Madhavi Tota | Computer Science | Best Researcher Award

Published on by Best Achievements

Mrs. Madhavi Tota | Computer Science | Best Researcher Award

Mrs. Madhavi Tota, G H Raisoni,  India.

Mrs. Madhavi Srinivas Sadu, Assistant Professor (Senior Grade) in the Department of Computer Science and Engineering, has over 18 years of teaching experience and a strong academic background in machine learning, big data security, and information privacy. She has authored 28 publications, including 12 international journal papers and 3 book chapters, and holds professional memberships in ISTE, IE, and INSC. Her research focuses on privacy-preserving methods and technological innovation, making her a significant contributor to the academic community.

Profile

ORCID ID

Early Academic Pursuits

Mrs. Madhavi Srinivas Sadu began her academic journey with a Bachelor’s degree in Computer Science and Engineering (B.E. CSE) from Prof. Ram Meghe Institute of Technology & Research, Badnera, affiliated with SGBAU, Amravati University, where she explored native XML databases through her project on Xindices. Her passion for computing led her to pursue M.Tech in Computer Science and Engineering from Vivekananda Institute of Technology & Science, Karimnagar, under JNTU Hyderabad, where she researched performance improvements in parsers using PEG (Parsing Expression Grammar). She has recently submitted her Ph.D. thesis at Raisoni University, Saikheda, focused on Information Security and Privacy Preservation in Big Data using Machine Learning.

Professional Endeavors

With over 18 years of rich teaching experience, Mrs. Madhavi Srinivas has steadily contributed to academia. She began as an Adhoc Lecturer at Kavikulguru Institute of Technology & Science, Ramtek, followed by a brief tenure at Rajiv Gandhi College of Engineering, Research & Technology, Chandrapur, where she later secured a permanent position as an Assistant Professor (Senior Grade). Since 2007, she has been actively involved in nurturing undergraduate students in Computer Science and Engineering, making substantial contributions to the academic ecosystem of her institution.

Contributions and Research Focus On Computer Science

Mrs. Madhavi Srinivas’s research focus lies at the intersection of machine learning, data security, and privacy. Her doctoral research centers on utilizing machine learning algorithms to ensure data privacy in Big Data environments, a pressing concern in today’s digital era. She has authored 28 research publications, including 12 papers in international journals and 3 book chapters, underscoring her commitment to advancing knowledge in her field. Her work bridges foundational computing concepts with emerging technologies, aiming for real-world solutions in information security.

Impact and Influence

Her influence extends beyond classroom teaching into academic administration and curriculum development. As a member of the Board of Studies and Question Paper Moderation Committee at Gondwana University, she has played a pivotal role in shaping the academic policies and examination standards. She has served as an organizer and speaker in national-level programs like AICTE-ISTE workshops and soft computing seminars, disseminating advanced computing knowledge to faculty and students alike. Her involvement in these roles reflects her leadership in academic governance and faculty development.

Research Skills

Mrs. Madhavi brings a diverse and practical skill set to her research. Her expertise includes data mining, algorithm design, parser optimization, and machine learning techniques. She has hands-on experience in developing intelligent systems for data privacy, and her work is grounded in both analytical rigor and software implementation. Her teaching subjects further reflect her technical command over areas like deep learning and computer architecture, making her a valuable resource for interdisciplinary research initiatives.

Awards and Honors

Her professional journey has been marked by multiple accolades and recognitions. Although a separate document details her achievements, it is noteworthy that she is a life member of several esteemed bodies, including the Indian Society for Technical Education (ISTE), Institution of Engineers (IE), and INSC. Her patent filing, participation in 13 national conferences/workshops, and recognized book chapter publications are testaments to her active scholarly involvement.

Academic Citations

While specific citation metrics are not provided, her 28 publications and her longstanding association with recognized academic committees and professional bodies indicate a healthy academic footprint. Her peer-reviewed papers in international journals contribute to the scholarly discourse in Big Data privacy, security frameworks, and parser performance optimization, areas vital to the advancement of secure computing environments.

Legacy and Future Contributions

With nearly two decades of service in academia, Mrs. Madhavi Srinivas has built a legacy of academic dedication, technical innovation, and mentorship. Her future ambitions likely include further refining machine learning applications in secure data analytics, expanding her patent portfolio, and potentially guiding doctoral candidates in emerging computing fields. Her continued engagement with curriculum design, student mentorship, and national educational forums promises enduring contributions to both computer science education and technological research in India.

Publications Top Notes

IBMESR: Towards Next-Generation Big Data Security with Integrated Blockchain Model for Efficient, Scalable, and Robust Operations

Abhilash Pati | Computer Science | Research Pioneer Award in Biomedical Sciences | 1881

Published on by Best Achievements

Dr. Abhilash Pati | Computer Science | Research Pioneer Award in Biomedical Sciences 

Dr. Abhilash Pati, Siksha O Anusandhan University, Bhubaneswar, India

Dr. Abhilash Pati is an accomplished Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan University, Bhubaneswar, India. With over 15 years of academic and research experience, he specializes in Artificial Intelligence, Machine Learning, Blockchain, IoT, and Fog Computing. He has authored three books, published over 60 research articles indexed in Scopus and WoS, and holds three patents, including a granted design utility. His work is widely recognized in high-impact journals such as IEEE Access, Scientific Reports, and PLOS ONE. Dr. Pati is also UGC-NET qualified and actively mentors students and research initiatives.

Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Abhilash Pati’s academic journey began with a strong passion for technology and computing, which later shaped his extensive career in computer science. From his early days, he exhibited a deep curiosity in how systems work, leading him to pursue higher education in Computer Science and Engineering. His dedication and academic rigor earned him recognition early on, culminating in qualifying the prestigious UGC-NET, a testament to his proficiency and commitment to academic excellence in India. His foundational training not only built his core technical skills but also fostered an analytical mindset that would serve as the cornerstone for his research pursuits in artificial intelligence and emerging technologies.

🧑‍🏫 Professional Endeavors

Dr. Abhilash Pati currently serves as an Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan University, Bhubaneswar, India, a premier institution recognized for academic innovation and research. With over 15 years of experience, Dr. Pati has built a career marked by dedication to teaching, curriculum development, and student mentorship.

Throughout his tenure, he has engaged in the delivery of undergraduate and postgraduate courses, supervised student projects, and contributed to the design of industry-aligned academic programs. His role is not limited to classroom instruction; he is actively involved in research groups and collaborative initiatives that bridge the gap between academia and industry. This dual focus on pedagogy and innovation has made him a respected figure among students and peers alike.

🔬 Contributions and Research Focus

Dr. Pati’s research spans several cutting-edge domains, including Artificial Intelligence (AI), Machine Learning (ML), Blockchain Technology, Internet of Things (IoT), and Fog Computing. These fields represent the frontier of technological advancement, and Dr. Pati’s contributions have helped propel research in these areas, especially in applications related to smart systems and intelligent data processing.

He has authored and co-authored over 60 research publications, many of which are indexed in Scopus and Web of Science (WoS). His work is regularly published in high-impact journals such as IEEE Access, Scientific Reports (Nature Portfolio), and PLOS ONE, reflecting the global recognition of his scholarly output.

Additionally, he has authored three academic books and holds three patents, including a granted design utility patent—further illustrating the practical implications of his research and its potential for technological innovation.

🏅 Accolades and Recognition

Dr. Pati’s academic and professional excellence has not gone unnoticed. His qualification in UGC-NET speaks volumes about his academic merit. Beyond that, his prolific publication record, patent filings, and scholarly books underscore his status as a thought leader in his field. His articles are frequently cited by researchers worldwide, and he has often been invited as a reviewer and editor for reputed international journals and conferences.

Moreover, his contributions are instrumental in shaping institutional research strategies, leading to enhanced collaborations and interdisciplinary research output within his university and beyond.

🌐 Impact and Influence

Dr. Pati’s influence extends far beyond the lecture hall or laboratory. As a mentor, he has guided numerous students toward academic excellence and research competence. Many of his mentees have gone on to pursue higher education, research careers, or roles in the tech industry, thanks to the foundational skills and inspiration he provided.

His interdisciplinary approach—linking AI with Blockchain, or IoT with Fog Computing—has opened up new research directions for his peers and collaborators. Furthermore, his publications have served as reference points in academia and industry, helping shape conversations around the ethical, scalable, and efficient deployment of smart technologies.

🌟 Legacy and Future Contributions

Dr. Abhilash Pati’s journey is one of sustained growth, intellectual curiosity, and purposeful impact. Looking ahead, he is poised to continue contributing to the evolving technological landscape by focusing on sustainable computing, ethical AI, and decentralized systems. His vision includes building robust academic-industry partnerships and creating innovation hubs that foster student-led research and startups.

His legacy will not just be defined by the number of papers or patents, but by the culture of curiosity, critical thinking, and compassion that he instills in the next generation of computer scientists. Through teaching, mentorship, and research, Dr. Pati is building a future where technology serves humanity more intelligently and equitably.

Publication Top Notes

An IoT-fog-cloud integrated framework for real-time remote cardiovascular disease diagnosis

Author: A Pati, M Parhi, M Alnabhan, BK Pattanayak, AK Habboush, …
Journal: Informatics
Year: 2023

Heartfog: Fog computing enabled ensemble deep learning framework for automatic heart disease diagnosis

Author: A Pati, M Parhi, BK Pattanayak
Journal: Intelligent and Cloud Computing
Year: 2022

COVID-19 pandemic analysis and prediction using machine learning approaches in India

Author: A Pati, M Parhi, BK Pattanayak
Journal: Advances in Intelligent Computing and Communication
Year: 2023

A review on prediction of diabetes using machine learning and data mining classification techniques

Author: A Pati, M Parhi, BK Pattanayak
Journal: International Journal of Biomedical Engineering and Technology
Year: 2021

Mei Song | Computer Science | Best Scholar Award

Published on by Best Achievements

Assoc. Prof. Dr. Mei Song | Computer Science | Best Scholar Award

Assoc. Prof. Dr Mei Song, Jiangsu Normal University, China.

Assoc. Prof. Dr. Mei Song is an accomplished academic and researcher at Jiangsu Normal University, China. Holding a Ph.D. from Shanghai Jiao Tong University, she specializes in machine learning and natural language processing. With over 40 publications in prestigious journals and conferences, she has also authored four monographs and secured multiple software copyrights. Her research projects, including the National Natural Science Foundation of China grant, emphasize innovation in FinTech and intelligent education. An active collaborator with institutions like Arizona State University, Dr. Song is a member of the China Computer Federation and a leader in advancing computational and information sciences.

Author Profile:

Scopus Profile

🎓 Education Background:

Assoc. Prof. Dr. Mei Song’s educational background reflects her dedication to academic excellence and innovation. She earned her Ph.D. in 2012 from the prestigious Shanghai Jiao Tong University, one of China’s leading institutions. Her doctoral studies laid the foundation for her expertise in machine learning and natural language processing. Further enhancing her academic credentials, Dr. Song completed a postdoctoral program at the Financial Research Institute and Credit Information Center, People’s Bank of China. These formative experiences have significantly shaped her research trajectory, equipping her with the knowledge and skills to lead cutting-edge projects in computational and financial technologies.

💼 Professional Experience:

Assoc. Prof. Dr. Mei Song has an extensive professional background in academia and research. Currently serving at Jiangsu Normal University in the School of Computer Science and Technology, she has made significant contributions to the fields of machine learning and natural language processing. Dr. Song earned her Ph.D. from Shanghai Jiao Tong University and completed a postdoctoral fellowship at the Financial Research Institute of the People’s Bank of China. Her expertise spans academic publishing, with over 40 papers, and leadership in research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the Jiangsu Provincial Education Science Planning Project.

🌍Research Contributions:

Assoc. Prof. Dr. Mei Song has made significant research contributions in machine learning, natural language processing, and FinTech. She has authored over 40 academic papers in leading journals and conferences, including Neurocomputing and Systems Engineering – Theory & Practice. Her innovative methodologies, such as improved over-sampling techniques, have advanced data processing and classification. Dr. Song has led and participated in over 30 research projects, including grants from the National Natural Science Foundation of China and the China Postdoctoral Science Foundation. Additionally, she has secured multiple software copyrights and authored monographs, showcasing her dedication to impactful and applied research.

🥇Award and Honors:

Assoc. Prof. Dr. Mei Song has received numerous accolades throughout her distinguished academic career. Her contributions to machine learning and natural language processing have been recognized with funding from prestigious bodies, including the National Natural Science Foundation of China. She has also been honored for her innovative research in FinTech and intelligent education, receiving awards for excellence in academic publishing and software development. Dr. Song’s work has earned her positions on editorial boards and memberships in esteemed organizations, such as the China Computer Federation. Her awards and honors reflect her profound impact on advancing computational sciences and education technology.

Conclusion:

Assoc. Prof. Dr. Mei Song’s extensive contributions to academia and research position her as a deserving candidate for the Best Scholar Award. Her work in machine learning and natural language processing has led to over 40 impactful publications, four authored monographs, and numerous patents. Through prestigious projects like the National Natural Science Foundation of China grant, she has demonstrated exceptional innovation and leadership. Her collaborations with global institutions and active participation in professional organizations highlight her commitment to advancing science and fostering international academic exchange. Dr. Song’s achievements exemplify excellence, making her a worthy recipient of this prestigious recognition.

📚Publication Top Notes:

📘 Hierarchical Dijkstra Algorithm Based on Generalized Rule Tree for Crowdsourced Express Delivery
Huang, J., Ding, C., Wang, R., Song, M., Yang, M.
🗓️ 2024 | 🔢 0 Citations

📗 Credit Risk Prediction Based on Improved ADASYN Sampling and Optimized LightGBM
Song, M., Ma, H., Zhu, Y., Zhang, M.
🗓️ 2024 | 🔢 0 Citations

📙 A Dynamic Interest-Aware Message-Passing GCN for Recommendation
He, W., Zhu, Y., Song, M., Wu, Z., Hao, G.
🗓️ 2024 | 🔢 0 Citations

📕 An Adaptive Learning Feature Model Validation Methodology Based on Formal Methods
Wang, C., Zhu, Y., Song, M.
🗓️ 2023 | 🔢 1 Citation

📘 Chinese Nested Named Entity Recognition Based on Boundary Prompt
Li, Z., Song, M., Zhu, Y., Zhang, L.
🗓️ 2023 | 🔢 3 Citations

📗 A Review of 3D Reconstruction from High-Resolution Urban Satellite Images
Zhao, L., Wang, H., Zhu, Y., Song, M.
🗓️ 2023 | 🔢 19 Citations

📙 Fixed-Time Bipartite Consensus of Nonlinear Multi-Agent Systems Under Directed Signed Graphs with Disturbances
Xu, Z., Liu, X., Cao, J., Song, M.
🗓️ 2022 | 🔢 27 Citations

📕 Analysis and Verification of Bisimulation Relationship for Learning Time-Behavior Sequence
Feng, S., Zhu, Y., Song, M., Gao, Y.
🗓️ 2022 | 🔢 0 Citations

📘 Research on Trust Formation of Dissimilar Source Information Within G2B Infomediary
Song, M., Zhang, P.-Z., Fan, J.
🗓️ 2015 | 🔢 1 Citation

📗 An Objective Measurement of Information Value Using Application Traces in Infomediary
Song, M., Wang, J.
🗓️ Year Unavailable | 🔢 Citation Data Not Listed