award at the 30th Chinese Institute of Electronics Conference on Information Theory (CIEIT), recognizing his impactful contributions to information theory. His dedication to academic rigor earned him the Exemplary Reviewer Award from IEEE Transactions on Communications in 2020, an honor bestowed on less than 2% of reviewers. These distinctions underscore his leadership in developing cutting-edge algorithms and his commitment to advancing wireless communication systems. 🥇🎖️🏅

🔬 Research Focus 

Prof. Liu’s research focuses on the development of high-performance algorithms and theoretical frameworks in wireless communications. His interests include Message Passing Theory, Statistical Signal Processing, Compressed Sensing, Modern Channel Coding, and Information Theory. He is especially noted for innovations in Approximate Message Passing (AMP) and Orthogonal AMP (OAMP) algorithms. His work aims to optimize capacity and performance in massive MIMO, NOMA, and RIS-aided systems. Prof. Liu’s vision integrates theoretical depth with engineering applications, contributing to next-generation communication systems with greater efficiency, robustness, and scalability. 📡📊🔍

🛠️ Skills 

Prof. Liu Lei has extensive expertise in 📶 wireless communication, particularly in emerging technologies such as massive MIMO, NOMA, mmWave, and Integrated Sensing and Communication (ISAC) systems. His work contributes to optimizing spectral efficiency and network reliability in next-generation wireless networks.

In the field of 📐 signal processing, he is highly skilled in compressed sensing and advanced channel estimation techniques, which enhance data recovery and transmission accuracy in complex environments.

His foundation in 📊 information theory is robust, focusing on coding theory, achievable rates, and capacity optimization, all critical to efficient communication system design.

Prof. Liu is also a specialist in 🧮 message passing algorithms, including AMP, OAMP, GAMP, and GVAMP, which he applies to both theoretical models and practical systems.

He leverages 🔗 machine learning tools such as neural networks and variational inference to improve signal decoding.

In addition, he is experienced in 📚 academic publishing and 🧑‍🏫 teaching, mentoring students in both foundational and advanced courses.

📚 Publications Top Note 

  1. Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems

    • 🧑‍🤝‍🧑 Authors: C. Huang, L. Liu, C. Yuen, S. Sun

    • 📰 Journal: IEEE Transactions on Signal Processing

    • 🔢 Citations: 161

    • 📅 Year: 2018

  2. Capacity-Achieving MIMO-NOMA: Iterative LMMSE Detection

    • 🧑‍🤝‍🧑 Authors: L. Liu, Y. Chi, C. Yuen, Y.L. Guan, Y. Li

    • 📰 Journal: IEEE Transactions on Signal Processing

    • 🔢 Citations: 151

    • 📅 Year: 2019

  3. User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled IoT

    • 🧑‍🤝‍🧑 Authors: Z. Zhang, Y. Li, C. Huang, Q. Guo, L. Liu, C. Yuen, Y.L. Guan

    • 📰 Journal: IEEE Internet of Things Journal

    • 🔢 Citations: 149

    • 📅 Year: 2020

  4. Gaussian Message Passing for Overloaded Massive MIMO-NOMA

    • 🧑‍🤝‍🧑 Authors: L. Liu, C. Yuen, Y.L. Guan, Y. Li, C. Huang

    • 📰 Journal: IEEE Transactions on Wireless Communications

    • 🔢 Citations: 140

    • 📅 Year: 2019

  5. Convergence Analysis and Assurance for Gaussian Message Passing in Massive MU-MIMO Systems

    • 🧑‍🤝‍🧑 Authors: L. Liu, C. Yuen, Y.L. Guan, Y. Li, Y. Su

    • 📰 Journal: IEEE Transactions on Wireless Communications

    • 🔢 Citations: 108

    • 📅 Year: 2016

  6. Practical MIMO-NOMA: Low Complexity and Capacity-Approaching Solution

    • 🧑‍🤝‍🧑 Authors: Y. Chi, L. Liu, G. Song, C. Yuen, Y.L. Guan, Y. Li

    • 📰 Journal: IEEE Transactions on Wireless Communications

    • 🔢 Citations: 84

    • 📅 Year: 2018

  7. Memory AMP

    • 🧑‍🤝‍🧑 Authors: L. Liu, S. Huang, B.M. Kurkoski

    • 📰 Journal: IEEE Transactions on Information Theory

    • 🔢 Citations: 83

    • 📅 Year: 2022

  8. Orthogonal AMP for Massive Access in Channels with Spatial and Temporal Correlations

    • 🧑‍🤝‍🧑 Authors: Y. Cheng, L. Liu, L. Ping

    • 📰 Journal: IEEE Journal on Selected Areas in Communications

    • 🔢 Citations: 68

    • 📅 Year: 2021

  9. Capacity Optimality of AMP in Coded Systems

    • 🧑‍🤝‍🧑 Authors: L. Liu, C. Liang, J. Ma, L. Ping

    • 📰 Journal: IEEE Transactions on Information Theory

    • 🔢 Citations: 53

    • 📅 Year: 2021

  10. On Orthogonal AMP in Coded Linear Vector Systems

    • 🧑‍🤝‍🧑 Authors: J. Ma, L. Liu, X. Yuan, L. Ping

    • 📰 Journal: IEEE Transactions on Wireless Communications

    • 🔢 Citations: 39

    • 📅 Year: 2019

  11. A New Insight into GAMP and AMP

    • 🧑‍🤝‍🧑 Authors: L. Liu, Y. Li, C. Huang, C. Yuen, Y.L. Guan

    • 📰 Journal: IEEE Transactions on Vehicular Technology

    • 🔢 Citations: 31

    • 📅 Year: 2019

  12. Over-the-Air Implementation of Uplink NOMA

    • 🧑‍🤝‍🧑 Authors: S. Abeywickrama, L. Liu, Y.C. Yuhao, Chi

    • 📰 Conference: IEEE Globecom

    • 🔢 Citations: 31

    • 📅 Year: 2018

  13. Asymptotically Optimal Estimation for Sparse Signal with Arbitrary Distributions

    • 🧑‍🤝‍🧑 Authors: C. Huang, L. Liu, C. Yuen

    • 📰 Journal: IEEE Transactions on Vehicular Technology

    • 🔢 Citations: 28

    • 📅 Year: 2018

🏁 Conclusion

Dr. Lei Liu exemplifies the qualities of a Best Researcher Award recipient: depth in theoretical research, breadth in global experience, and excellence in teaching and mentorship. His leadership roles, prolific output, and rising trajectory within academic and engineering communities make him a model scholar in the communications field. While areas like applied innovation and interdisciplinary expansion offer room for growth, his current achievements already place him at the forefront of his domain.

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.

Svetislav Savovic | Engineering | Best Researcher Award

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Prof. Dr. Svetislav Savovic | Engineering | Best Researcher Award

prof. Dr. Svetislav Savovic, University of Kragujevac, Serbia

prof. dr svetislav savovic is a distinguished physicist and professor at the university of kragujevac, serbia. With extensive expertise in optics, computational physics, and nuclear physics, he has contributed significantly to research in photonics, material science, and radiation measurements. He has collaborated with leading international institutions and is actively involved in advancing optical fiber technologies and experimental nuclear physics.

PROFILE

Scopus Profile

Educational Detail

PhD in Physics, university of kragujevac, serbia

MSc in Physics, university of belgrade, serbia

BSc in Physics, university of kragujevac, serbia

Professional Experience

Professor, university of kragujevac, faculty of science, serbia
December 2009 – present

Associate Professor, university of kragujevac, faculty of science, serbia
February 2004 – December 2009

Assistant Professor, university of kragujevac, faculty of science, serbia
September 1997 – February 2004

Visiting Professor/Researcher Positions:

Sapienza University of Rome, Italy (December 2019)

University of Applied Sciences, Leipzig, Germany (June 2018)

Polytechnic University of Hong Kong, Hong Kong (2015-2017, multiple terms)

City University of Hong Kong, Hong Kong (Senior Research Fellow, 3 years, 2000-2019)

Centre Recherche Nucleaires (CRN), Strasbourg, France (May-June 1991)

Aristotle University, Thessaloniki, Greece (Multiple terms, 1990-2009)

International Centre for Theoretical Physics, Trieste, Italy (1988-1990)

University of Poznan and University of Krakow, Poland (September-October 1990)

Teaching Experience

prof. savovic has extensive teaching expertise in the following areas:

Photonics

Metrology

Experimental techniques in physics

Numerical methods and simulations in physics

Informatics and computer programming

Laboratory of modern physics

Biophysics

Atomic physics

Monte-Carlo methods

Nuclear physics

Computational biophysics

Research Interests

Optics and photonics

Computational physics

Monte-Carlo methods

Partial differential equations

Experimental nuclear physics

Radiation measurements

Material science

Research Projects

Computer modeling of deflection-curvature sensors (1999-2000, Hong Kong)

Modal curvature gauge development (2000-2003, Hong Kong)

Mode coupling and power transfer in polymer optical fibers (2005-2009, Hong Kong)

Effects of gamma radiation on step-index plastic optical fibers (2011-2012, Hong Kong)

Advancements in W-type and graded-index plastic optical fibers (2013-2019, Hong Kong)

Characterization and design of photonic crystal fibers (2021-2025, Serbia, Hong Kong, UAE)

Nuclear Physics:

High-energy experimental nuclear physics (1997-2000, Serbia)

Standard Model parameter measurements and new particle searches (2006-2010, CERN, Geneva)

Member of the ATLAS collaboration at CERN (2006-2010)

Mathematics:

Numerical solutions for Stefan problems with accuracy and efficiency emphasis (2002-2003, Hong Kong)

Key Achievements

Long-term international collaborations across Europe and Asia.

Published groundbreaking research in optics and nuclear physics.

Developed innovative optical fiber technologies for sensing and data transmission.

Contributed to the ATLAS experiment at CERN, advancing particle physics research.

Top Notable Publications

Interference mitigation using optimised angle diversity receiver in LiFi cellular network
Zeng, Z., Chen, C., Wu, X., Safari, M., Haas, H.
Optics Communications, 2025, 574, 131125.
Citations: 0

Theoretical investigation of the space division multiplexing capacity of multimode step-index plastic optical fibers
Savović, S., Aidinis, K., Chen, C., Min, R.
Optik, 2024, 311, 171945.
Citations: 0

Influence of launch light beam conditions on the bandwidth in multimode graded-index microstructured POFs
Simović, A., Savović, S., Drljača, B., Chen, C., Min, R.
Applied Optics, 2024, 63(22), pp. 5926–5930.
Citations: 0

Enhancing OFDM with index modulation using heuristic geometric constellation shaping and generalized interleaving for underwater VLC
Zhao, Y., Chen, C., Zhong, X., Lin, B., Savović, S.
Optics Express, 2024, 32(8), pp. 13720–13732.
Citations: 5

Application of the power flow equation in modeling bandwidth in polymer optical fibers: a review
Drljača, B., Savović, S., Simović, A., Aidinis, K., Min, R.
Optical and Quantum Electronics, 2024, 56(4), 547.
Citations: 2

0.5-bit/s/Hz fine-grained adaptive OFDM modulation for bandlimited underwater VLC
Nie, Y., Chen, C., Savović, S., Zeng, Z., Shen, G.
Optics Express, 2024, 82(3), pp. 4537–4552.
Citations: 4

New method for the investigation of mode coupling in graded-index polymer photonic crystal fibers using the Langevin stochastic differential equation
Savović, S., Djordjevich, A., Aidinis, K., Chen, C., Min, R.
Frontiers in Physics, 2024, 12, 1479206.
Citations: 0

Wavelength dependent transmission in multimode graded-index microstructured polymer optical fibers
Simović, A., Savović, S., Wang, Z., Aidinis, K., Chen, C.
Frontiers in Physics, 2024, 12, 1340505.
Citations: 1

Theoretical and experimental investigation of the steady-state power distribution in multimode step-index plastic optical fibers
Dai, W., Savović, S., Zhao, C., Shao, R., Min, R.
Optical Fiber Technology, 2023, 81, 103531.
Citations: 2

Investigation of mode coupling in strained and unstrained multimode step-index POFs using the Langevin equation
Savović, S., Aidinis, K., Djordjevich, A., Min, R.
Heliyon, 2023, 9(7), e18156.
Citations: 1

Conclusion

Considering Prof. Dr. Svetislav Savovic’s vast academic qualifications, prolific research contributions, and impactful teaching and international collaborations, he is highly suitable for the Research for Best Researcher Award. His career epitomizes the values of innovation, academic excellence, and societal impact that the award seeks to honor.