SaiTeja Chopparapu | ECE | Best Paper Award

Posted on by Best Paper Award

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.

 

 

Ritwik Maiti | Mechanical Engineering | Best Researcher Award

Posted on by Best Paper Award

Dr. Ritwik Maiti | Mechanical Engineering | Best Researcher Award

Assistant Professor at Birla Institute of Technology Mesra, India

Summary:

Dr. Ritwik Maiti is an accomplished researcher in the field of fluid dynamics and granular flow, with a particular emphasis on the behavior of granular materials in various contexts such as silos, open channels, and underground cavities. His work has contributed significantly to understanding the flow of granular media in natural and industrial processes. Dr. Maiti has held prestigious research positions at the National University of Singapore and the University of Sheffield, where he worked on projects ranging from wind-tunnel tests to flow modeling in porous media. He is currently contributing to the academic and research community at Birla Institute of Technology Mesra, where he continues his innovative research on granular flows and their interactions with fluid dynamics.

Professional Profile:

👩‍🎓Education:

Dr. Ritwik Maiti is an Assistant Professor in the Department of Mechanical Engineering at Birla Institute of Technology, Mesra, Ranchi. He earned his Ph.D. in Mechanical Engineering from the Indian Institute of Technology Kharagpur (2011–2017), where his research focused on the dynamics of dense granular flows through silos, closed channels, and open channels. Dr. Maiti holds a Master of Engineering (M.E.) in Heat Power Engineering from Jadavpur University, Kolkata (2009–2011), and a Bachelor of Technology (B.Tech) in Mechanical Engineering from Kalyani Government Engineering College, West Bengal (2008).

🏢 Professional Experience:

Dr. Maiti has extensive research experience in both mechanical and civil engineering. From 2018 to 2021, he was a Research Fellow with the Fluid Mechanics Research Group at the National University of Singapore, where he worked on projects related to wind-tree interaction and the minimization of granular mixture segregation. Prior to this, he was a Research Associate at the University of Sheffield (2017–2018), where he focused on modeling flow through porous granular media as part of the Geotechnical Engineering Research Group. His professional expertise includes the design and development of experimental fluid flow facilities and the handling of advanced equipment such as high-speed cameras, particle image velocimetry, and particle analyzers.

Research Interests:

Dr. Maiti’s research interests lie at the intersection of fluid mechanics and granular flow. His areas of focus include:

  • Experimental Fluid Dynamics
  • Granular Flow Dynamics
  • Geophysical Flows and Avalanches
  • Granular Mixing and Segregation
  • Fluid-Structure Interaction
  • Impact Crater Analysis
  • Underground Cavity Collapse
  • Multiphase Flows
  • Discrete Element Model (DEM)
  • Computational Fluid Dynamics (CFD) and CFD-DEM Coupling

He is also skilled in high-speed photography, image processing, and the use of software such as Matlab, Autocad, and LIGGGHTS for simulation and analysis.

Author Metrics:

Dr. Maiti has published numerous articles in international journals and conferences, including:

  • 10 publications in top-tier journals such as Physics of Fluids, Powder Technology, and AIChE Journal.
  • Contributions to leading conferences such as the International Conference on Fluid Mechanics and Fluid Power and the International Conference on Multiphase Flow.
  • A book chapter published by Springer in 2017.
  • Several research papers currently under review in journals like Powder Technology and Ocean Engineering.

Dr. Maiti’s research on granular dynamics has garnered significant attention in his field, contributing valuable insights into both theoretical models and practical applications.

Top Noted Publication:

Experiments on Eccentric Granular Discharge from a Quasi-Two-Dimensional Silo

  • Authors: R. Maiti, G. Das, P.K. Das
  • Journal: Powder Technology
  • Volume: 301
  • Pages: 1054-1066
  • Year: 2016
  • Citations: 35
  • Summary: This study presents experimental investigations on granular discharge from a quasi-two-dimensional silo with an eccentric outlet. The paper discusses the flow behavior, discharge rates, and the formation of patterns in the granular material as it exits the silo. The experiments provide a detailed understanding of the flow field dynamics during eccentric discharge.

Granular Drainage from a Quasi-2D Rectangular Silo through Two Orifices Symmetrically and Asymmetrically Placed at the Bottom

  • Authors: R. Maiti, G. Das, P.K. Das
  • Journal: Physics of Fluids
  • Volume: 29 (10)
  • Year: 2017
  • Citations: 25
  • Summary: This research explores the granular flow through a rectangular silo with two bottom orifices, placed both symmetrically and asymmetrically. The work examines how different placement configurations of the orifices affect the flow and drainage dynamics of granular materials, contributing valuable insights into granular discharge mechanics.

Flow Field During Eccentric Discharge from Quasi-Two-Dimensional Silos—Extension of the Kinematic Model with Validation

  • Authors: R. Maiti, S. Meena, P.K. Das, G. Das
  • Journal: AIChE Journal
  • Volume: 62 (5)
  • Pages: 1439-1453
  • Year: 2016
  • Citations: 19
  • Summary: This paper extends a kinematic model to describe the flow field during eccentric discharge from a quasi-2D silo. The study provides experimental validation of the model and offers insights into the flow patterns and velocity fields of granular materials, expanding the understanding of discharge processes in industrial and natural granular systems.

Cracking of Tar by Steam Reforming and Hydrogenation: An Equilibrium Model Development

  • Authors: R. Maiti, S. Ghosh, S. De
  • Journal: Biomass Conversion and Biorefinery
  • Volume: 3
  • Pages: 103-111
  • Year: 2013
  • Citations: 6
  • Summary: This paper focuses on developing an equilibrium model for tar cracking using steam reforming and hydrogenation. The study addresses the challenges associated with tar removal in biomass gasification and proposes a model to predict the outcomes of chemical reactions involved in the process.

Self-Organization of Granular Flow by Basal Friction Variation: Natural Jump, Moving Bore, and Flying Avalanche

  • Authors: R. Maiti, G. Das, P.K. Das
  • Journal: AIChE Journal
  • Volume: 69 (1)
  • Article: e17943
  • Year: 2023
  • Citations: 2
  • Summary: This recent study investigates the self-organization phenomena in granular flows due to variations in basal friction. The paper describes natural jumps, moving bores, and flying avalanches in granular media, providing key insights into the mechanics of granular flow and segregation.

Conclusion:

Dr. Ritwik Maiti’s contributions to fluid dynamics and granular flow research, particularly in areas like silo flows and porous media, make him a strong candidate for the Best Researcher Award. His published work demonstrates both depth and innovation in key fields of mechanical engineering, and his international experience enhances his profile. While expanding his research into more applied fields and taking on greater leadership roles could strengthen his application, his current contributions to science are exceptional, positioning him well for recognition in the field of mechanical engineering research.

 

E.Laxmi Lydia | Computer Science | Best Researcher Award

Posted on by Best Paper Award

Prof. E.Laxmi Lydia, Computer Science, Best Researcher Award

Professor at Velagapudi Ramakrishna Siddhartha Engineering College, Siddhartha Academy of Higher Education (SAHE), India

Summary:

Dr. E. Laxmi Lydia is a seasoned educator and researcher with over 20 years of experience in teaching, training, and research. Currently serving as a Professor and Dean of R&D at Vignan’s Institute of Information Technology, she has significantly contributed to the academic and research community. Dr. Lydia is recognized for her exceptional interpersonal skills, commitment to student development, and active involvement in curriculum design and institutional accreditation processes. Her extensive expertise and numerous accolades, including the Best Researcher Award for five consecutive years, highlight her dedication to advancing knowledge and fostering innovation in the field of computer science and engineering.

Professional Profile:

👩‍🎓Education:

Ph.D. in Computer Science and Engineering (Year not specified)

Master of Computer Applications (MCA) (Year not specified)

Bachelor of Science (B.Sc.) (Year not specified)

🏢 Professional Experience:

Professor & Dean of R&D Vignan’s Institute of Information Technology (A), July 2019 – Present
Dr. E. Laxmi Lydia leads the Research and Development department, overseeing various research initiatives and fostering collaborations both within and outside the institution. She plays an integral role in curriculum development and significantly contributes to the institution’s growth and academic excellence.

Associate Professor Vignan’s Institute of Information Technology (A), 2015 – 2019
In her tenure as an Associate Professor, Dr. Lydia taught both undergraduate and postgraduate courses, guided numerous research projects, and actively participated in various academic committees. Her efforts were pivotal in advancing the research capabilities and academic standards of the institution.

Associate Professor Raghu Engineering College, 2011 – 2015
At Raghu Engineering College, Dr. Lydia conducted lectures, supervised research activities, and contributed significantly to the academic community through her publications and participation in conferences. Her work helped in elevating the research profile and educational quality of the college.

Assistant Professor Ravindra and Rajendra PG College for MCA, 2003 – 2009
During her tenure as an Assistant Professor, Dr. Lydia was responsible for teaching MCA students, developing comprehensive course materials, and mentoring students. Her dedication to teaching and mentorship helped shape the careers of many students in the field of computer science and engineering.

Honors & Certifications:

  • Oracle Certified (2009)
  • Microsoft Certified Solution Developer (MCSD)
  • Outcome-Based Education (OBE) Certified
  • Engineering Education Certification
  • EPICS-Engineering Projects in Community Services Certified
  • Reviewer for JEET Scopus Journal
  • Best Researcher Award (2018, 2019, 2020, 2021, 2022) at Vignan’s Institute of Information Technology
  • Distinguished Faculty in CSE-2021 by Ambitions, an educational entity

Professional Affiliations:

  • Member of the Board of Studies (BOS) at Vignan’s Institute of Information Technology
  • Member of the International Accreditation Council of Quality Education & Research (IACQER)
  • Member of the Computer Society of India

Research Interests:

Dr. Lydia’s research interests encompass a wide range of topics within computer science and engineering, including but not limited to:

  • Artificial Intelligence and Machine Learning
  • Data Science and Big Data Analytics
  • Cybersecurity and Information Assurance
  • Software Engineering and Development
  • Internet of Things (IoT) and Smart Systems

Top Noted Publication:

An Optimal Least Square Support Vector Machine Based Earnings Prediction of Blockchain Financial Products

  • Authors: M Sivaram, EL Lydia, IV Pustokhina, DA Pustokhin, M Elhoseny, GP Joshi
  • Journal: IEEE Access
  • Volume: 8
  • Pages: 120321-120330
  • Year: 2020
  • Citations: 97

Concept of Electronic Document Management System (EDMS) as an Efficient Tool for Storing Document

  • Authors: ATR Rosa, IV Pustokhina, EL Lydia, K Shankar, M Huda
  • Journal: Journal of Critical Reviews
  • Volume: 6
  • Issue: 5
  • Pages: 85-90
  • Year: 2019
  • Citations: 91

Synergic Deep Learning Model–Based Automated Detection and Classification of Brain Intracranial Hemorrhage Images in Wearable Networks

  • Author: EL Lydia
  • Journal: Personal and Ubiquitous Computing
  • Year: 2022
  • Citations: 90

Optimal Deep Learning Based Image Compression Technique for Data Transmission on Industrial Internet of Things Applications

  • Authors: B Sujitha, VS Parvathy, EL Lydia, P Rani, Z Polkowski, K Shankar
  • Journal: Transactions on Emerging Telecommunications Technologies
  • Volume: 32
  • Issue: 7
  • Article: e3976
  • Year: 2021
  • Citations: 84

Data Encryption for Internet of Things Applications Based on Catalan Objects and Two Combinatorial Structures

  • Authors: MH Saračević, SZ Adamović, VA Miškovic, M Elhoseny, ND Maček, EL Lydia
  • Journal: IEEE Transactions on Reliability
  • Volume: 70
  • Issue: 2
  • Pages: 819-830
  • Year: 2020
  • Citations: 83