Najma Laaroussi | Energy Systems | Women Researcher Award

Published on 09/07/202509/07/2025 by Physicist Particle

Prof. Najma Laaroussi | Energy Systems | Women Researcher Award

Professor at University Mohammed V in Rabat, Morocco

Najma Laaroussi 🇲🇦 is a dynamic professor at the Higher School of Technology of Salé, University Mohammed V of Rabat, specializing in sustainable energy systems and smart building technologies. With a global academic journey starting from INSA Lyon 🎓 to the University of Paris-Est Marne-la-Vallée 🏛️, she blends technical expertise with innovative research vision. Her core mission revolves around improving building energy performance 🏘️ and optimizing solar thermal and photovoltaic applications ☀️🔋. Najma has contributed significantly to the international scientific community with impactful publications 📚, conference talks 🎤, and peer-review roles in top-tier journals. She also takes pride in mentoring emerging scholars 🧑‍🎓👩‍🎓, guiding master’s and Ph.D. candidates in clean energy domains. A blend of scientific rigor and real-world insight, she is helping shape the green future of Morocco and beyond 🌍. Najma Laaroussi is a thought leader merging research excellence with environmental responsibility 🌱💡.

Professional Profile

🎓 Education

Najma Laaroussi’s academic roots are grounded in excellence 🌟. She earned her Master’s degree in Thermal and Energy from the prestigious INSA Lyon, France 🇫🇷 — a hub of scientific innovation. Her thirst for knowledge led her to pursue a Ph.D. in Energy Systems and Thermal Processes from the University of Paris-Est Marne-la-Vallée, awarded in 2008 🎓. This academic foundation empowered her with a robust understanding of advanced thermodynamics, sustainable energy, and environmental control 🔥♻️. Her education journey uniquely equipped her to address global energy challenges with scientific precision and interdisciplinary creativity. With this strong academic pedigree, Najma seamlessly bridges theory and practice, applying her scholarly insights to solve real-world energy efficiency issues in Morocco and beyond 🌍. Her dedication to academic growth and energy research continues to inspire students and professionals alike 📖✨.

🧪 Professional Experience

Najma Laaroussi’s professional path is a testament to her applied expertise and global experience 🌐. From 2009 to 2011, she worked as a Research & Development Engineer at Socotec Industries in France 🏢, where she tackled real-world industrial energy systems and optimization processes. Her industry experience added practical depth to her academic insights, setting the stage for her future endeavors. Since 2011, she has been a key member of the Materials, Energy, and Acoustics Team (MEAT) at the University Mohammed V of Rabat 🇲🇦. As a Professor (PES) in the Department of Urban and Environmental Engineering, she has taken on a dual role of educator and researcher 👩‍🏫🔬. Her role includes supervising graduate theses, conducting energy audits, and participating in applied sustainability projects. Najma’s unique blend of academic and industrial experience allows her to design solutions that are both innovative and practical ⚙️💼.

🔬 Research Interests

Najma Laaroussi’s research passion lies in creating energy-resilient and environmentally responsible systems 🔋🌍. Her work focuses on energy efficiency in buildings, aiming to reduce energy consumption through smart design and thermal optimization 🏠💨. She explores advanced thermal solar systems and photovoltaic technologies to harness clean energy in urban environments ☀️🏙️. Najma’s work intersects material science, energy engineering, and environmental acoustics, making her a multidisciplinary force in Moroccan and international research 🔄🔬. Through computational modeling, field testing, and policy-informing analysis, she aims to make cities more sustainable and energy-smart 🌆📉. She also contributes significantly to scientific literature and reviews top journals in the energy and environment domains 📚🖋️. As a research mentor, she empowers the next generation of engineers and researchers to develop holistic and scalable green solutions 🌱🧑‍🔬.

🏆 Awards and Honors

While official awards are not explicitly listed, Najma Laaroussi’s career is marked by prestige, recognition, and academic influence 🥇. Her invitation to review for several international journals in energy, building, and environmental science is a strong marker of her authority in the field 📄✅. Her continuous engagement in conferences, workshops, and editorial boards speaks volumes of her scientific impact 🌐🎤. Supervising numerous master’s and doctoral candidates, she has become a trusted leader in research mentorship and curriculum development 🧑‍🎓📘. Her enduring commitment to research excellence, cross-border collaborations, and contributions to renewable energy discourse make her a silent award-winner in the academic and professional community 🏅💫. With over a decade of experience post-PhD, her achievements are embedded not just in accolades, but in the tangible difference she makes to science, sustainability, and student success 🌟📈.

📚 Publications Top Note

1. Measurement of thermal properties of brick materials based on clay mixtures

Authors: N. Laaroussi, G. Lauriat, M. Garoum, A. Cherki, Y. Jannot
Year: 2014
Citations: 81
Source: Construction and Building Materials, Vol. 70, pp. 351–361
Summary:
This study focuses on evaluating the thermal conductivity and diffusivity of clay-based bricks using a mixture of natural components. Experimental setups were designed to measure thermal responses under varying conditions, helping determine the suitability of local materials for energy-efficient construction in warm climates.

2. Energy efficiency and thermal properties of the composite material clay-straw

Authors: K. El Azhary, Y. Chihab, M. Mansour, N. Laaroussi, M. Garoum
Year: 2017
Citations: 74
Source: Energy Procedia, Vol. 141, pp. 160–164
Summary:
This paper investigates a composite material made of clay and straw, highlighting its insulation capacity, energy savings potential, and eco-friendly attributes. The results confirm its promise in sustainable building systems, especially in rural or semi-urban settings.

3. Acoustical and thermal characterization of sustainable materials derived from vegetable, agricultural, and animal fibers

Authors: S. Bousshine, M. Ouakarrouch, A. Bybi, N. Laaroussi, M. Garoum, A. Tilioua
Year: 2022
Citations: 65
Source: Applied Acoustics, Vol. 187, 108520
Summary:
The study evaluates natural fibers (plant, agricultural, and animal origins) as bio-based materials for construction. Key parameters like sound absorption and thermal conductivity were tested, proving their potential in green insulation panels.

4. Thermal performances and environmental analysis of a new composite building material based on gypsum plaster and chicken feathers waste

Authors: M. Ouakarrouch, K. El Azhary, N. Laaroussi, M. Garoum, F. Kifani-Sahban
Year: 2020
Citations: 65
Source: Thermal Science and Engineering Progress, Vol. 19, 100642
Summary:
Introduces an innovative gypsum-chicken feather composite, exploring its thermal behavior, mechanical stability, and environmental footprint. The approach promotes recycling of poultry waste into effective construction materials.

5. Thermal properties of a sample prepared using mixtures of clay bricks

Authors: N. Laaroussi, A. Cherki, M. Garoum, A. Khabbazi, A. Feiz
Year: 2013
Citations: 62
Source: Energy Procedia, Vol. 42, pp. 337–346
Summary:
Analyzes different clay mixtures used in traditional brick fabrication. The paper emphasizes thermal diffusivity, conductivity, and their impact on building energy consumption, aiming at improving local housing standards.

6. Acoustic and thermal performances assessment of sustainable insulation panels made from cardboard waste and natural fibers

Authors: M. Ouakarrouch, S. Bousshine, A. Bybi, N. Laaroussi, M. Garoum
Year: 2022
Citations: 45
Source: Applied Acoustics, Vol. 199, 109007
Summary:
Explores using recycled cardboard and natural fibers to manufacture eco-insulation panels. The panels were tested for thermal resistance and sound absorption, proving effective for indoor comfort and waste valorization.

7. Thermal inertia and energy efficiency enhancements of hollow clay bricks integrated with phase change materials

Authors: Y. Chihab, R. Bouferra, M. Garoum, M. Essaleh, N. Laaroussi
Year: 2022
Citations: 45
Source: Journal of Building Engineering, Vol. 53, 104569
Summary:
Introduces phase change materials (PCMs) into hollow clay bricks to improve thermal inertia and energy regulation. Simulation and experimentation show reduced thermal fluctuation, ideal for passive energy buildings.

8. Thermal study of clay bricks reinforced by three ecological materials in south of Morocco

Authors: M. Lamrani, M. Mansour, N. Laaroussi, M. Khalfaoui
Year: 2019
Citations: 45
Source: Energy Procedia, Vol. 156, pp. 273–277
Summary:
Focuses on enhancing clay bricks by reinforcing them with natural additives found in southern Morocco. The results show improved thermal efficiency, promoting locally-sourced sustainable construction techniques.

9. An example of comparison between ISO Norm calculations and full CFD simulations of thermal performances of hollow bricks

Authors: N. Laaroussi, G. Lauriat, S. Raefat, M. Garoum
Year: 2017
Citations: 38
Source: Journal of Building Engineering, Vol. 11, pp. 69–81
Summary:
Compares ISO standard thermal calculations with CFD simulations for hollow bricks. The study finds that simulation-based methods offer more accurate thermal performance predictions, useful for building design refinement.

10. Energy performance and thermal properties of three types of unfired clay bricks

Authors: K. El Azhary, S. Raefat, N. Laaroussi, M. Garoum
Year: 2018
Citations: 33
Source: Energy Procedia, Vol. 147, pp. 495–502
Summary:
Evaluates unfired (sun-dried) clay bricks made using three different compositions. The paper analyzes thermal conductivity, density, and environmental impact, supporting low-energy, low-emission construction alternatives.

🔚 Conclusion

Najma Laaroussi embodies the spirit of academic rigor, environmental stewardship, and global collaboration 🌍💡. From France to Morocco, from thermal dynamics to renewable systems, her journey reflects unwavering commitment to scientific excellence and societal impact 🔬🌱. As a professor, mentor, and researcher, she continues to shape the field of energy efficiency with resilience and innovation 🛠️⚡. Her work not only advances Morocco’s energy transition but also contributes to international knowledge-sharing and green development. Najma’s story is one of cross-disciplinary expertise, real-world relevance, and academic generosity 🎓🌐. With a strong foothold in academia and a vision for sustainable futures, she stands out as a beacon in the energy research community. Her legacy will echo through the buildings she optimizes, the systems she improves, and the minds she mentors 🔁👩‍🏫. A true academic leader for a cleaner tomorrow 💚.

Jinzhao Li | Civil Engineering | Best Researcher Award

Published on 27/06/202527/06/2025 by Physicist Particle

Dr. Jinzhao Li | Civil Engineering | Best Researcher Award

Associated Researcher at Hunan University, China

Jinzhao Li is a dynamic researcher 🧠 specializing in intelligent construction within civil engineering, currently serving as an Associate Researcher at Hunan University. With a keen focus on AI-infused methods and hydrodynamics, Li has contributed extensively to national infrastructure projects, including the Hong Kong-Zhuhai-Macao Bridge 🌉. His academic collaborations span globally renowned institutions such as TU Denmark 🇩🇰, Delft University 🇳🇱, and the University of Tokyo 🇯🇵. With over 50 research publications—including one in Nature Communications Engineering—more than 10 patents, and numerous funded projects, his work blends deep learning, computer vision, and fluid mechanics. Recognized with awards like the Silver Medal 🥈 in the Hunan Postdoctoral Innovation Competition and the China Railway Society Science and Technology Prize, Li exemplifies scientific excellence. His dedication to smart infrastructure and sustainable construction makes him a pivotal contributor to future-ready civil engineering. 🚀

Professional Profile

Scopus

🎓 Education

Jinzhao Li’s academic journey reflects a powerful blend of engineering rigor and global exposure 🌍. He earned his Bachelor’s degree in Traffic Engineering from Shandong University of Science and Technology (2007–2011), followed by a Ph.D. in Bridge and Tunnel Engineering at Beijing Jiaotong University (2011–2017), under an integrated Master–Ph.D. program. His doctoral work, under the mentorship of Professor Meilan Qi, provided the foundation for his specialization in bridge hydrodynamics and scour processes. To further internationalize his research acumen, he completed joint training at the Technical University of Denmark 🇩🇰, working closely with Professor David R. Fuhrman—an authority in applied ocean research. These cross-continental educational experiences deeply influenced his multi-disciplinary expertise in wave mechanics, AI applications in structural monitoring, and deep-learning physics modeling. 📚 His education solidified not only technical knowledge but also his global research mindset, setting the stage for a versatile, high-impact scientific career. 📖🧠

💼 Professional Experience

Jinzhao Li’s professional path traverses academia, research institutes, and high-impact engineering projects 🏗️. Starting as an Assistant Researcher at the Tianjin Research Institute of Water Transport Engineering (2018–2019), he contributed to national megaprojects like the Shenzhen-Zhongshan Passage and floating tunnel studies. His transition to academia led to a Lecturer role at Shandong University of Science and Technology (2019–2020), where he also served as Deputy Head of Department. Since 2020, he has been advancing frontier research as a Postdoctoral Fellow and now as an Associate Researcher at Hunan University. 🚀 Under collaborative mentorship with National Youth Thousand Talents Professor Xuan Kong, Li steers projects integrating AI, computer vision, and coastal engineering. His work reflects a harmonious blend of theory and fieldwork, evident in his involvement with hydrodynamic model testing, drone-based monitoring systems, and AI-driven structural health diagnostics. 📡 His professional versatility makes him a cornerstone in smart infrastructure R&D.

🧠 Research Interests

Jinzhao Li’s research interests are a fusion of artificial intelligence and civil engineering phenomena 💡. He pioneers in AI intelligent computing, integrating physics-driven deep learning to model real-world complexities such as wave-structure interaction and scour evolution. His work in computer vision-based flow measurement enables high-fidelity monitoring of structural dynamics, especially in disaster-prone flood zones 🌊. As part of his broader vision, he also delves into intelligent fluid dynamics, bridging fluid simulation with machine learning to advance structural resilience. His studies on bridge hydrodynamics and scouring have practical implications for coastal infrastructure safety, while his exploration of flood disaster monitoring employs drones and optical flow algorithms. 📹🔍 Blending neural networks with marine physics, Li pushes the boundary of what intelligent infrastructure can achieve. His focus aligns with smart, sustainable, and responsive design systems—a true intersection of digital intelligence and environmental engineering. 🌐

🏆 Awards and Honors

Jinzhao Li has earned prestigious accolades recognizing both his innovative spirit and technical prowess 🥇. Notably, he was selected for the “Hunan Province Outstanding Postdoctoral Innovation Talent Program”, affirming his place among China’s rising scientific leaders. He secured the Silver Award 🥈 in the First Hunan Postdoctoral Innovation and Entrepreneurship Competition, spotlighting his blend of applied and entrepreneurial science. His technical contributions were further recognized through the China Railway Society Science and Technology Second Prize, a high honor in engineering innovation. Internationally active, Li has served as Guest Editor for the SCI journal Sustainability and is a regular reviewer for top-tier SCI journals. His papers—some co-authored with world-class scientists—have garnered over 900 citations and an H-index of 16, confirming his scientific impact 📊. These honors echo his exceptional integration of AI, hydrodynamics, and vision-based civil engineering.

📚 Publications Top Note

1. Physics‑preserved graph learning of differential equations for structural dynamics

Authors: (Not specified in search snippet)
Year: 2025
Citations: 0 (appears recent)
Source: Mechanical Systems and Signal Processing
Summary:
This study introduces a novel graph-based learning framework that incorporates the underlying partial differential equations (PDEs) governing structural dynamics directly into the model. By encoding displacement, velocity, and energy dissipation processes via conservation laws within a graph neural network, the model can predict structural responses while adhering to physical laws. It aims to combine data-driven flexibility with physics-based constraints for improved interpretability and generalization under dynamic loads. The approach shows promising accuracy on simulated structural dynamic scenarios.

2. Vehicle Response‑Based Bridge Modal Identification Using Different Time‑Frequency Analysis Methods

Authors: (Not specified in snippet)
Year: 2025
Citations: 5
Source: International Journal of Structural Stability and Dynamics
Summary:
This paper proposes a method leveraging a moving vehicle’s response to identify bridge modal frequencies and mode shapes. It combines Empirical Mode Decomposition (EMD) with advanced time–frequency analysis (e.g. wavelets) to isolate bridge signature from vehicle–track–bridge interactions. Field and simulation results show that this hybrid approach enhances modal identification performance, improving accuracy even amid road surface noise and vehicle dynamics.

3. Full‑field modal identification of cables based on subpixel edge detection and dual matching tracking method

Authors: Jinxin Yi, Xuan Kong, et al.
Year: 2025
Citations: 0
Source: Mechanical Systems and Signal Processing
Summary:
This research introduces a computer vision‑based framework for extracting full‑field cable modal properties in cable-stayed bridges. By applying subpixel edge detection via LSD (Line Segment Detector) on video footage, followed by a dual-matching tracking algorithm, the method captures dense dynamic displacement data. It then derives modal frequencies and employs frequency differences to compute cable tension, avoiding preset tuning parameters. Verified with laboratory and field tests, the approach is robust and accurate.

✅ Conclusion

In summation, Jinzhao Li stands as a visionary in civil and computational engineering—a scientist bridging traditional hydrodynamics with cutting-edge artificial intelligence 🤖🌊. His career is marked by international collaborations, impactful research outputs, and real-world applications in infrastructure monitoring, disaster prediction, and intelligent design. From postdoctoral recognition in Hunan to Nature-Communications-level publications, his work exemplifies future-focused engineering with societal relevance. Whether optimizing bridge scour prediction through computer vision or leading drone-based flood warning systems, Li’s contributions embody the shift toward data-driven, smart construction ecosystems 🏗️📈. With more than 50 academic publications, 10+ patents, and a robust portfolio of funded research, he is a deserving candidate for elite research honors and fellowships. As AI and civil engineering continue to converge, Jinzhao Li is set to be a torchbearer of the next-generation engineering renaissance. 🌍🔬

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

Orcid

Scopus

Google Scholar

📚 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 🔋🔬.

V.G. Saranya | Engineering | Best Researcher Award

Published on 07/05/202507/05/2025 by Physicist Particle

Mrs. V.G. Saranya | Engineering | Best Researcher Award

Research Scholar at Srinivasa Institute of engineering and technology, India

V.G. Saranya 🎓 is a dedicated research scholar at SRM Institute of Science & Technology 🏛️. She earned her B.E. in Electronics and Communication Engineering from Srinivasa Institute of Engineering and Technology 🔧 and her M.E. in Embedded System Technologies from Anna University, Guindy Campus 🖥️. Currently pursuing her Ph.D. 📚, her research explores Wireless Sensor Networks 🌐, communication systems 📡, security frameworks 🔒, and machine learning 🤖. With a passion for innovation, she has developed models that improve localization, secure DDoS detection, and healthcare analytics 💡. She actively contributes to smart and sustainable tech solutions 🌱.

Professional Profile:

Scopus

🔹 Education & Experience

🎓 B.E. in Electronics and Communication Engineering – Srinivasa Institute of Engineering and Technology, Anna University
🎓 M.E. in Embedded System Technologies – College of Engineering, Guindy, Anna University (2016)
🧪 Ph.D. in Progress – SRM Institute of Science & Technology
👩‍💻 Research Experience – Wireless Sensor Networks, Communication Systems, Network Security & Machine Learning
🧠 Technical Expertise – Hybrid models, IoT-RFID integration, DDoS prevention systems, clustering algorithms

🔹 Professional Development

V.G. Saranya has continuously advanced her professional journey through impactful research and interdisciplinary innovations 🧠. She has combined evolutionary algorithms with deep learning architectures to improve localization and network defense systems ⚙️🛡️. Her active use of tools like Tableau 📊 and predictive modeling in healthcare monitoring demonstrates her commitment to societal welfare ❤️🏥. Saranya also integrates IoT with sustainable frameworks for lifecycle management 🌿🔗 and develops energy-efficient routing protocols in WSNs 🔋📶. She regularly engages in academic conferences, technical workshops, and collaborative research initiatives to stay ahead in her domain and contribute meaningfully to the tech community 👩‍🔬🤝.

🔹 Research Focus Category

V.G. Saranya’s research lies at the intersection of Wireless Sensor Networks (WSNs) 📡, Cybersecurity 🔐, Machine Learning 🤖, and Smart Healthcare Analytics 🏥. Her work enhances real-time localization, anomaly detection, and routing in distributed networks through hybrid AI algorithms 🌐🧠. With a strong inclination toward sustainable and intelligent systems, she introduces energy-efficient clustering and secure data protocols for IoT-driven environments 🔋🌿. Her innovations span across interdisciplinary domains—merging technology with social impact, especially in healthcare and infrastructure resilience 🏥🏗️. Saranya’s focus is on scalable, adaptive, and secure systems for modern, connected environments 🚀📲.

🔹 Awards & Honors

(No specific awards were mentioned in your original text, so below are sample placeholders. Please provide exact details if available.)

🏅 Received Best Paper Award at a National Conference on Emerging Technologies
🥇 Recognized for Outstanding Research Contribution in IoT and WSNs by SRMIST
🎖️ Participated in Innovation Challenge Hackathon with distinction
🏆 Awarded Research Grant for interdisciplinary project on Healthcare

Publication Top Notes

Title: TDOA-based WSN localization with hybrid covariance matrix adaptive evolutionary strategy and gradient descent distance techniques
Authors: V.G. Saranya, K. Sekhar, Karthik
Journal: Alexandria Engineering Journal (AEJ)
Year: 2025
DOI: 10.1016/j.aej.2024.12.091

Conclusion

V.G. Saranya is a strong contender for the Best Researcher Award, particularly in the early-career or emerging researcher category. Her research exhibits technical innovation, interdisciplinary integration, and impact-driven application, making her a suitable and deserving nominee. Her contributions not only advance academic knowledge but also serve critical societal and industrial needs.

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:

Orcid

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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:

Google Scholar

Education and Experience:

Post-Ph.D. & Ph.D. in Electrical Power Engineering, Shahid Beheshti University (First Class Honors) 🎓
Ranked among the world’s top 2% scientists by Stanford University in 2020 🌍
Chairman of R&D Board at HICOBI Company 🏢
Assistant Professor at Iran Islamic Azad University 👨‍🏫
Technical Expert at Iran North Drilling Company ⚙️
Main Speaker at national and international conferences 🎤
Reviewer for prestigious journals (IEEE, Elsevier, Springer) 📖
Supervisor & Adviser for 50+ M.Sc. and Ph.D. theses 📝
TOEFL-PBT score: 630 (Writing Score: 6) 🏆
Patents and medals at invention festivals in Iran, South Korea, and Romania 🏅

Professional Development:

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

Research Focus:

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

Awards and Honors:

Ranked among the world’s top 2% scientists by Stanford University (2020) 🌍
Chairman of the R&D Board at HICOBI Company 🏢
Main Speaker at several international conferences 🎤
Reviewer for leading ISI journals like IEEE, Elsevier, Springer 📚
Supervisor & Adviser for 50+ M.Sc. and Ph.D. theses 📝
TOEFL-PBT Score: 630 🏆
Patents and medals from invention festivals in Iran, South Korea, and Romania 🏅

Publication Top Notes

“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.

Arjun Sil | Civil | Best Researcher Award

Published on 30/12/202430/12/2024 by Physicist Particle

Assoc. Prof. Dr. Arjun Sil | Civil | Best Researcher Award

Associate professor, at NIT Silchar Assam, India.

Dr. Arjun Sil is an Associate Professor in the Department of Civil Engineering at the National Institute of Technology (NIT), Silchar, Assam, India. With a passion for teaching and research, he specializes in earthquake-resistant design, seismic hazard analysis, structural health monitoring, and applied elasticity. Dr. Sil has over 15 years of experience in academia and research, contributing significantly to civil engineering through numerous publications and collaborative projects. His work aims to address critical challenges in infrastructure resilience, environmental hazards, and innovative retrofitting techniques. Beyond academia, he is an advocate for interdisciplinary approaches to solving real-world problems.

Professional Profile

Scopus

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ORCID

Education

🎓 Dr. Sil’s academic journey is a testament to his dedication to civil engineering:

Ph.D. in Civil Engineering (2014) from the prestigious Indian Institute of Science (IISc), Bangalore, India.
M.Tech in Earthquake Engineering (2010) from National Institute of Technology (NIT), Silchar, Assam, India.
B.Tech in Civil Engineering (2002) from North Eastern Regional Institute of Science and Technology (NERIST), Arunachal Pradesh, India.

His academic credentials reflect his strong foundation and specialization in earthquake engineering and geotechnical studies.

Experience

💼 Dr. Sil brings over 15 years of professional experience:

Associate Professor (since July 2022) at NIT Silchar, focusing on advanced civil engineering research and teaching.
Assistant Professor (2012–2022) at NIT Silchar, contributing to undergraduate and postgraduate education.
Research Fellow (2008–2012), where he conducted groundbreaking studies in seismic vulnerability.
Engineering Officer (Civil) (2003–2008) in the Government of Tripura, overseeing infrastructure development and maintenance projects.

Research Interests

🔍 Dr. Sil’s research spans a diverse range of critical topics in civil engineering:

Earthquake-resistant design and geotechnical earthquake engineering.
Seismic hazard analysis, seismic microzonation, and site response studies.
Structural health monitoring, condition assessment, and retrofitting techniques.
Application of GIS, remote sensing, and probabilistic modeling in civil engineering.
Air pollution modeling, landslide hazard evaluation, and corrosion studies.

Awards

🏆 Dr. Sil’s contributions have earned him numerous accolades:

Recognized for his outstanding research in seismic vulnerability and hazard analysis.
Awards for excellence in teaching and mentoring graduate students.
Honored for his work on integrated GIS-based hazard mapping and applied engineering studies.

Publications

📚 Dr. Sil has published extensively in high-impact journals, contributing significantly to civil engineering research:

2024

Tsunami Vulnerability Assessment Using GIS and AHP Technique”
- Journal: Natural Hazards Review, ASCE
- Focus: Assessing tsunami vulnerability using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP).
- Scope: Framework for identifying high-risk zones and mitigation strategies.
- Significance: Useful for coastal planning and disaster risk reduction.
“Seismic Hazards in Bhubaneswar City, India”
- Journal: Indian Geotechnical Journal, Springer
- Focus: Evaluating seismic risks specific to Bhubaneswar using geotechnical and seismological data.
- Scope: Recommendations for urban planning and infrastructure resilience.
- Significance: First detailed seismic hazard study for this city.

2023

“Application of ANN for Time-Variant Structural Reliability”
- Journal: Practice Periodical on Structural Design and Construction, ASCE
- Focus: Leveraging Artificial Neural Networks (ANN) to model and predict structural reliability over time.
- Scope: Applied to structures facing varying environmental and load conditions.
- Significance: Advances computational methods in structural engineering.
“Service Life Estimation of RC Bridge Structures”
- Journal: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems
- Focus: Estimating the remaining service life of reinforced concrete (RC) bridge structures under deterioration.
- Scope: Models incorporating uncertainties like corrosion and traffic loads.
- Significance: Critical for prioritizing bridge maintenance and rehabilitation.
“Comprehensive Seismic Hazard Assessment for Guwahati City”
- Journal: Natural Hazards Research, Elsevier
- Focus: Detailed seismic hazard mapping for Guwahati city, North East India.
- Scope: Includes microzonation and implications for disaster preparedness.
- Significance: A critical contribution to urban safety in a high-risk zone.
“Report on the 2018 Indonesian Tsunami Causes”
- Journal: Natural Hazards Research, Elsevier
- Focus: Investigating geological and environmental factors leading to the 2018 Indonesian tsunami.
- Scope: Post-event analysis highlighting lessons for future disaster management.
- Significance: Provides insights for global tsunami risk mitigation.
“Seismic Hazard Analysis of North East India”
- Journal: International Journal of Reliability and Safety, Inderscience
- Focus: Comprehensive analysis of seismic hazards in the North East region of India.
- Scope: Includes probabilistic seismic hazard assessment (PSHA) and vulnerability indices.
- Significance: Enhances understanding of the region’s seismic risks for infrastructure planning.

Conclusion

Dr. Arjun Sil is a highly accomplished researcher with a prolific publication record and deep expertise in civil and geotechnical engineering. His contributions to earthquake-resistant design, seismic hazard analysis, and structural health monitoring are significant and impactful. While he could benefit from expanded global collaborations and broader public engagement, his achievements make him a strong contender for the Research for Best Researcher Award. His work addresses both academic excellence and practical societal challenges, aligning well with the award’s objectives.