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

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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 🔋🔬.

Jian-Fei Sun | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Jian-Fei Sun | Engineering | Best Researcher Award

Assoc. Prof. Dr Jian-Fei Sun, Qingdao University of Technology, China

Dr. Jian-Fei Sun is an Associate Professor at Qingdao University of Technology, specializing in chemical engineering with a focus on green solvent technology and chemical equipment. His research has led to several SCI/EI publications and collaborations with industry, advancing environmentally sustainable solutions in chemical processes.

PROFILE

Orcid Profile

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Educational Details

Assoc. Prof. Dr. Jian-Fei Sun completed his Bachelor’s degree at Shandong Normal University in 2016, followed by a Master’s degree from Inner Mongolia University of Technology in 2019. He earned his Ph.D. from Dalian University of Technology in 2023, showcasing a solid academic progression in engineering and chemical sciences. As of September 2024, Dr. Sun is a post-doctoral researcher and visiting scholar in the Department of Chemical Engineering at Qingdao University of Science and Technology.

Professional Experience

Dr. Sun is an Associate Professor at the School of Mechanical and Automotive Engineering, Qingdao University of Technology, where he has developed expertise in gas adsorption, green solvents, and chemical process equipment. His collaborations extend to the Chinese Chemical Society and the China Occupational Safety and Health Association, where he is an active member.

Research Interest

Thermodynamics and Applications of Green Solvents: Involving supercritical and CO2-expanded liquids, critical for eco-friendly chemical processes.

Nanomaterial Synthesis and Catalysis: Focused on catalytic conversion and pretreatment of biomass.

Chemical Engineering Equipment Design: Including innovations in vaporization, heat exchange, and coating processes.

Research Innovations

Dr. Sun’s research is pioneering in green solvent technology, encompassing supercritical fluids, CO2-expanded liquids, and ionic liquids. His work emphasizes the synthesis of nanomaterials, catalytic conversion of lignocellulosic biomass, and advanced chemical engineering equipment design. Notable projects include submerged combustion vaporizers, heat exchangers, jet cavitation cleaning, and supercritical cleaning technologies.

Top Notable Publications

Chen, X., Sun, J., Yu, K., Wu, J., & Yin, J. (2024). Design of novel bracket structure for falling film devolatilizer and numerical simulation of its film-forming property. Chemical Engineering Journal, 499, 156317.

Citations: 0

Sun, J., Yu, K., Zhou, D., Sun, H., & Wu, J. (2024). Continuous process for CO2 cycloaddition reaction in a fixed bed reactor: Kinetic model of reaction transport. Chemical Engineering Science, 283, 119415.

Citations: 2

Zhou, D., Sun, J., Xue, M., Xu, Q., & Yin, J. (2024). Imidazole based ionic liquid grafted graphene for enhancing the new green conversion process of carbon dioxide. Journal of Cleaner Production, 434, 140083.

Citations: 5

Sun, H., Qi, J., Sun, J., Wu, J., & Yin, J. (2024). Solubility of iron(III) and nickel(II) acetylacetonates in supercritical carbon dioxide. Chinese Journal of Chemical Engineering, 65, 29–34.

Citations: 0

Chen, X., Sun, J., Wu, J., Zhang, Y., & Yin, J. (2023). Simulation study on mass transfer characteristics and disk structure optimization of a rotating disk reactor with high viscosity region. Journal of Applied Polymer Science, 140(48), e54717.

Citations: 1

Chen, X., Wu, J., Sun, J., Yu, K., & Yin, J. (2023). Numerical investigation of film-forming characteristics and mass transfer enhancement in horizontal polycondensation kettle. Chinese Journal of Chemical Engineering, 63, 31–42.

Citations: 0

Li, X., Sun, J., Xue, M., Wu, J., & Yin, J. (2023). The imidazole ionic liquid was chemically grafted on SBA-15 to continuously catalyze carbon dioxide to prepare propylene carbonate. Journal of Environmental Chemical Engineering, 11(5), 110438.

Citations: 9

Sun, J.-F., Chen, X.-P., Li, X.-T., Li, L., & Yin, J.-Z. (2023). Theoretical study of supported ionic liquid membrane reaction and transport for CO2 cycloaddition reaction. Chemical Engineering Journal, 470, 144299.

Citations: 2

Yu, K., Liu, J., Sun, J., Shen, Z., & Yin, J. (2023). Study of polyester degradation by sub/supercritical ethanol and enhancement of carbon dioxide. Journal of Supercritical Fluids, 194, 105837.

Citations: 7

Conclusion

Dr. Sun has published numerous SCI and EI-indexed papers and collaborated with chemical enterprises to secure research funding. His contributions emphasize his dedication to both academic excellence and real-world applications, reinforcing his suitability for the Best Researcher Award through innovation and impactful research in sustainable chemical processes.

 

 

 

Sowon Choi | Engineering | Women Researcher Award

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Dr. Sowon Choi | Engineering | Women Researcher Award

Dr. Sowon  Choi, Pohang University of Science and Technology, South Korea

Dr. sowon choi is a research professor at the Graduate Institute of Ferrous and Eco Materials Technology (GIFT) at Pohang University of Science and Technology (POSTECH), South Korea. Her research integrates data-driven project management methodologies through artificial intelligence (AI) and unstructured text data analysis, particularly within big data environments. Dr. choi’s work is grounded in her comprehensive experience in both onshore and offshore EPC (Engineering, Procurement, and Construction) projects, with specialized expertise in contract negotiation and project management. Her academic focus is complemented by a solid background in strategic management, planning, and marketing.

PROFILE

Orcid Profile

Educational Details

Ph.D. in Plant System Engineering (PSE), POSTECH, 2022

Master of Science in Plant System Engineering (PSE), POSTECH, 2015

Bachelor of Commerce, Double Major in Marketing & International Business, University of Auckland, 2005

Professional Experience

Dr. choi has a diverse professional background, which spans across various industries and roles. She currently serves as a research professor and postdoctoral research fellow at POSTECH, a position she has held since 2022. Before this, Dr. choi held leadership roles in prominent South Korean companies. From 2012 to 2016, she was Principal Manager at Taekyung Heavy Industries Co., Ltd., where she played a key role in managing large-scale projects. Additionally, she has experience as a Principal Consultant with Korea PMI Consulting Group and as a Principal Researcher with Korea Marketing and Retailing Consulting. Early in her career, Dr. choi worked as an Assistant Manager at Paris Croissant Co., Ltd.

Research Interest

 

AI-driven project management and analysis of unstructured text data

Big data applications in EPC project management

Strategic and marketing planning within the engineering and technology sectors

Top Notable Publications

Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications

Authors: To be determined

Journal: Sustainability

Date: 2024-03-27

DOI: 10.3390/su16072770

Development of Cycloid-Shaped Roll Charging Chute for Sintering Process for Energy Decarbonization and Productivity Improvement in Steel Plants

Authors: To be determined

Journal: Energies

Date: 2024-03-23

DOI: 10.3390/en17071536

Prediction Modeling of Flue Gas Control for Combustion Efficiency Optimization for Steel Mill Power Plant Boilers Based on Partial Least Squares Regression (PLSR)

Authors: To be determined

Journal: Energies

Date: 2023-09-30

DOI: 10.3390/en16196907

A Question-Answering Model Based on Knowledge Graphs for the General Provisions of Equipment Purchase Orders for Steel Plants Maintenance

Authors: To be determined

Journal: Electronics

Date: 2023-06-01

DOI: 10.3390/electronics12112504

Modeling of Predictive Maintenance Systems for Laser-Welders in Continuous Galvanizing Lines Based on Machine Learning with Welder Control Data

Authors: To be determined

Journal: Sustainability

Date: 2023-05-07

DOI: 10.3390/su15097676

A Prediction Model for Spot LNG Prices Based on Machine Learning Algorithms to Reduce Fluctuation Risks in Purchasing Prices

Authors: To be determined

Journal: Energies

Date: 2023-05

DOI: 10.3390/en16114271

Machine Learning-Based Tap Temperature Prediction and Control for Optimized Power Consumption in Stainless Electric Arc Furnaces (EAF) of Steel Plants

Authors: To be determined

Journal: Sustainability

Date: 2023-04-08

DOI: 10.3390/su15086393

Knowledge Retrieval Model Based on a Graph Database for Semantic Search in Equipment Purchase Order Specifications for Steel Plants

Authors: To be determined

Journal: Sustainability

Date: 2023-04-06

DOI: 10.3390/su15076319

An AI-Based Automatic Risks Detection Solution for Plant Owner’s Technical Requirements in Equipment Purchase Order

Authors: To be determined

Journal: Sustainability

Date: 2022-08-12

DOI: 10.3390/su141610010

Contractor’s Risk Analysis of Engineering Procurement and Construction (EPC) Contracts Using Ontological Semantic Model and Bi-Long Short-Term Memory (LSTM) Technology

Authors: To be determined

Journal: Sustainability

Date: 2022-06-06

DOI: 10.3390/su14116938

The Engineering Machine-Learning Automation Platform (EMAP): A Big-Data-Driven AI Tool for Contractors’ Sustainable Management Solutions for Plant Projects

Authors: To be determined

Journal: Sustainability

Date: 2021-09

DOI: 10.3390/su131810384

AI and Text-Mining Applications for Analyzing Contractor’s Risk in Invitation to Bid (ITB) and Contracts for Engineering Procurement and Construction (EPC) Projects

Authors: So Won Choi (and additional authors as listed in the article)

Journal: Energies

Date: 2021-07-30

DOI: 10.3390/en14154632

Conclusion

Dr. Sowon Choi’s extensive background in data analysis, project management, and strategic planning, combined with her advanced research in AI and EPC projects, makes her an exemplary candidate for the Best Researcher Award. Her innovative work aligns closely with the award criteria, addressing sustainability, efficiency, and technological advancement in project management. Given her diverse experience and strong academic foundation, she demonstrates a well-rounded expertise that positions her as a compelling candidate for this honor.