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:

👩‍🎓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%.

🏢 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. Chopparapu’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.

 

 

Vito Errico | Meccanica | Best Researcher Award

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Dr. Vito Errico, Meccanica, Best Researcher Award

Doctorate at Politecnico di Bari Italy

Summary:

Dr. Vito Errico is a dedicated researcher in the field of mechanical engineering, specializing in additive manufacturing, materials science, and surface engineering. He completed his Ph.D. in Mechanical and Management Engineering from the Polytechnic University of Bari, Italy, with a focus on innovative solutions to enhance the quality of metallic components produced through additive manufacturing technologies.

Throughout his academic and professional journey, Dr. Errico has demonstrated a strong commitment to advancing knowledge and technology in mechanical engineering. He has held various research positions, including postdoctoral research fellowships, where he has contributed to projects aimed at optimizing additive manufacturing processes, developing high-performance coatings, and characterizing advanced materials for aerospace, automotive, and other engineering applications.

Professional Profile:

👩‍🎓Education:

Ph.D. in Mechanical and Management Engineering

  • Duration: November 2019 – March 2023
  • Institution: Polytechnic University of Bari, Italy

Master’s Degree (Second Level) in Mechanical Engineering

  • Duration: November 2016 – April 2019
  • Institution: Polytechnic University of Bari, Italy

Bachelor’s Degree (First Level) in Mechanical Engineering

  • Duration: October 2013 – November 2016
  • Institution: Polytechnic University of Bari, Italy

Professional Experience:

Dr. Vito Errico has extensive professional experience in the field of mechanical engineering, with a focus on additive manufacturing, materials science, and surface engineering. He has held various research positions, including postdoctoral research fellowships and collaborative projects with industry and academic institutions. Dr. Errico’s expertise lies in the optimization of innovative multi-material metallic parts produced through additive manufacturing techniques. He has contributed to projects aimed at developing high-performance coatings using additive technologies and has conducted in-depth studies on the micro and macrostructural characterization of components manufactured through Laser Metal Deposition (LMD) and Cold Spray (CS) processes. His research also involves the study and experimentation of advanced materials and manufacturing methods for applications in aerospace, automotive, and other engineering sectors. Through his interdisciplinary research endeavors, Dr. Errico has made significant contributions to advancing knowledge and technology in mechanical engineering, with a particular emphasis on enhancing the quality and performance of manufactured components.

Research Interest:

Additive Manufacturing: Investigating novel approaches and techniques to optimize the additive manufacturing process, including metal additive manufacturing (AM) and polymer-based AM, to enhance the quality, efficiency, and functionality of manufactured components.

Multi-Material Manufacturing: Exploring advanced methods for producing multi-material metallic parts using additive manufacturing technologies, with a particular emphasis on optimizing the performance and properties of these components for various applications.

Surface Engineering and Coatings: Studying the development and application of high-performance coatings and surface treatments using additive manufacturing methods, such as Laser Metal Deposition (LMD) and Cold Spray (CS), to improve wear resistance, corrosion resistance, and other surface properties.

Advanced Materials Characterization: Conducting comprehensive characterization studies to analyze the micro and macrostructural properties of materials manufactured through additive manufacturing processes, including the evaluation of mechanical, thermal, and chemical properties.

Process Monitoring and Optimization: Developing and implementing advanced monitoring and control systems for additive manufacturing processes, including optical and thermal monitoring techniques, to optimize process parameters and ensure the quality and consistency of manufactured components.

Applications in Aerospace and Automotive Industries: Exploring the application of additive manufacturing technologies in aerospace and automotive industries, including the development of lightweight and high-performance components, rapid prototyping, and customized manufacturing solutions.

Publications Top Noted: 

“Coaxial monitoring of AISI 316L thin walls fabricated by direct metal laser deposition”

  • Authors: V Errico, SL Campanelli, A Angelastro, M Dassisti, M Mazzarisi, …
  • Journal: Materials
  • Volume: 14
  • Issue: 3
  • Pages: 673
  • Year: 2021
  • Citations: 27

“On the feasibility of AISI 304 stainless steel laser welding with metal powder”

  • Authors: V Errico, SL Campanelli, A Angelastro, M Mazzarisi, G Casalino
  • Journal: Journal of Manufacturing Processes
  • Volume: 56
  • Pages: 96-105
  • Year: 2020
  • Citations: 27

“Effect of DED coating and DED+ Laser scanning on surface performance of L-PBF stainless steel parts”

  • Authors: V Errico, A Fusco, SL Campanelli
  • Journal: Surface and Coatings Technology
  • Volume: 429
  • Pages: 127965
  • Year: 2022
  • Citations: 21

“High resolution-optical tomography for in-process layerwise monitoring of a laser-powder bed fusion technology”

  • Authors: MG Guerra, V Errico, A Fusco, F Lavecchia, SL Campanelli, …
  • Journal: Additive Manufacturing
  • Volume: 55
  • Pages: 102850
  • Year: 2022
  • Citations: 18

“In-process dimensional and geometrical characterization of laser-powder bed fusion lattice structures through high-resolution optical tomography”

  • Authors: MG Guerra, M Lafirenza, V Errico, A Angelastro
  • Journal: Optics & Laser Technology
  • Volume: 162
  • Pages: 109252
  • Year: 2023
  • Citations: 12