SaiTeja Chopparapu | ECE | Best Paper Award

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Mr. SaiTeja Chopparapu | ECE | Best Paper Award

Assistant Professor at St. PETER’S Engineering College, India

Summary:

Mr. SaiTeja Chopparapu is an enthusiastic researcher and educator with expertise in electronics and communication engineering. With a solid academic background and hands-on experience in IoT, sensor systems, and image processing, he is committed to fostering innovation and critical thinking in the field. Known for his dedication and leadership skills, he aims to contribute to technological advancements and create an engaging learning environment for his students.

Professional Profile:

šŸ‘©ā€šŸŽ“Education:

Mr. SaiTeja Chopparapu is a dedicated researcher in Electronics and Communication Engineering, currently in the final stages of his Ph.D. at GITAM University, Visakhapatnam, where he submitted his thesis in October 2023. He earned an M.Tech in Sensor System Technology from Vellore Institute of Technology (VIT), Vellore, in 2019 with a CGPA of 8.49, building upon a B.Tech in Electronics and Communication Engineering from Dhanekula Institute of Engineering and Technology, JNTUK, in 2017. His foundational education includes an Intermediate in MPC from Sri Chaitanya Junior College, Kakinada, where he scored 88.4%, and an SSC from Ratnam High School, Dargamitta, with an aggregate of 84.67%.

šŸ¢ Professional Experience:

Mr. Chopparapu is currently an Assistant Professor at St. Peters Engineering College, JNTUH, where he has been teaching since February 2024. His courses include Digital Electronics, IoT Architecture and Protocols, and Image Processing. With a passion for hands-on education, he has served as a lab in-charge for B.Tech students, mentoring them in programming fundamentals and facilitating discussions to deepen their understanding. His research experience includes a 9-month internship at the Research Centre Imarat (RCI), DRDO, where he developed a GUI for a capacitance-to-voltage converter for capacitive-based sensors. He also completed a 30-day internship at Effectronics Pvt. Ltd., where he was involved in testing and analyzing signaling systems. Over his career, Mr. Chopparapu has participated in more than 40 faculty development programs, covering a variety of topics such as MATLAB, Python, IoT, and technical skill enhancement.

Research Interests:

Mr. Chopparapuā€™s research interests are centered on sensor systems, IoT, and embedded systems, with an emphasis on IoT architecture and image processing. His dedication to advancing electronics and communication engineering is evident in his academic pursuits, professional roles, and active involvement in technical conferences. He has also expressed a keen interest in developing automation technologies and vehicle control systems.

Top Noted Publication:

“A Hybrid Learning Framework for Multi-Modal Facial Prediction and Recognition Using Improvised Non-Linear SVM Classifier”

  • Authors: C. SaiTeja, J.B. Seventline
  • Journal: AIP Advances, Vol. 13, Issue 2, 2023
  • Citations: 9
  • Abstract: This study presents a hybrid framework that integrates multi-modal inputs to enhance the accuracy of facial prediction and recognition systems. The framework leverages an improvised non-linear Support Vector Machine (SVM) classifier, optimizing recognition rates through a synergistic use of varied input sources.

“An Efficient Multi-Modal Facial Gesture-Based Ensemble Classification and Reaction to Sound Framework for Large Video Sequences”

  • Authors: S.T. Chopparapu, J.B. Seventline
  • Journal: Engineering, Technology & Applied Science Research, Vol. 13, Issue 4, Pages 11263-11270, 2023
  • Citations: 5
  • Abstract: This paper introduces a multi-modal ensemble classification framework that combines facial gesture recognition with sound response mechanisms, specifically designed for extensive video sequences. The framework enhances real-time interactions, addressing performance demands in complex multimedia environments.

“Object Detection Using MATLAB, Scilab, and Python”

  • Authors: S. Chopparapu, B. Seventline
  • Journal: Technology, Vol. 11, Issue 6, Pages 101-108, 2020
  • Citations: 5
  • Abstract: This publication compares the efficacy of object detection across three platforms: MATLAB, Scilab, and Python. By analyzing detection rates, computational efficiency, and implementation complexity, the study provides insights into the adaptability of these platforms for real-time applications.

“GUI for Object Detection Using Voila Method in MATLAB”

  • Authors: S.T. Chopparapu, D.B. Seventline J
  • Journal: International Journal of Electrical Engineering and Technology, Vol. 11, Issue 4, 2020
  • Citations: 4
  • Abstract: This work introduces a graphical user interface (GUI) for object detection utilizing the Viola-Jones method in MATLAB. The study highlights the GUI’s design features, ease of use, and effectiveness for beginner-level applications in image processing.

“Enhancing Visual Perception in Real-Time: A Deep Reinforcement Learning Approach to Image Quality Improvement”

  • Authors: S.T. Chopparapu, G. Chopparapu, D. Vasagiri
  • Journal: Engineering, Technology & Applied Science Research, Vol. 14, Issue 3, Pages 14725-14731, 2024
  • Citations: 2
  • Abstract: This paper explores the use of deep reinforcement learning techniques for enhancing real-time image quality. The proposed approach aims to improve visual perception in dynamic environments, with potential applications in surveillance, autonomous vehicles, and other fields requiring high-quality image processing.

Conclusion:

Overall, Mr. SaiTeja Chopparapu presents a strong case for the Best Paper Award. His impactful publications, coupled with his practical experience in IoT and image processing, are aligned with the award’s objective to recognize innovative contributions in ECE. Addressing the suggested areas for improvement could help maximize the visibility and impact of his work in the field. With his impressive background and dedication, he is well-positioned as a competitive candidate for this award.

 

 

Daniel Mutia Mwendwa | Energy Systems | Best Researcher Award

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Mr. Daniel Mutia Mwendwa | Energy Systems | Best Researcher Award

Daniel Mutia Mwendwa at University of Oxford, United Kingdom

Summary:

Daniel Mutia Mwendwa is a Rhodes Scholar currently pursuing a DPhil in Engineering Science at the University of Oxford, where his research focuses on geospatial analysis of solar-powered irrigation systems in Sub-Saharan Africa. He holds an MSc in Energy Systems (Distinction) from Oxford and a BEng (First Class Honours) in Electronics and Electrical Engineering from the University of Edinburgh. Co-founder of BuniTek, he is dedicated to introducing technology to African youth. Daniel also works as a Research Assistant in the Climate Compatible Growth Programme, contributing to energy planning in Kenya and global green hydrogen initiatives.

Professional Profile:

šŸ‘©ā€šŸŽ“Education:

University of Oxford, UK (2023 ā€“ Present)
DPhil in Engineering Science (Rhodes Scholar)

  • Thesis Topic: Geospatial analysis of solar-powered irrigation in Sub-Saharan Africa, focusing on the water, energy, and food nexus.

University of Oxford, UK (2021 ā€“ 2022)
MSc in Energy Systems (Distinction, Rhodes Scholar)

  • Thesis: Developed a geospatial methodology for sizing and costing solar-powered irrigation systems for different crops.

University of Edinburgh, UK (2017 ā€“ 2021)
BEng (Hons) in Electronics and Electrical Engineering (First Class Honours, MasterCard Foundation Scholar)

  • Thesis: Developed an optimized hybrid energy storage system (HESS) combining battery storage, hydrogen fuel cells, and supercapacitors using MATLAB Simulink.

šŸ¢ Professional Experience:

Rhodes Trust, Oxford, UK (Mar 2024 ā€“ Present)
Rhodes Scholarship Ambassador for East Africa

  • Engages with universities across East Africa to introduce students to the Rhodes Scholarship and supports their application process.

University of Oxford, Oxford, UK (Mar 2022 ā€“ Present)
Research Assistant, Climate Compatible Growth Programme

  • Developed least-cost electrification pathways for Kenyan counties using the Open-Source Spatial Electrification Tool (OnSSET). Conducted capacity-building workshops on energy planning models like OSeMOSYS and IRENAā€™s Flextool. Also involved in geospatial modeling of green hydrogen production potential globally.

Loughborough University, Nairobi, Kenya (Nov 2022 ā€“ Present)
Research Consultant

  • Designed off-grid electrification solutions for poultry farming and health facilities. Authored academic papers on energy planning and developed funding proposals.

BuniTek, Nairobi, Kenya (Jun 2020 ā€“ Present)
Co-Founder

  • Co-founded BuniTek, an initiative that introduces technology concepts to African high school students in an engaging and hands-on manner. Led a team of 15 volunteers to develop 14 new courses.

Research Interests:

Daniel Mutia Mwendwa’s research interests lie in renewable energy systems, particularly in optimizing solar-powered irrigation and hybrid energy storage solutions. He is passionate about integrating geospatial modeling and energy planning to address sustainability challenges in Sub-Saharan Africa. His work also focuses on green hydrogen production, off-grid electrification, and the energy-water-food nexus.

Author Metrics:

Mwendwa has co-authored several research papers and reports, including:

  1. “Spatial Data Starter Kit for OnSSET Energy Planning in Kitui County, Kenya” – Published in Data in Brief (2022).
  2. “Mapping the Energy Planning Ecosystem in Kenya” – Published on GOV.UK (2023).
  3. “County Energy Planning Data Flows in Kenya: Practitioner Perspectives” – Published on GOV.UK (2023).

Top Noted Publication:

GIS-Based Method for Assessing the Viability of Solar-Powered Irrigation

  • Journal: Applied Energy
  • Publication Date: January 2025
  • DOI: 10.1016/j.apenergy.2024.124461
  • Contributors: Daniel Mutia Mwendwa, Alycia Leonard, Stephanie Hirmer
  • Summary: This paper presents a Geographic Information System (GIS)-based methodology for evaluating the feasibility of solar-powered irrigation systems. The method integrates spatial data with factors such as water availability, crop water demand, and solar energy potential to determine where solar-powered irrigation systems can be most effectively deployed in Sub-Saharan Africa.

Spatial Data Starter Kit for OnSSET Energy Planning in Kitui County, Kenya

  • Journal: Data in Brief
  • Publication Date: December 2022
  • DOI: 10.1016/j.dib.2022.108691
  • Contributors: Daniel Mutia Mwendwa, Jeffrey Tchouambe, Emily Hu, Micaela Flores Lanza, Andrea Babic Brener, Gyubin Hwang, Layla Khanfar, Alycia Leonard, Stephanie Hirmer, Malcolm McCulloch
  • Summary: This article provides a comprehensive spatial data kit designed for energy planning in Kitui County, Kenya. It is part of the Open-Source Spatial Electrification Tool (OnSSET) framework, which assists planners in developing least-cost electrification pathways. The dataset includes geographic and energy-related data to facilitate more efficient and accurate energy planning.

Xiaoxiao Huo | Electric Engineering | Best Researcher Award

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Ms. Xiaoxiao Huo | Electric Engineering | Best Researcher Award

Xiaoxiao Huo at Xiamen University, China

Summary:

Ms. Xiaoxiao Huo is a promising researcher in the field of electrical engineering, currently pursuing her master’s degree at Xiamen University, China. With a strong foundation in power electronics and control theory, she has engaged in various research projects focused on optimizing energy systems and improving power conversion techniques. Ms. Huo is an award-winning student, recognized for her academic excellence and contributions to both research and engineering competitions. She has published several papers on advanced control strategies and holds patents in image recognition technologies for meter reading. Her diverse academic and practical experiences position her as a future leader in energy system optimization and power management.

Professional Profile:

šŸ‘©ā€šŸŽ“Education:

Ms. Xiaoxiao Huo is currently pursuing her M.Eng. in Electrical Engineering at Xiamen University (2022-2025, expected), where she maintains a GPA of 3.6/4.0. She is under the supervision of Dr. Po Li (Xiamen University) and Dr. Zhengmao Li (Aalto University). Her primary coursework includes modern control theory, advanced power electronics, and numerical analysis. She completed her B.Eng. in Electrical Engineering and Automation from South China Agricultural University (SCAU) in 2022 with an average score of 90.91/100. Her undergraduate studies focused on power electronics technology, power system analysis, and electrical machinery theory.

šŸ¢ Professional Experience:

Throughout her academic journey, Ms. Huo has engaged in various research and professional roles. Currently, she is conducting research on multi-energy system planning and operation at Aalto University, where she is developing a planning and operation model for integrated energy systems. In addition, at Xiamen University, she is working on power conversion and energy management strategies for power systems, focusing on model predictive control and its applications. In 2022, Ms. Huo gained hands-on experience as an intern and research assistant at the Guangzhou Institute of Energy Testing, where she designed instrument verification methods using computer vision. She has also been an active volunteer with the Chinese Association of Automation (CAA) since 2021, contributing to academic promotion and conference organization. Her participation in robotics competitions, including the Robomaster visual team, further demonstrates her interest in AI and automation.

Research Interests:

Ms. Huoā€™s research interests lie in the areas of power electronics, control engineering, energy management, and hybrid energy storage systems. Her work focuses on model predictive control, model-free control, observer design, and hardware-in-the-loop (HIL) simulations. She has also contributed to projects involving grid-tied inverters, multi-energy systems, and the optimization of electric power conversion.

Author Metrics:

Ms. Huo has contributed to several significant publications in the fields of energy systems and power electronics. Some of her key works include:

  • Huo, X., & Li, P. (2024). Power Management and Control Strategy Based on Model-Free Control for Hybrid Energy Storage System. Accepted by 2024 9th International Conference on Power and Renewable Energy (ICPRE 2024).
  • Huo, X., & Li, P. Parameter-Free Ultralocal Model-Based Predictive Current Control for Three-Phase Four-Leg Inverters. Submitted to Electric Power Systems Research.
  • Zhang, Y., Huo, X., et al. (2023). Design of an Image Recognition Device for Electronic Water Meter Readings Based on Improved Threading Method. IEEE Chinese Automation Congress (CAC 2023).
  • She is also the co-author of two Chinese patents on image recognition methods for gas and water meter readings.

Top Noted Publication:

Simplified Finite Control Set Model Predictive Control for Single-Phase Grid-Tied Inverters with Twisted Parameters

  • Journal: Electric Power Systems Research
  • Publication Date: January 2025
  • DOI: 10.1016/j.epsr.2024.111063
  • Contributors: Po Li, Xiaoxiao Huo
  • Details: The paper discusses an advanced control method for single-phase grid-tied inverters with twisted parameters, focusing on reducing total harmonic distortion (THD).

Design of an Image Recognition Device for Electronic Water Meter Readings Based on Improved Threading Method

  • Conference: 2023 China Automation Congress (CAC)
  • Publication Date: November 17, 2023
  • DOI: 10.1109/cac59555.2023.10451216
  • Contributors: Yuanming Zhang, Qilun Lu, Xiaoxiao Huo, Yong Wan, Peng Tian
  • Details: This paper focuses on the design of a device utilizing image recognition technology for reading electronic water meters, improving accuracy through an enhanced threading method.

Total Harmonic Distortion Reduction Method of Improved Finite Control Set Model Predictive Control for Single-Phase Inverter with Twisted Parameter

  • Conference: 2023 5th International Conference on Power and Energy Technology (ICPET)
  • Publication Date: July 27, 2023
  • DOI: 10.1109/icpet59380.2023.10367520
  • Contributors: Po Li, Xiaoxiao Huo, Feng Guo
  • Details: This paper presents an improved control method for reducing THD in single-phase inverters with twisted parameters.

Multi-Sampling Rate Finite Control Set Model Predictive Control and Adaptive Method of Single-Phase Inverter

  • Journal: Electronics
  • Publication Date: June 27, 2023
  • DOI: 10.3390/electronics12132848
  • Contributors: Yunfeng She, Xiaoxiao Huo, Xiaoshan Tong, Chunjie Wang, Kunkun Fu
  • Details: The paper discusses multi-sampling rate model predictive control methods for single-phase inverters, including adaptive control to enhance performance.

Research on Quality Control Application of Whole Process Intelligent Manufacturing in Steel Industry 4.0 Based on Big Data Analysis

  • Journal: Journal of Network Intelligence
  • Publication Year: 2022
  • EID: 2-s2.0-85136270844
  • ISSN: 2414-8105
  • Contributors: Zhao, F., Yin, C., Huo, X., Xu, Y.
  • Details: This paper examines the application of big data analysis for quality control in Industry 4.0, focusing on intelligent manufacturing in the steel industry.