Prof. Hwa Yaw Tam | Engineering | Best Researcher Award

Published on 10/07/202510/07/2025 by Physicist Particle

Prof. Hwa Yaw Tam | Engineering | Best Researcher Award

Prof. Hwa Yaw Tam at The Hong Kong Polytechnic University , Hong Kong

Prof. Hwa Yaw TAM 🎓🔬, IEEE Life Fellow and OPTICA Fellow, is a visionary in photonics and optical fibre sensing. Currently Chair Professor of Photonics at The Hong Kong Polytechnic University 🇭🇰, he has spearheaded groundbreaking innovations in fibre-optic sensor systems for transportation 🚄, energy ⚡, and medical 👂 applications. With over 800 publications 📚 and 20 patents 🔖, he stands as the second most cited expert in fibre-optic sensing, boasting an H-index of 73. His trailblazing contributions span continents, from Hong Kong’s MTR to the Netherlands and Australia 🌍. A laureate of the Berthold Leibinger Innovationspreis 🏆 and multiple Geneva Invention awards, Prof. Tam’s legacy bridges academia, industry, and public safety. His work has also spun off seven photonics companies 🚀. With unwavering passion and pioneering spirit, Prof. Tam continues to illuminate the future of smart sensing and laser technologies 🔭.

Professional Profile

🎓 Education

Prof. Hwa Yaw TAM embarked on his academic voyage at The University of Manchester, UK 🇬🇧, earning both his B.Eng in 1985 and Ph.D. in 1989 🎓. His early educational foundations laid the groundwork for a lifelong commitment to photonics and optical engineering. Specializing in electrical and electronic engineering, his doctoral studies fused rigorous theory with hands-on research in laser systems and fibre technologies 🔍. This dual emphasis cultivated a mindset driven by innovation and precision. The UK academic environment, rich in historical scientific achievement, greatly influenced his research ethos 🌐. Prof. Tam’s education not only equipped him with cutting-edge technical knowledge but also instilled in him a vision to translate science into impactful, real-world applications. Today, that foundation continues to echo through his advanced fibre-optic sensor innovations 🔬, standing as a beacon for future generations of engineers and scientists 📘💡.

🏛️ Professional Experience

Prof. Tam’s professional journey spans academia and industry in equal brilliance 🌠. He began his research career at GEC-Marconi Ltd. (London) between 1989–1993, delving into erbium-doped fibre amplifiers and laser systems 💡. He then joined The Hong Kong Polytechnic University in 1993, rising through the ranks from Lecturer to Chair Professor of Photonics. He also served as Head of the Electrical Engineering Department and was the Founding Director of the Photonics Research Centre (2000–2022) 🏫. Presently, he is Associate Director at PolyU’s Photonics Research Institute, spearheading interdisciplinary innovations. Prof. Tam’s work transcends traditional academia—his team has launched seven start-ups, catalyzing photonics-based solutions globally 🚀. His leadership has shaped fibre-optic sensing systems for cities and industries across Asia, Europe, and Australia, turning theoretical breakthroughs into operational systems in railways 🚉, energy grids 🔋, and hospitals 🏥, positioning him as a pivotal force in global smart sensing networks 🌐.

🔬 Research Interest

Prof. Tam’s research orbits around specialty optical fibres tailored for real-world sensor applications 🔍. His core interests span the design and fabrication of advanced fibre-optic systems that serve as digital sentinels in complex infrastructures 🧠. From structural health monitoring (SHM) to real-time railway diagnostics, his innovations help prevent failures before they occur ⚠️. His pioneering optical fibre networks have monitored everything from high-speed trains 🚆 to smart escalators and even cochlear implants for medical precision 👂. By embedding fibre Bragg gratings (FBGs) into intelligent sensing webs, he’s revolutionized predictive maintenance across industries. His group’s work is particularly transformative in railway monitoring, with deployment success stories in Hong Kong, Singapore, and the Netherlands 🌍. Always ahead of the curve, Prof. Tam’s research fuses AI 🤖, photonic engineering, and real-time analytics to create a safer, more connected world through light 🌈 and precision sensing technologies 📈.

🏅 Awards and Honors

Prof. Tam’s achievements are globally celebrated 🏆. In 2025, he won the Special Prize and Gold Medal at Geneva’s Invention Expo for a smart cochlear implant 👂🌟. In 2024, he secured another Gold Medal for lithium-ion battery health monitoring via FBG sensors 🔋. Earlier, in 2022, his intelligent escalator monitoring system earned him yet another Geneva Gold Award 🥇. The Berthold Leibinger Innovationspreis in 2014, among the world’s highest laser tech honors, recognized his work in wavelength-tunable laser sensing for railways 🚄. His team also received the President’s Award for Knowledge Transfer in 2022 at PolyU for creating AI-enhanced optical fibre networks 🌐. Further accolades include a Best Paper finalist at IEEE SENSORS 2016 📃. Each honor underscores Prof. Tam’s deep impact on laser technology, smart sensing, and translational engineering. His consistent award-winning contributions reflect a perfect blend of scientific creativity, societal value, and engineering excellence 💼🔬.

📚 Publications Top Note

Title: Enhanced Quasi-Distributed Accelerometer Array Based on ϕ-OTDR and Ultraweak Fiber Bragg Grating
Authors: , , , …
Year: 2023
Citations: 6
Source: IEEE Sensors Journal
Summary: Proposes an enhanced accelerometer array using phase-sensitive optical time-domain reflectometry (ϕ-OTDR) and ultraweak fiber Bragg gratings for distributed vibration sensing, suitable for applications like structural health monitoring.

Title: Label-Free DNA Detection Using Etched Tilted Bragg Fiber Grating-Based Biosensor
Authors: , , , …
Year: 2023
Citations: 6
Source: Sensors
Summary: Describes a label-free biosensor using etched tilted fiber Bragg gratings to detect DNA without the need for fluorescent labels, enhancing sensitivity and simplicity in genetic diagnostics.

Title: Recovery of a Highly Reflective Bragg Grating in DPDS-Doped Polymer Optical Fiber by Thermal Annealing
Authors: , , , …
Year: 2023
Citations: 2
Source: Optics Letters
Summary: Demonstrates the recovery of degraded Bragg gratings in doped polymer optical fibers using thermal annealing, showing potential for longer lifespan and reusability in fiber-optic sensors.

Title: Accident Risk Tensor-Specific Covariant Model for Railway Accident Risk Assessment and Prediction
Authors: , , , …
Year: 2023
Citations: 8
Source: Reliability Engineering and System Safety
Summary: Introduces a tensor-based statistical model for accurately assessing and predicting accident risks in railway systems by incorporating covariant risk factors.

Title: Polymeric Fiber Sensors for Insertion Forces and Trajectory Determination of Cochlear Implants in Hearing Preservation
Authors: , , , …
Year: 2023
Citations: 10
Source: Biosensors and Bioelectronics
Summary: Presents polymeric fiber-optic sensors designed to measure insertion force and trajectory during cochlear implant surgeries, helping to preserve hearing by reducing inner ear trauma.

Title: Miniature Two-Axis Accelerometer Based on Multicore Fiber for Pantograph-Catenary System
Authors: , , , ,
Year: 2023
Citations: 8
Source: IEEE Transactions on Instrumentation and Measurement
Summary: Develops a compact fiber-based accelerometer capable of sensing in two axes, tailored for monitoring the dynamics of pantograph-catenary interactions in electric rail systems.

Title: Ultraminiature Optical Fiber-Tip Directly-Printed Plasmonic Biosensors for Label-Free Biodetection
Authors: , , , …
Year: 2022
Citations: 19
Source: Biosensors and Bioelectronics
Summary: Describes a highly miniaturized fiber-tip plasmonic biosensor fabricated via direct printing, enabling sensitive and label-free detection of biomolecules at the microscale.

Title: Accelerated Pyro-Catalytic Hydrogen Production Enabled by Plasmonic Local Heating of Au on Pyroelectric BaTiO3 Nanoparticles
Authors: , , , …
Year: 2022
Citations: 83
Source: Nature Communications
Summary: Reports a novel hydrogen production method using gold-decorated BaTiO₃ nanoparticles, where plasmonic heating enhances pyro-catalytic activity under mild conditions.

Title: Biomechanical Assessment and Quantification of Femur Healing Process Using Fibre Bragg Grating Strain Sensors
Authors: , , , …
Year: 2022
Citations: 5
Source: Sensors and Actuators A: Physical
Summary: Uses fiber Bragg grating strain sensors to monitor and quantify mechanical changes in the femur during bone healing, supporting better postoperative assessment.

Title: Mach-Zehnder Interferometer Based Fiber-Optic Nitrate Sensor
Authors: , , , ,
Year: 2022
Citations: Not listed
Source: Optics Express
Summary: Presents a Mach-Zehnder interferometer design using optical fiber for detecting nitrate concentrations in water, aiming at applications in environmental monitoring

🔚 Conclusion

Prof. Hwa Yaw TAM is more than a scholar—he is a trailblazer in light-based sensing technologies 🌟. His career weaves together pioneering science, practical engineering, and impactful entrepreneurship 🌐. Through over 800 papers, 20 patents, and numerous awards, he has reshaped how the world monitors structural, environmental, and human conditions using optical fibres 💡. His real-world implementations—from monitoring city-wide railways to enabling hearing restoration—demonstrate how research can elevate safety, precision, and quality of life for millions 🌍. He continues to mentor future innovators and drive collaborative photonic research through his leadership roles at PolyU and the Photonics Research Institute. With vision, dedication, and humility, Prof. Tam stands as a guiding light for the global photonics community 🌠. His journey exemplifies how science, when paired with compassion and creativity, becomes a force for building a smarter, safer, and more sustainable world 🔗🌿.

Ai Haiping | Mechanical Engineering | Best Researcher Award

Published on 03/07/202503/07/2025 by Physicist Particle

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

Published on 20/06/202520/06/2025 by Physicist Particle

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

Published on 12/06/202512/06/2025 by Physicist Particle

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

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
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
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
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
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
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
Memory AMP
- 🧑‍🤝‍🧑 Authors: L. Liu, S. Huang, B.M. Kurkoski
- 📰 Journal: IEEE Transactions on Information Theory
- 🔢 Citations: 83
- 📅 Year: 2022
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
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
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
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
Over-the-Air Implementation of Uplink NOMA
- 🧑‍🤝‍🧑 Authors: S. Abeywickrama, L. Liu, Y.C. Yuhao, Chi
- 📰 Conference: IEEE Globecom
- 🔢 Citations: 31
- 📅 Year: 2018
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.

Dr. K. Lakshmi Prasanna | Engineering | Best Researcher Award

Published on 26/05/202526/05/2025 by Physicist Particle

Dr. K. Lakshmi Prasanna | Engineering | Best Researcher Award

Visiting faculty at Birla Institute of Technology and Science Pilai, India

Dr. K. Lakshmi Prasanna 🎓 is a passionate researcher and academician in the field of High Voltage Engineering, with a strong command over system modeling, fault diagnostics, and parameter estimation using MATLAB/Simulink 🛠️. She brings a unique blend of theoretical insight and hands-on expertise in simulation, optimization, control systems, and signal processing. Her innovative Ph.D. work at BITS Pilani, Hyderabad focused on transformer winding modeling and inter-turn fault diagnostics 🔍, proposing novel, non-intrusive algorithms with real-world applicability. With a foundation in Power Electronics and Electrical Engineering ⚡, she also has teaching experience at multiple esteemed engineering colleges, nurturing minds in core subjects. Driven by curiosity and adaptability, she actively embraces new software tools and collaborative environments 💡. Her professional trajectory reflects a consistent commitment to academic excellence, technical rigor, and transformative innovation in electrical engineering. 🚀

Professional Profile

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📚 Education

Dr. Lakshmi Prasanna’s educational journey 🌱 reflects a steady and impressive rise through the academic ranks of electrical engineering. Beginning with a remarkable 96.9% in her Higher Secondary 🏫, she pursued her B.Tech in EEE and M.Tech in Power Electronics from JNTUA, scoring 85.1% and 85%, respectively 🎯. Her academic excellence culminated in a Ph.D. in High Voltage Engineering at BITS Pilani, Hyderabad Campus, where she maintained an impressive 8.0 CGPA 📈. Her doctoral thesis delved into cutting-edge research on transformer fault diagnosis and system modeling, placing her at the forefront of innovation in condition monitoring and electrical diagnostics. Throughout her educational path, she has consistently demonstrated not just technical brilliance but also a hunger for knowledge and an ability to bridge theory and application seamlessly 📘⚙️.

👩‍🏫 Professional Experience

With over a decade of dedicated service in academia and research, Dr. Lakshmi Prasanna has built a versatile and impactful professional portfolio 🧠. Beginning her journey as an Assistant Professor at Rami Reddy Subbarami Reddy Engineering College (2012–2017), she laid her pedagogical foundations teaching essential subjects like Electrical Machines, Circuits, and Power Electronics 🔌. Her journey continued at St. Martin’s Engineering College (2017–2019), where she continued imparting technical knowledge with enthusiasm and clarity. From 2018 to 2025, her role as a Research Assistant at BITS Hyderabad marked a turning point, as she immersed herself in advanced simulation and transformer fault diagnostics 🔬. Beyond teaching, her experience also includes proposal writing, technical documentation using LaTeX, and collaborative interdisciplinary projects, marking her as a well-rounded professional 🌐📝.

🔍 Research Interests

Dr. Lakshmi Prasanna’s research is deeply rooted in the intelligent modeling of electrical systems, with a spotlight on transformer winding diagnostics, state-space modeling, and parameter estimation using non-intrusive techniques 🧩. Her innovative Ph.D. work proposed the integration of subspace identification and similarity transformations to estimate transformer parameters and detect inter-turn faults purely from terminal measurements ⚙️🔍. Her expertise in MATLAB M-script development, COMSOL Multiphysics simulations, and system optimization reflects a rare proficiency in both simulation and real-world application. Additionally, she is intrigued by control systems, fault-tolerant design, and signal processing, with a strong drive toward creating robust, adaptive models for condition monitoring 🧠📊. Her work directly contributes to the reliability and safety of electrical infrastructure, making her research highly relevant to modern power systems and smart grid innovation 🌐⚡.

🏅 Awards and Honors

Dr. Lakshmi Prasanna’s academic journey is marked by consistently high achievements and academic recognition 🏆. From securing a 96.9% in her HSC to maintaining top scores through her undergraduate and postgraduate studies, her excellence has been evident from the outset 🎓. While formal awards during her doctoral years may not be listed, her selection and continuation at BITS Pilani, one of India’s premier institutions, is a distinction in itself 🌟. Her progression into high-level research projects, including complex simulation and modeling of transformer systems, attests to her recognition within the academic and research community. Her teaching roles across reputed engineering colleges and involvement in technical proposal writing and collaborative research are testaments to her leadership and scholarly respect 🥇. She continues to be acknowledged for her dedication, depth of knowledge, and clarity in delivering technical content.

Publications Top Notes

1. Terminal-based method for efficient inter-turn fault localization and severity assessment in transformer windings

Authors: K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal
Year: 2025
DOI: 10.1016/j.prime.2025.100982
Source: e-Prime – Advances in Electrical Engineering, Electronics and Energy
Summary: This study introduces a non-invasive method for identifying and assessing the severity of inter-turn faults in transformer windings using only external terminal measurements. The approach enhances fault detection accuracy without requiring internal access to the transformer.

2. Radial deformation detection and localization in transformer windings: A terminal measured impedance approach

Authors: Lakshmi Prasanna Konjeti, Manoj Samal, Mithun Mondal
Year: 2025
DOI: 10.1016/j.prime.2025.100945
Source: e-Prime – Advances in Electrical Engineering, Electronics and Energy
Summary: The paper presents a novel, non-invasive method for diagnosing radial deformation faults in transformer windings by analyzing terminal impedance measurements, enabling effective detection and severity assessment based on capacitance changes.

3. A non-iterative analytical approach for estimating series-capacitance in transformer windings solely from terminal measured frequency response data

Authors: K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal
Year: 2025
DOI: 10.1016/j.epsr.2024.111086
Source: Electric Power Systems Research
Summary: This research proposes a non-iterative analytical method to estimate the series capacitance of transformer windings using only terminal frequency response data, simplifying the estimation process and improving accuracy.

4. Accurate Estimation of Transformer Winding Capacitances and Voltage Distribution Factor Using Driving Point Impedance Measurements

Authors: K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal
Year: 2024
DOI: 10.1109/ACCESS.2024.3460968
Source: IEEE Access
Summary: The study introduces an innovative methodology for precisely estimating winding capacitances and the voltage distribution factor using driving point impedance measurements, enhancing transformer modeling and analysis.

5. A Symbolic Expression for Computing the Driving Point Impedance and Pole-Zero-Gain of a Transformer from its Winding Parameters

Authors: K. Lakshmi Prasanna
Year: 2023
DOI: 10.1109/INDICON59947.2023.10440729
Source: 2023 IEEE 20th India Council International Conference (INDICON)
Summary: This paper presents a symbolic expression for computing the driving point impedance and pole-zero-gain of a transformer based on its winding parameters, facilitating efficient analysis of transformer behavior.

6. Analytical computation of driving point impedance in mutually coupled inhomogeneous ladder networks

Authors: K. Lakshmi Prasanna, Mithun Mondal
Year: 2023
DOI: 10.1002/cta.3839
Source: International Journal of Circuit Theory and Applications
Summary: The research introduces a new approach for computing the driving point impedance of inhomogeneous ladder networks with mutual coupling, enhancing the accuracy of electrical network modeling.

7. Analytical formulas for calculating the electrical characteristics of multiparameter arbitrary configurational homogenous ladder networks

Authors: K. Lakshmi Prasanna
Year: 2023
DOI: 10.1002/cta.3547
Source: International Journal of Circuit Theory and Applications
Summary: This paper presents generalized analytical formulas for computing the electrical properties of multiparameter arbitrary configuration homogeneous ladder networks, aiding in the design and analysis of complex electrical circuits.

8. Terminal Measurements-Based Series Capacitance Estimation of Power Transformer Windings Using Frequency-Domain Subspace Identification

Authors: K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal
Year: 2023
DOI: 10.1109/TIM.2023.3311074
Source: IEEE Transactions on Instrumentation and Measurement
Summary: The study proposes a method for estimating the series capacitance of power transformer windings using frequency-domain subspace identification based on terminal measurements, improving the accuracy of transformer diagnostics.

9. Elimination of Mutual Inductances from the State-Space Model of a Transformer Winding’s Ladder Network Using Eigen Decomposition

Authors: K. Lakshmi Prasanna
Year: 2022
DOI: 10.1109/CATCON56237.2022.10077664
Source: 2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON)
Summary: This paper presents a method to eliminate mutual inductances from the state-space model of a transformer winding’s ladder network using eigen decomposition, simplifying the analysis of transformer dynamics.

10. Internet Of Things (IOT) in Distribution grid using DSTATCOM

Authors: K. Lakshmi Prasanna
Year: 2019
DOI: 10.1109/RDCAPE47089.2019.8979044
Source: 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE)
Summary: The paper discusses the integration of Internet of Things (IoT) technology with DSTATCOM in distribution grids to improve power factor and enable real-time monitoring, enhancing the efficiency and reliability of power distribution systems.

✅ Conclusion

In conclusion, Dr. K. Lakshmi Prasanna stands as a beacon of innovation, diligence, and academic integrity in the realm of electrical engineering and high voltage research 🌟. Her journey from a stellar student to a dynamic researcher and dedicated educator is marked by technical excellence, innovative research, and a passion for teaching 🎯. With deep expertise in MATLAB/Simulink, transformer modeling, and non-intrusive diagnostics, she contributes meaningfully to the future of smart and resilient power systems ⚡💻. Her collaborative spirit, adaptability to emerging tools, and constant pursuit of knowledge ensure her continued relevance and impact in the scientific community 📚🚀. As she continues to explore new horizons in diagnostics and system modeling, her work promises to empower more efficient and intelligent energy systems of tomorrow 🔋🔬.

Farshad Nobakhtkolour | Engineering | Best Researcher Award

Published on 28/04/202528/04/2025 by Physicist Particle

Mr. Farshad Nobakhtkolour | Engineering | Best Researcher Award

Researcher at K.N.Toosi University of Technology, Iran

Farshad Nobakht-Kolur 🎓 is a passionate civil engineer specializing in marine structures and offshore renewable energy 🌊⚡. He earned his M.Sc. in Coasts, Ports, and Marine Structures from K. N. Toosi University of Technology and his B.Sc. in Civil Engineering from Shahrood University 🏫. Farshad’s research focuses on floating structures, marine hydrodynamics, and aquaculture engineering 🚢🌱. He has published multiple journal papers and served as a peer reviewer 📚🖋️. A top-ranked student throughout his academic journey 🏆, he continues to contribute actively to the marine engineering community through research, reviews, and professional memberships 🤝.

Professional Profile:

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🔵 Education and Experience

🎓 M.Sc. in Coasts, Ports, and Marine Structures – K. N. Toosi University of Technology (2016-2019)
🎓 B.Sc. in Civil Engineering – Shahrood University of Technology (2009-2013)
🏫 Diploma in Mathematics and Physics – Bagher-al-Olum High School (2005-2009)
👨‍🏫 Teaching Assistant – Shahrood University of Technology (Statics & Steel Structures Courses)
🧪 Researcher – Published papers in top marine and fluid mechanics journals
📑 Conference Presenter – Marine Industries Conference and academic workshops

🔵 Professional Development

Farshad Nobakht-Kolur has actively contributed to professional growth through memberships and peer reviewing 🛠️📖. He is a member of the Iranian Coastal and Marine Structural Engineering Association (ICOMSEA) 🌐, and The American Society for Nondestructive Testing (ASNT) 🧪🔍. Farshad has reviewed articles for prestigious journals like Ocean Engineering and Journal of Modern Green Energy ✍️📘. His commitment to continuous learning and sharing knowledge is evident through his workshop presentations, paper publications, and involvement with academic and industrial bodies 🌟. Farshad’s work bridges the gap between theoretical research and real-world marine engineering solutions 🌊🔗.

🔵 Research Focus Category

Farshad Nobakht-Kolur’s research focus lies in marine and offshore engineering 🌊🔧. His primary interests include floating wind turbines, floating solar islands, offshore renewable energy structures, and aquaculture engineering 🌱⚡. He specializes in fluid-structure interaction, experimental modeling, and numerical simulation 🧪💻. Farshad’s work emphasizes sustainable marine structures like floating seaweed farms and hybrid platforms that support renewable energy production and food security 🌿🔋. Through advanced physical modeling and hydrodynamic analysis, he contributes innovative solutions to the growing demands of the offshore and marine industry 🚢🌍.

🔵 Awards and Honors

🥇 First rank – Best Graduate M.Sc. Students in Marine Engineering, Iranian Marine Industries Organization, 2022
🥈 Second rank – Top MSc Students in Marine Structure Engineering, 2019
🧠 Top 1% – MSc Entrance Exam of Universities, 2016
🎓 Top 10% – B.Sc. Students in Civil Engineering, 2013
🧠 Top 1% – University Entrance Exam, 2009
🎖️ Top 10 – High School Graduates, 2009

Publication Top Notes

Effects of soft marine fouling on wave-induced forces in floating aquaculture cages: Physical model testing under regular waves
- Journal: Ocean Engineering
- Date: October 2021
- DOI: 10.1016/j.oceaneng.2021.109759
- Focus: How soft biofouling (like algae and soft marine growth) changes the forces exerted on aquaculture cages when regular waves hit them, using physical model tests.
Hydrodynamic forces in marine-fouled floating aquaculture cages: Physical modelling under irregular waves
- Journal: Journal of Fluids and Structures
- Date: August 2021
- DOI: 10.1016/j.jfluidstructs.2021.103331
- Focus: Similar to above but testing under irregular waves (more realistic sea conditions), focusing on how fouling affects hydrodynamic forces.
Wave attenuation/build-up around and inside marine fouled floating aquaculture cages under regular wave regimes
- Journal: Journal of Ocean Engineering and Marine Energy
- Date: February 24, 2021
- DOI: 10.1007/s40722-021-00186-y
- Focus: Investigating wave energy behavior—whether it’s dampened (attenuated) or amplified (build-up)—around/inside fouled cages during regular waves.
Experimental Modelling of Biofouling Effects on the Regular and Irregular Waves Load in Aquaculture Cages
- Institution: K. N. Toosi University of Technology
- Type: Dissertation/Thesis
- Year: 2019
- DOI: 10.13140/RG.2.2.28208.48644
- Focus: The early foundational work by Farshad Nobakht-Kolur, focusing on both regular and irregular waves and their loading effects on biofouled cages, likely forming the base for the later journal papers.

Conclusion

Farshad Nobakht-Kolur demonstrates all the qualities of a promising and impactful researcher: scientific excellence, originality, practical application of research, international publication record, and community engagement.
In my opinion, he is a highly suitable and strong candidate for the Best Researcher Award — particularly within the fields of marine structures, offshore engineering, and renewable energy systems.

Ehsan Adibnia | Engineering | Best Academic Researcher Award

Published on 24/04/202524/04/2025 by Physicist Particle

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.

Ali Darvish Falehi | Engineering | Excellence in Researcher Award

Published on 19/04/202519/04/2025 by Physicist Particle

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:

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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

“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.
“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).
“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.
“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.
“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.

Guanqun Li | Engineering | Best Researcher Award

Published on 17/04/202517/04/2025 by Physicist Particle

Dr. Guanqun Li | Engineering | Best Researcher Award

Associate Researcher at Shengli oilfield, SINOPEC, China

Guanqun Li (李冠群), born in May 1994 in Shandong, China 🇨🇳, is an Associate Researcher at Shengli Oilfield Company, SINOPEC 🛢️. He earned his PhD in Oil and Gas Field Development Engineering from China University of Petroleum (East China) 🎓. His work focuses on the microscopic characterization of shale reservoirs and fluid dynamics in oil and gas systems 🔬💧. With numerous publications in top journals like Fuel and Physics of Fluids 📚, he brings innovation to shale oil recovery technologies. Passionate about fractal modeling and fluid imbibition research, Guanqun Li is contributing significantly to modern energy development ⚙️🌍.

Professional Profile:

Scopus

🔹 Education and Experience

🎓 Sep. 2016 – June 2019: Master’s in Oil and Gas Field Development Engineering, Yangtze University
📚 Sep. 2019 – June 2023: PhD in Oil and Gas Field Development Engineering, China University of Petroleum (East China)
🏢 July 2023 – Present: Associate Researcher, Shengli Oilfield Company, SINOPEC

🔹 Professional Development

Dr. Guanqun Li 📘 has shown consistent professional growth, moving from academic research to applied industry innovation. His academic journey through Yangtze University and the China University of Petroleum provided a solid foundation in oilfield development ⚒️. At SINOPEC, he applies his expertise in reservoir simulation, fracturing mechanics, and fluid flow modeling 🔬. He actively contributes to peer-reviewed journals and international conferences 🌍. Guanqun continuously develops novel analytical and fractal models for imbibition in shale formations 🌀. His cross-disciplinary collaboration and technical excellence are hallmarks of his evolving career in the energy sector 🚀.

🔹 Research Focus Category

Guanqun Li’s research centers on unconventional oil and gas recovery, specifically shale oil reservoir characterization and fluid imbibition mechanisms 🛢️💧. His work explores microscale fluid motion, fractal modeling, and productivity analysis in hydraulically fractured formations 🔍📈. He is especially interested in the spontaneous and forced imbibition processes in complex porous media under various boundary conditions 🧪. His models help optimize horizontal well performance and support enhanced oil recovery (EOR) strategies 🧠⚙️. With a clear focus on improving efficiency in volume fracturing and fluid migration mechanisms, his research is highly impactful in modern petroleum engineering 🚧.

🔹 Awards and Honors

🏅 Interpore Conference Presentation (2020) – Recognized for outstanding research on production enhancement in fractured wells
📖 Multiple First-Author Publications – Published in top journals like Fuel, Physics of Fluids, and Energy & Fuels
🧠 Acknowledged for Innovative Fractal Modeling – In spontaneous/forced imbibition in shale formations
🥇 Highly Cited Review Paper – On EOR techniques in shale oil (Geofluids, 2021)

Publication Top Notes

Title: Quantifying lithofacies-dependent imbibition behavior in continental shale oil by fractal modeling: A case study of the gentle slope fault zone, Jiyang DepressionAuthors: Li Guanqun, Peng Yanxia, Yang Yong, Cao Xiaopeng, Su YuliangJournal: Fuel
Year: 2025

Conclusion

Dr. Guanqun Li stands out as an emerging leader in petroleum reservoir engineering with clear scientific originality, engineering relevance, and a solid record of first-author publications in high-impact journals. His work has contributed meaningfully to advancing the understanding of shale oil imbibition mechanisms and their application in field operations.

Sahar Ghatrehsamani | Engineering | Best Scholar Award

Published on 01/04/202501/04/2025 by Physicist Particle

Dr. Sahar Ghatrehsamani | Engineering | Best Scholar Award

Postdoctoral at Isfahan University of Technology, Iran

Dr. Sahar Ghatrehsamani is a passionate mechanical engineer specializing in tribology, with a strong background in machine learning and surface engineering. She earned her Ph.D. in Mechanical Engineering from Isfahan University of Technology (IUT), Iran (2022) and is currently a postdoctoral researcher at IUT, applying AI techniques to predict the tribological behavior of agricultural machinery. With expertise in CAD, FEA, and statistical analysis, she has contributed significantly to teaching, research, and mentoring students. Her work intersects materials science, additive manufacturing, and precision agriculture, making her a versatile and innovative researcher. 🌍🔬

Professional Profile:

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Education & Experience

📚 Education:

🎓 Ph.D. in Mechanical Engineering (Tribology) – Isfahan University of Technology, Iran (2017-2022)
🎓 M.Sc. in Mechanical Engineering (Tribology) – Isfahan University of Technology, Iran (2015-2017)
🎓 B.Sc. in Mechanical Engineering (Biosystem) – Shahrekord University, Iran (2009-2013)

🔬 Experience:

🔍 Postdoctoral Researcher – Isfahan University of Technology, Iran (2024-Present)
👩‍🏫 Teaching Experience – Multiple undergraduate courses in mechanical engineering at IUT (2018-Present)
🤝 Co-Advisor – 2 Master’s & 6 Bachelor’s students

Professional Development

Dr. Sahar Ghatrehsamani is dedicated to research, teaching, and innovation in mechanical engineering, particularly in tribology, surface engineering, and AI-driven modeling. She has actively mentored students, guided research projects, and developed expertise in CAD, numerical simulation, and data analysis. Her teaching career at Isfahan University of Technology spans multiple engineering courses, and she has consistently ranked highly in teaching evaluations. Passionate about bridging the gap between mechanical engineering and materials science, she explores new technologies in additive manufacturing and precision agriculture to enhance sustainability and performance. 🚜🛠️

Research Focus

Dr. Sahar Ghatrehsamani’s research spans multiple engineering domains, focusing on:

🏎️ Tribology – Studying friction, wear, and lubrication for various applications
🏭 Surface Engineering – Enhancing material properties for durability and efficiency
🤖 Machine Learning & AI – Applying predictive modeling in tribological behavior and material design
🏗 Mechanical Behavior of Materials – Understanding stress, strain, and failure mechanics
🚜 Precision Agriculture – Developing efficient and smart agricultural machinery
🖨️ Additive Manufacturing – Investigating 3D printing & advanced manufacturing
📊 Data Analysis & Numerical Modeling – Integrating simulation techniques for engineering solutions

Awards & Honors

Teaching Excellence:

🎖️ Ranked 1st in Mechanical Engineering Group (2021)
🏅 Ranked 2nd in College of Engineering (2021)
🏆 Ranked 13th among 569 faculty members at IUT (2021)

Research Contributions:

📜 Published multiple high-impact research papers in tribology and AI modeling
🌍 Contributed to international collaborations in mechanical engineering research

🚀 Her dedication to education, research, and innovation has established her as a rising expert in tribology and machine learning!

Publication Top Notes

On the running-in nature of metallic tribo-components: A review
- Authors: M.M. Khonsari, S. Ghatrehsamani, S. Akbarzadeh
- Journal: Wear (Vol. 474, 2021)
- Citations: 113
- Summary: A comprehensive review of the running-in phase in metallic tribo-systems, examining the changes in friction, wear, and surface topography over time.
Experimentally verified prediction of friction coefficient and wear rate during running-in dry contact
- Authors: S. Ghatrehsamani, S. Akbarzadeh, M.M. Khonsari
- Journal: Tribology International (Vol. 170, 2022)
- Citations: 41
- Summary: Experimental validation of predictive models for friction and wear rate during the running-in phase under dry contact conditions.
Experimental and numerical study of the running-in wear coefficient during dry sliding contact
- Authors: S. Ghatrehsamani, S. Akbarzadeh, M.M. Khonsari
- Journal: Surface Topography: Metrology and Properties (Vol. 9, Issue 1, 2021)
- Citations: 25
- Summary: Investigates the wear coefficient during dry sliding contact using both experimental methods and numerical simulations.
Predicting the wear coefficient and friction coefficient in dry point contact using continuum damage mechanics
- Authors: S. Ghatrehsamani, S. Akbarzadeh
- Journal: Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology (2019)
- Citations: 23
- Summary: Develops a predictive framework for wear and friction coefficients in dry point contact using continuum damage mechanics.
Application of continuum damage mechanics to predict wear in systems subjected to variable loading
- Authors: S. Ghatrehsamani, S. Akbarzadeh, M.M. Khonsari
- Journal: Tribology Letters (Vol. 69, 2021)
- Citations: 15
- Summary: Extends continuum damage mechanics principles to predict wear in tribological systems under varying load conditions.

Conclusion

Sahar Ghatrehsamani is a strong candidate for the Best Scholar Award. Her contributions to tribology, AI-driven material predictions, and mechanical behavior research are significant. She excels in both academic and applied research, making notable interdisciplinary advancements. Given her teaching excellence, mentorship, and research output, she is highly deserving of recognition as a leading researcher in her field.