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.

 

 

Sumei Li | Neural Network | Best Researcher Award

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Assoc Prof Dr. Sumei Li | Neural Network | Best Researcher Award

Associate Professor at Tianjin University, China
Summary:

Assoc Prof Dr. Sumei Li is a distinguished researcher in the field of communication engineering, with a focus on advancing technologies for image and video processing. With over 37 published papers in prestigious journals and numerous contributions to leading international conferences, Dr. Li is at the forefront of her field. She has also filed 20 invention patents, demonstrating her commitment to innovation and excellence in research. Her collaborations with renowned institutions and experts, such as Wei Xiang, highlight her dedication to fostering interdisciplinary research.

Professional Profile:

👩‍🎓Education:

Ph.D. in Communication Engineering
Nankai University, Tianjin, China

🏢 Professional Experience:

Assoc Prof Dr. Sumei Li has been an Associate Professor in the Communication Engineering Department at Tianjin University since 2006. She has successfully chaired a national 863 project, a National Natural Science Foundation project, and a key fund in Tianjin, underscoring her leadership in the field. Her contributions to academia include significant research and innovations in 3D image and video processing, quality evaluation, and stereo image super-resolution reconstruction.

Research Interests:

Dr. Li’s primary research interests include:

  • 3D image and video processing
  • Quality evaluation
  • Stereo/image super-resolution reconstruction
  • Neural networks
  • Deep learning

Author Metrics:

  • Total Published Papers: 37
  • Citations: 1,791
  • Patents Published/Under Process: 20

Top Noted Publication:

1. Multi-Scale Visual Perception Based Progressive Feature Interaction Network for Stereo Image Super-Resolution

Authors: Liu, A., Li, S., Chang, Y., Hou, Y.
Journal: IEEE Transactions on Circuits and Systems for Video Technology
Year: 2024
Volume: 34
Issue: 3
Pages: 1615–1626
Citations: 1

2. Bidirectional Feature Aggregation Network for Stereo Image Quality Assessment Considering Parallax Attention-Based Binocular Fusion

Authors: Chang, Y., Li, S., Liu, A., Jin, J., Xiang, W.
Journal: IEEE Transactions on Broadcasting
Year: 2024
Volume: 70
Issue: 1
Pages: 278–289
Citations: 1

3. Coarse-to-Fine Cross-View Interaction Based Accurate Stereo Image Super-Resolution Network

Authors: Liu, A., Li, S., Chang, Y., Zhang, W., Hou, Y.
Journal: IEEE Transactions on Multimedia
Year: 2024
Volume: 26
Pages: 7321–7334
Citations: 2

4. Cross-Resolution Feature Attention Network for Image Super-Resolution

Authors: Liu, A., Li, S., Chang, Y.
Journal: Visual Computer
Year: 2023
Volume: 39
Issue: 9
Pages: 3837–3849
Citations: 3

5. No Reference Stereoscopic Video Quality Assessment Considering Self-Attention and Different Resolution Level

Authors: Zhang, X., Li, S.
Conference: ACM International Conference Proceeding Series
Year: 2023
Pages: 36–41

Conclusion:

Assoc Prof Dr. Sumei Li is a highly qualified candidate for the Best Researcher Award, given her extensive publication record, innovative contributions to communication engineering, and leadership in significant research projects. Her dedication to advancing image and video processing technologies, coupled with her emphasis on neural networks and deep learning, showcases her as a pivotal figure in her field. By addressing areas for improvement, such as broadening her research scope and increasing public engagement, Dr. Li can further amplify her impact on both academia and industry. Overall, her commitment to research excellence and innovation makes her a deserving contender for this prestigious award.