Vaishnavee Rathod | Analysis | Best Researcher Award

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Ms. Vaishnavee Rathod | Analysis | Best Researcher Award

Research Scholar, Department of Computer Science Engineering SVNIT SURAT INDIA India

Vaishnavee Vijay Rathod is a Ph.D. candidate at SVNIT Surat, focusing on remote sensing and deep learning. She has earned her B.E., M.Tech., and is currently pursuing her Ph.D., with a specialized focus on satellite imaging, machine learning, and image processing. Vaishnavee has published multiple papers in renowned journals and conferences, contributing significantly to the fields of medical image analysis, remote sensing, and AI-based systems. She has also received recognition for her work, including the Best Paper Award at an international conference in 2020. Her innovative research on vehicle detection using computer vision and AI has gained attention in smart city development.

 

Publication Profile

Scopus Scholar

🎓 Education

Vaishnavee completed her B.E. in Electronics and Telecommunication in 2018 from Thakur College of Engineering and her M.Tech. in Electronics and Digital Image Processing from GHRIET Nagpur in 2020. She is currently pursuing a Ph.D. in Satellite Imaging and Deep Learning at SVNIT Surat, specializing in deep learning-driven satellite image classification. Throughout her academic journey, she has achieved distinction and published several research papers in prominent conferences and journals.

💼 Experience

Vaishnavee has significant experience as a research scholar in deep learning and image processing. Her Ph.D. research includes the development of models for satellite image analysis and AI-based vehicle detection systems using UAV data. She has contributed to over 10 publications, including SCI-indexed journals and prestigious conferences. Additionally, Vaishnavee has been a recipient of several project funding awards, including SSIP 2.0 funding for her “RoadMitra” AI-based system project, showcasing her expertise in smart city technologies.

🏆 Awards & Honors

Vaishnavee has been recognized for her research contributions, including the “Best Paper Award” at the International Conference on Engineering Systems Design and Optimization in 2020. She has received various honors, including funding under SSIP 2.0 for her smart city project “RoadMitra,” aimed at detecting road issues using UAVs. Additionally, she has won awards for her research excellence and has received numerous accolades for her participation in international conferences and workshops.

🔬 Research Focus

Vaishnavee’s research focuses on the intersection of satellite imaging, remote sensing, and deep learning. She works on developing deep learning models for efficient satellite image classification and vehicle detection systems using UAV technology. Her work also extends to image enhancement, biomedical image processing, and AI applications in smart city infrastructure. Vaishnavee’s research contributes to the development of innovative solutions for urban challenges, including road crack detection, traffic analysis, and the enhancement of healthcare technologies using AI.

Publication Top Notes

  • Title: Deep learning-driven UAV vision for automated road crack detection and classification
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G.
    • Journal: Nondestructive Testing and Evaluation (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: Road Crack Detection and Classification Using UAV and Deep Transfer Learning Optimization
    • Authors: Rathod, V., Rana, D., Mehta, R.
    • Journal: Journal of the Indian Society of Remote Sensing (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: A computer vision approach to vehicle detection, classification, and tracking from UAV data for Indian traffic analysis
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G., Nath, V.
    • Journal: IETE Journal of Research (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: An Extensive Review of Deep Learning Driven Remote Sensing Image Classification Models
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G.
    • Conference: Proceedings of the 2022 3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT 2022)
    • Citations: 4

 

Ronny Mabokela | NLP and AI | Best Researcher Award

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Mr. Ronny Mabokela | NLP and AI | Best Researcher Award

PHD at University of Johannesburg, South Africa

Koena Ronny Mabokela is a South African computer scientist with a diverse background in technology and education. Currently pursuing a PhD in Computer Science at the University of the Witwatersrand, he has built a career focused on speech technology, system integration, and tech innovation. With years of experience as an educator, lecturer, and researcher, he also holds a leadership role at the University of Johannesburg, where he serves as Acting Deputy Head of Department and Head of the Technopreneurship Centre. Koena is passionate about fostering technological advancements, particularly in education and enterprise systems.

Profile

Scholar

🎓 Education

Koena Ronny Mabokela holds a PhD in Computer Science from the University of the Witwatersrand (2020-2024). He earned a Master of Science in Computer Science with a focus on Speech Technology at the University of Limpopo (2012-2014). His academic journey includes a Bachelor of Science Honours in Computer Science (2011) and a Bachelor of Science in Computer Science and Mathematics (2008-2010), both from the University of Limpopo.

💼 Experience

Mabokela’s career spans various leadership and academic roles. He is currently the Acting Deputy HoD for CEPs/SLPs and Online at the University of Johannesburg. Previously, he served as the Head of the Technopreneurship Centre, managing strategy, projects, and research. He has taught various programming modules and supervised postgraduate students while conducting research and engaging in community development. His professional experience also includes roles at Vodacom and Telkom in business systems integration and product development.

🏆 Awards and Honors

Mabokela has received numerous accolades, including being a session chair for SATNAC 2014 and a peer reviewer for prestigious conferences like IEEE and SATANC. He has also contributed to the scientific community with his published research in areas such as sentiment analysis and AI for under-resourced languages. His leadership skills and contributions to innovation have been recognized throughout his academic and professional career.

🔬 Research Focus

Koena Mabokela’s research interests revolve around speech technology, AI, and multilingual sentiment analysis, particularly for under-resourced languages. He focuses on enhancing language identification and sentiment analysis systems for South African languages. His work includes exploring distant supervision approaches and applying AI to tackle social challenges, as seen in his published papers and presentations at international conferences. His research aims to bridge technological gaps in underrepresented languages and communities.

Conclusion

Koena Ronny Mabokela is an outstanding researcher with a diverse and impactful portfolio that bridges academia and industry. His extensive experience, leadership in academic development, and commitment to advancing knowledge in computer science and technology position him as a top candidate for the Best Researcher Award. While there are opportunities to expand his interdisciplinary work and enhance the practical impact of his research, his contributions to the academic community and the field of technology are significant. His future work promises to continue shaping the landscape of digital innovation and research.

Publications 📚

sofia aftab | Neural network | Best Researcher Award

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 Ms. sofia aftab | Neural network | Best Researcher Award

Ms. Norges Teknisk-Naturvitenskapelige Universitet, Norway

👩‍🔬 Highly experienced Data Scientist with expertise in research, data science, machine learning, advanced analytics, and Generative AI. Proficient in Python, SQL, SAS, Teradata, R, and QlikView. Possesses strong skills in business analysis, model building, and communication. Excels in statistical techniques, machine learning algorithms, deep learning frameworks, NLP, data engineering, and Generative AI. Experienced in agile project management and collaborative team environments.🌟

Profile

Scopus

 

 

Scholar

 

🎓📚Academics

  • MS (IT) specialization in Data Mining/Analytics from NUST
  • Ph.D (Machine Learning/Data Science) from NTNU

 

💼📊Career Skills/Knowledge

Over 12 years of experience as an enthusiastic Data Scientist Strong business analysis and data mining skills Expertise in model building and execution Proficient in segmentation and customer value management analytics Skilled in statistical techniques including regression, A/B testing, and statistical significance of ML models Experienced in machine learning algorithms such as NN, SVM, Naive Bayes, ensemble modeling, and deep learning (DNN)Knowledgeable in NLP techniques, data engineering, MLOps, and cloud deployments Experienced in Generative AI techniques including prompt engineering, Lang chain, and Semantic search Research-focused with experience in improving evaluation metrics and developing recommendation algorithms Proficient in agile project management methodologies

🏢💼Experience

Accenture-Norway (Aug 2022 – Present)Data Science Consultant/Team Lead Built and maintained data and ML pipelines Developed ML models and CI/CD workflows Collaborated with cross-functional teams Led agile projects and worked on Generative AI Telenor-Norway (Dec 2020 – Aug 2022)Data Scientist Evaluated and improved ML projects Transformed business questions into analysis Led agile projects and presented to management NTNU (Apr 2018 – 2020)Research Scientist Worked on Recommendation systems using deep learning Improved evaluation metrics for recommender systems HPE (May 2016 – 2018)Data Scientist (Consultant)Identified cross-sell and upsell opportunities Developed and maintained next best action engine Telenor (Aug 2015 – May 2016)Specialist Advance Analytics and Consumer Insight Conducted subscriber analysis and developed churn/retention framework Telenor (Aug 2013 – Aug 2015)Executive Advance Analytics and Consumer Insight Developed behavioral segmentation and churn prediction models Protégé Global (Aug 2012 – 2013)Team Lead Data Miner/Data Scientist Managed a team for data mining projects and conducted exploratory data analysis Muhammad Ali Jinnah University (MAJU) (2012 – 2013)Lecturer, Trainer National University of Science and Technology (NUST) (2011 – 2012)Research Assistant

Publications Top Notes 📝

  1. Title: Data Mining in Insurance Claims (DMICS) Two-way mining for extreme values
    • Authors: S Aftab, W Abbas, MM Bilal, T Hussain, M Shoaib, SH Mehmood
    • Conference: Eighth International Conference on Digital Information Management (ICDIM)
    • Year: 2013
    • Citations: 6

 

  1. Title: Evaluating top-n recommendations using ranked error approach: An empirical analysis
    • Authors: S Aftab, H Ramampiaro
    • Journal: IEEE Access
    • Volume: 10
    • Pages: 30832-30845
    • Year: 2022
    • Citations: 4

 

  1. Title: Improving top-N recommendations using batch approximation for weighted pair-wise loss
    • Authors: S Aftab, H Ramampiaro
    • Journal: Machine Learning with Applications
    • Volume: 15
    • Pages: 100520
    • Year: 2024

 

  1. Title: Deep Contextual Grid Triplet Network for Context-Aware Recommendation
    • Authors: S Aftab, H Ramampiaro, H Langseth, M Ruocco
    • Journal: IEEE Access
    • Year: 2023

 

  1. Title: Data Mining in Insurance Claims (DMICS)
    • Authors: S Aftab, W Abbass, MM Bilal, T Hussain, M Shoaib, SH Mehmood