Shivani Joshi | Neural Networks | Innovative Research Award

Dr. Shivani Joshi | Neural Networks | Innovative Research Award

Galgotias University, India

Author Profile

๐ŸŒฑ Early Academic Pursuits

Dr. Shivani Joshiโ€™s journey into the world of technology and academia began with a strong foundation in Computer Science & Engineering. She earned her B.Tech from Chotu Ram State College of Engineering, Murthal, affiliated with Maharshi Dayanand University (MDU), Rohtak, securing an impressive 82% in 1997. Her passion for deeper knowledge led her to pursue an M.Tech in Computer Science & Engineering from Vaish Engineering College, also under MDU, where she excelled with 83% marks. ๐Ÿ…

Driven by an insatiable curiosity and commitment to academic excellence, Dr. Joshi undertook her doctoral studies at C.S.J.M. University, Kanpur, a state government university, and completed her Ph.D. in Computer Science & Engineering in 2013. Her early academic endeavors laid a robust platform for her dynamic career, blending theoretical rigor with practical technological insight. ๐Ÿง 


๐Ÿ‘ฉโ€๐Ÿซ Professional Endeavors

With an illustrious career spanning over 26 years, Dr. Shivani Joshi has donned multiple influential roles in the academic sphere. From a Professor to Director and Program Director at the reputed Stratford University, her leadership has left an indelible mark on higher education, both nationally and internationally.

Currently serving as a Professor at Galgotias University, Greater Noida, Dr. Joshi contributes significantly to the institutionโ€™s mission of academic excellence. Her good working knowledge of Outcome-Based Education (OBE) and her hands-on experience with NBA and NAAC Accreditation processes have been instrumental in steering academic programs toward quality assurance and continuous improvement. ๐Ÿ›๏ธ

Her teaching portfolio includes cutting-edge subjects like Big Data, DBMS, Artificial Intelligence (AI), Digital Image Processing, Software Engineering, and Object-Oriented Technologies (OOT). Her sessions are marked by clarity, technical depth, and a deep engagement with students. ๐Ÿ–ฅ๏ธ๐Ÿ“Š


๐Ÿ”ฌ Contributions and Research Focus

Dr. Joshiโ€™s scholarly work revolves around the ever-evolving domains of Artificial Intelligence, Big Data, and Digital Image Processing. Her Ph.D. research contributed to advancements in the theoretical underpinnings and practical applications of intelligent systems.

She has mentored numerous postgraduate students and guided academic projects that emphasize real-world applications. Known for her good analytical skills and adaptability, she embraces emerging tools like MATLAB, Hadoop, and Oracle in her research and pedagogy.

Dr. Joshi is also highly proficient in programming languages such as C, C++, Java, and Visual Basic (VB), ensuring her teaching aligns with current industry standards. Her research contributions and classroom practices exemplify a perfect blend of academic excellence and technological expertise. ๐Ÿ”๐Ÿ’ป


๐Ÿ† Accolades and Recognition

Dr. Shivani Joshiโ€™s contributions to education have been recognized by numerous academic forums and institutions. Her tenure at Stratford University and Galgotias University has earned her accolades for academic leadership, curriculum development, and student mentoring.

Her reputation as a knowledgeable and committed educator with good communication and interpersonal skills has made her a sought-after figure in academic circles, often invited to participate in accreditation reviews, conference panels, and quality assurance committees. ๐ŸŒŸ๐Ÿ“œ


๐ŸŒ Impact and Influence

Through her decades of experience, Dr. Joshi has significantly influenced curriculum development and academic policy, especially in aligning programs with NBA and NAAC standards. Her expertise in Outcome-Based Education (OBE) has empowered departments to adopt student-centric, performance-driven models.

She is not only an educator but a mentor who has helped shape the careers of countless students and faculty members. By keeping herself abreast of modern tools like Hadoop, MATLAB, and Oracle, she ensures that her students are future-ready. ๐Ÿ“˜๐Ÿš€


๐ŸŒŸ Legacy and Future Contributions

As she continues her academic journey, Dr. Shivani Joshi is poised to contribute even more profoundly to education and research. With her firm belief in lifelong learning and her motivation to rapidly acquire new skills on the job, she plans to delve deeper into Artificial Intelligence, Big Data Analytics, and their role in smart education systems. ๐Ÿ“ˆ๐Ÿค–

Her legacy lies in her dedication to teaching excellence, her active involvement in academic quality frameworks, and her unwavering support for student growth. Future contributions may include policy advisory roles, international collaborations, and pioneering research in AI-driven education.

With her vast experience, technical proficiency, and commitment to student success, Dr. Shivani Joshi continues to be an inspiring academic leader who bridges the gap between foundational learning and advanced technological evolution. ๐ŸŒ๐Ÿ“š

Citations

A total of 1470 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations        1470
  • h-index           09
  • i10-index        09

Notable Publications 

  • Title: Brain Tumor Detection Using ADARN Optimizer
    Authors: R Kumar, A Dwivedi, S Joshi, VC Tripathi
    Journal/Conference: 2024 2nd International Conference on Disruptive Technologies (ICDT), pp. 1271โ€“1275
    Year: 2024

  • Title: Identification of Pneumonia in Corona Virus Patient
    Authors: R Kumar, S Joshi, V Rai, A Dwivedi, N Jha
    Journal/Conference: 2022 International Conference on Computational Intelligence and Sustainable Computing
    Year: 2022

  • Title: Innovative Detection of IoT Cyber Threats Using a GBiTCN-Temformer and MKOA Framework
    Authors: V Rai, PK Mishra, S Joshi, R Kumar, A Dwivedi
    Journal/Conference: Journal of Network and Computer Applications, Article 104192
    Year: 2025

  • Title: Automated AI System for Online Phishing Detection and Mitigation
    Authors: D Raj, R Kumar, S Joshi
    Journal/Conference: 2024 International Conference on Electrical Electronics and Computing
    Year: 2024

  • Title: Cyberbullying Detection in Hinglish Language
    Authors: R Kumar, V Rai, S Joshi, D Raj, A Amrita
    Journal/Conference: 2024 International Conference on Electrical Electronics and Computing
    Year: 2024

RAJEASHWARI. S | Deep Learning | Best Researcher Award

Mrs. RAJEASHWARI. S | Deep Learning | Best Researcher Award

SRI S. RAMASAMY NAIDU MEMORIAL COLLEGE, India

Author Profile

Early Academic Pursuits ๐ŸŽ“๐Ÿ“–

Rajeswari S. has consistently demonstrated a deep passion for the field of Computer Science, as evident in her academic journey that began with her undergraduate studies in 2004. She earned a degree in Computer Science from a Deemed University, securing an impressive 75.6% and setting the foundation for her career in technology and education. Her dedication continued through her postgraduate studies at Anna University, where she achieved a commendable 73% in Computer Science in 2007.

Her academic curiosity led her to pursue an M.Phil. in Computer Science at Vinayaka Missions University in 2009, attaining a respectable 61.75%. Her dissertation, titled โ€œAnalysis of Medical Image Segmentation Using Fuzzy Hopfield Neural Network and Competitive Hopfield Neural Network,โ€ reflects her interest in innovative computational methodologies. Currently, she is pursuing a Ph.D. in Computer Science from Madurai Kamaraj University, furthering her expertise and research capabilities in this ever-evolving field.


Professional Endeavors ๐Ÿ’ผ๐Ÿ‘ฉโ€๐Ÿซ

Rajeswari has built a robust teaching career, marked by impactful roles at esteemed institutions. She began her professional journey as an Assistant Professor at K.R. College of Arts & Science, Kovilpatti, from June 2008 to June 2010. During this period, she nurtured budding technologists with her insightful teaching and dedication.

In 2016, she joined Sri Krishnasamy Arts and Science College, Sattur, where she served until April 2021. Her tenure was characterized by her ability to blend theoretical concepts with practical applications, making complex topics accessible to her students. Her teaching not only enriched the academic environment but also inspired many to explore advanced areas of Computer Science.


Contributions and Research Focus ๐Ÿง ๐Ÿ”ฌ

Rajeswariโ€™s research interests are deeply rooted in computational intelligence and its applications. Her M.Phil. dissertation delves into advanced image processing techniques, specifically medical image segmentation. By employing Fuzzy Hopfield Neural Network and Competitive Hopfield Neural Network, she contributed to the development of more accurate and efficient methods for medical diagnostics, showcasing her commitment to impactful research.

Her ongoing Ph.D. studies aim to expand this work, likely exploring cutting-edge technologies such as Artificial Intelligence (AI), Machine Learning (ML), and their intersections with image processing. Her research holds the potential to contribute to the fields of healthcare, diagnostics, and data analysis, addressing critical challenges with innovative solutions.


Accolades and Recognition ๐Ÿ†๐ŸŒŸ

Throughout her academic and professional career, Rajeswari has earned recognition for her dedication and contributions. While specific accolades are not listed, her ability to consistently secure teaching positions and handle complex research topics speaks volumes about her reputation in the academic community. She is undoubtedly appreciated for her commitment to quality education and her efforts to advance knowledge in her field.


Impact and Influence ๐ŸŒโœจ

Rajeswariโ€™s influence extends beyond the classroom. As an educator, she has empowered countless students with the skills and knowledge necessary to thrive in the tech industry. Her research work, particularly in medical image segmentation, has the potential to make significant contributions to healthcare by improving diagnostic accuracy and efficiency.

Her dual role as a teacher and researcher positions her as a bridge between theoretical knowledge and practical applications, fostering a deeper understanding of computer scienceโ€™s capabilities and limitations.


Legacy and Future Contributions ๐ŸŒŸ๐Ÿ”ฎ

Looking forward, Rajeswari is poised to leave a lasting legacy in both academia and research. Her ongoing Ph.D. studies and prior achievements suggest a future filled with innovative contributions to technology and education. As she continues to explore the realms of AI and neural networks, her work will likely influence emerging technologies and inspire new generations of researchers.

In the classroom, her commitment to nurturing talent ensures that her influence will echo through the achievements of her students. Meanwhile, her research endeavors promise to address pressing challenges, particularly in healthcare and data processing, cementing her position as a thought leader in her field.

Notable Publications 

  • Title: An Enhanced Learning Model Based on an Improved Random Forest Classifier and an Integrated Attribute Selector for Healthcare Datasets
    Authors: Rajeswari, S., Arunesh, K.
    Journal: Communications in Computer and Information Science
    Year: 2025.
  • Title: Enhancing pneumonia diagnosis with ensemble-modified classifier and transfer learning in deep-CNN based classification of chest radiographs
    Authors: Rajeswari, S., Arunesh, K.
    Journal: Biomedical Signal Processing and Control
    Year: 2024.
  • Title: Chronic disease prediction with deep convolution based modified extreme-random forest classifier
    Authors: Rajeswari, S., Arunesh, K.
    Journal: Biomedical Signal Processing and Control
    Year: 2024.
  • Title: Chronic disease diagnosis and classification using data mining approaches โ€“ a comprehensive review
    Authors: Rajeswari, S., Arunesh, K.
    Conference Proceedings: AIP Conference Proceedings
    Year: 2023.
  • Title: Highly Correlated Linear Discriminant Analysis for Dimensionality Reduction and Classification in Healthcare Datasets
    Authors: Rajeswari, S., Arunesh, K.
    Conference Proceedings: Lecture Notes in Networks and Systems
    Year: 2023.