Dr. Divya Nimma | Machine Learning | Best Researcher Award
Doctorate at The University of Southern Mississippi, United States
Profiles
Early Academic Pursuits
Dr. Nimma’s academic journey began with a strong foundation in electronics and communication engineering, earning a Bachelor of Technology in Electronics and Communication Engineering from JNT University Hyderabad, India (2008–2012). Building on this, he advanced to earn a Master of Science in Computer and Information Science from Alcorn State University, USA (2015–2016), achieving an outstanding 3.81 GPA. His educational path culminated with a Ph.D. in Computational Sciences from The University of Southern Mississippi (2019–2023), where he secured a 3.71 GPA. Throughout these years, Dr. Nimma demonstrated a keen aptitude for computational sciences, particularly in the fields of image processing, computer vision, and machine learning, laying the groundwork for his significant contributions to the field.
Professional Endeavors
Dr. Nimma’s career trajectory has been marked by impactful roles in both industry and academia. Since August 2024, he has been working as a Python Developer at SVK Systems Inc. in Duluth, GA, where he develops software applications, manages APIs, optimizes databases, and collaborates with front-end developers. Previously, in 2024, Dr. Nimma contributed as a System Analyst at the University of Mississippi Medical Center (UMMC), where he worked extensively with data analysis, system software troubleshooting, and the management of clinical tools like REDCap and Ripple. These roles reflect his versatility, demonstrating his ability to work across various sectors, from healthcare to software development, with a focus on leveraging data and technical expertise to solve real-world problems.
Contributions and Research Focus
Dr. Nimma’s research focus has primarily been on the application of machine learning and vision transformers in the realms of computer vision and video recognition. His Ph.D. dissertation titled “IntelPVT and Opt-STViT: Advances in Vision Transformers for Object Detection, Classification, and Video Recognition” (2023) introduced two innovative approaches that have significantly advanced the field of visual data analysis. By enhancing object detection and classification through a flexible patching mechanism for Vision Transformers (ViTs) and reducing computational costs in video recognition via the Opt-STViT model, Dr. Nimma’s work has contributed to pushing the boundaries of efficiency and accuracy in machine learning models. This dissertation was advised by Dr. Zhaoxian Zhou and forms a key part of his growing academic and professional legacy.
Impact and Influence
Dr. Nimma’s contributions have not gone unnoticed, particularly in the fields of image processing, computer vision, and machine learning. His work has not only advanced theoretical knowledge but has also found practical applications in areas such as video recognition and cybersecurity. His research has demonstrated a commitment to improving algorithm efficiency, performance optimization, and data analysis, providing valuable insights into how these technologies can be used in a more resource-efficient manner. His achievements have earned him several accolades, including the Best Paper Award at the International Conference on Intelligent Computing and Sustainable Innovations in Technology (IC-SIT) in 2024 for his paper on “Enhancing Customer Churn Prediction in Telecommunication with CNN-Gradient Boosting Machine.”
Academic Citations
Dr. Nimma’s work has garnered attention in various academic and professional circles, underscoring his growing influence. His book, “Advancements in Artificial Intelligence in Computer Vision Applications” (2024), co-authored with R. Nimma and A. Uddagiri, delves into AI applications in computer vision and stands as a testament to his thought leadership in the field. His research publications and conference presentations further highlight his contributions to evolving technologies and methodologies, enriching the academic community’s understanding of these complex areas.
Teaching Experience
Although Dr. Nimma has not formally served as a faculty member, his experience extends to tutoring and mentoring students in various technical domains. His ability to convey complex concepts in machine learning and computational sciences makes him an invaluable resource to students and peers alike. His role as an Editorial Board Member and Reviewer for multiple international journals further highlights his commitment to the academic community and the dissemination of knowledge in the fields of engineering and technology.
Technical Skills
Dr. Nimma’s extensive technical toolkit includes expertise in a range of programming languages such as Python, C++, C#, and MATLAB, alongside proficiency in web technologies like HTML, CSS, and JavaScript. His experience spans across both frontend and backend development, and he is well-versed in SQL and MySQL for database management. Dr. Nimma has also developed a keen understanding of Salesforce administration and development, alongside his prowess in algorithm development, data analysis, and image processing techniques, making him a versatile professional capable of addressing challenges in multiple domains.
Legacy and Future Contributions
Dr. Nimma’s legacy is already evident in his research advancements, his leadership in shaping computational science through his reviewer roles and publications, and his ongoing work in machine learning and computer vision. Looking to the future, Dr. Nimma aims to continue expanding the boundaries of his research in artificial intelligence, image processing, and cybersecurity, with a focus on real-world applications that benefit both academic and industry sectors. His contributions are poised to have a long-lasting impact on future generations of scientists, engineers, and researchers who will build upon his work in the coming decades.
Publications
Logical reasoning for human activity recognition based on multisource data from wearable device
- Authors: Alsaadi, M., Keshta, I., Ramesh, J.V.N., Kiyosov, S., Soni, M.
- Journal: Scientific Reports
- Year: 2025
Privacy-preserving explainable AI enable federated learning-based denoising fingerprint recognition model
- Authors: Byeon, H., Seno, M.E., Nimma, D., Soni, M., Shabaz, M.
- Journal: Image and Vision Computing
- Year: 2025
Implications of climate change on freshwater ecosystems and their biodiversity
- Authors: Nimma, D., Devi, O.R., Laishram, B., Tirth, V., Arabil, A.
- Journal: Desalination and Water Treatment
- Year: 2025
IoT-Based Intelligent Energy Management for EV Charging Stations
- Authors: Dasi, S., Bondalapati, S.R., Subbaraju, M.P., Reddy, R.V.K., Zareena, N.
- Journal: IAENG International Journal of Computer Science
- Year: 2024
Correction to: IntelPVT: intelligent patch-based pyramid vision transformers for object detection and classification
- Authors: Nimma, D., Zhou, Z.
- Journal: International Journal of Machine Learning and Cybernetics
- Year: 2024