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.

 

 

Amarachi Madu | Automated Intelligence | Best Researcher Award

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Mrs. Amarachi Madu, Automated Intelligence, Best Researcher Award

Amarachi Madu at Virginia Tech, United States

Summary:

Mrs. Amarachi Madu is a Ph.D. candidate in Computer Science at Virginia Tech, with a strong background in mathematics and computer science. With a keen interest in artificial intelligence and its applications, she has conducted groundbreaking research in various domains including finance, healthcare, and human-computer interaction. With a Master’s degree from Austin Peay State University and a Bachelor’s degree from Nnamdi Azikiwe University, she brings a diverse skill set encompassing programming, data analytics, machine learning, and statistical analysis. Amarachi is passionate about leveraging cutting-edge technologies to address real-world challenges and improve human lives.

Professional Profile:

👩‍🎓Education:

Ph.D. in Computer Science

  • University: Virginia Tech, Blacksburg, VA
  • Duration: 8/2020 – Present
  • GPA: 3.93/4.0

Master of Science in Computer Science and Quantitative Methods

  • University: Austin Peay State University, Clarksville, TN
  • Duration: 8/2018 – 5/2020
  • GPA: 4.0/4.0

Bachelor of Science in Mathematics

  • University: Nnamdi Azikiwe University, Awka, Nigeria
  • Duration: 9/2010 – 9/2014
  • GPA: 4.72/5.0

Professional Experience:

Mrs. Amarachi Madu has accumulated a wealth of professional experience across various prestigious institutions and organizations:

As an AI Research Summer Associate at JPMorgan Chase & Co from June 2023 to August 2023, she conducted groundbreaking research in financial services, focusing on complex problems in the finance domain in collaboration with the natural language processing team.

Currently, she serves as a Graduate Research Assistant at Virginia Tech, Blacksburg, VA since January 2023, where she contributes to cutting-edge AI research.

Prior to her role at Virginia Tech, she was a Graduate Teaching Assistant at Virginia Tech from August 2020 to December 2022, where she played a key role in teaching information visualization, problem-solving in computer science, introduction to programming in Java, and data analytics and visualization.

Previously, she also worked as an AI Research Summer Associate at JPMorgan Chase & Co from June 2022 to August 2022, focusing on AI research in financial services, particularly collaborating with the natural language processing team on research problems in finance.

During her tenure as a Summer Extern at AT&T from July 2021 to August 2021, she underwent extensive training in various business and technical aspects to enhance personal and professional development.

Her journey in research began as a Graduate Research Assistant at Austin Peay State University, Clarksville, TN from August 2018 to May 2020, where she facilitated structured learning sessions for students and contributed to advancements in research, particularly in the application of linear multi-step methods and statistical analysis.

Through these roles, Mrs. Amarachi Madu has demonstrated her commitment to advancing knowledge in artificial intelligence, natural language processing, and related fields, while also gaining valuable experience in teaching, research, and industry collaboration.

Research Interest:

  • Artificial Intelligence
  • Natural Language Processing
  • Multi-modal Machine Learning
  • Medical Imaging
  • Human-Computer Interaction

Top Noted Publication:

Title: ChatGPT passing USMLE shines a spotlight on the flaws of medical education

  • Authors: AB Mbakwe, I Lourentzou, LA Celi, OJ Mechanic, A Dagan
  • Journal: PLOS Digital Health
  • Volume: 2
  • Issue: 2
  • Page: e0000205
  • Year: 2023

Title: Chexrelnet: An anatomy-aware model for tracking longitudinal relationships between chest x-rays

  • Authors: G Karwande, AB Mbakwe, JT Wu, LA Celi, M Moradi, I Lourentzou
  • Conference: International Conference on Medical Image Computing and Computer-Assisted
  • Year: 2022

Title: Fairness metrics for health AI: we have a long way to go

  • Authors: AB Mbakwe, I Lourentzou, LA Celi, JT Wu
  • Journal: EBioMedicine
  • Volume: 90
  • Page: 9
  • Year: 2023

Title: Enhancing mathematics achievement of introverted and extroverted secondary school students through the use of advance organizers

  • Authors: OE Chinelo, ON Francisca, MA Blessing
  • Journal: Journal of Educational Research and Reviews
  • Volume: 4
  • Issue: 3
  • Page: 27-32
  • Year: 2016