Chaudhury Sanjeev Kumar Dash | Social Media and Digital Marketing | Best Researcher Award

Dr Chaudhury Sanjeev Kumar Dash Silicon University, India

Dr. Chaudhury Sanjeev Kumar Dash received his Ph.D. in Computer Science from Fakir Mohan University, India, in 2014. His doctoral research, supervised by Prof. Satchidananda Dehuri at F. M. University in Balasore, focused on “Evolutionary Neural Network for Data Mining.” With a solid foundation in academia, he embarked on a career in teaching and research. He began as an Associate Professor at the Silicon Institute of Technology, where he later assumed the position of Senior Assistant Professor. Throughout his tenure, he has been dedicated to shaping the minds of future professionals, imparting knowledge, and fostering a culture of innovation. Driven by a passion for advancing the field of computer science, he continues to explore new avenues in research and education.

🌐 Profile Links:

• Scopus
• ORCID
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• ResearchGate 

Education:

He obtained his Ph.D. in Computer Science from Fakir Mohan University, India, in 2014. His doctoral thesis, titled “Evolutionary Neural Network for Data Mining,” was completed under the guidance of Prof. Satchidananda Dehuri at F. M. University in Balasore. Prior to his Ph.D., he earned his M.Tech in Computer Science with First Class distinction from the School of Mathematics, Statistics & Computer Science at Utkal University, India, in 2004. This academic journey equipped him with a solid foundation in both theoretical and practical aspects of computer science, particularly focusing on data mining and computational intelligence techniques. Through his research and academic pursuits, he has demonstrated a strong aptitude for applying advanced computational methods to solve complex problems in various domains. His expertise in evolutionary neural networks and data mining reflects his dedication to exploring innovative solutions for challenging real-world issues. With a solid educational background and guidance from esteemed mentors, he continues to contribute to the advancement of computer science through his research, teaching, and professional endeavors.

Experience:

He served as an Associate Professor at the Silicon Institute of Technology and later transitioned to the role of Senior Assistant Professor at the same institution. With a keen dedication to academia, he contributed significantly to the academic and research endeavors within the institution. His roles encompassed not only teaching but also mentoring students, guiding research projects, and engaging in scholarly activities. At Silicon Institute of Technology, he played a pivotal role in shaping the educational experiences of students, fostering a dynamic learning environment, and instilling a passion for knowledge among learners. Additionally, his expertise and leadership qualities were instrumental in driving initiatives aimed at enhancing the academic standards and research output of the institution. Prior to his tenure at Silicon Institute of Technology, he served as a Lecturer at B.C.E.T., Balasore, where he honed his teaching skills and laid the foundation for his academic career. Throughout his journey, he has demonstrated a commitment to excellence in education and has been a source of inspiration for both students and colleagues alike.

Publications:

1. Radial basis function neural networks: a topical state-of-the-art survey Cited By : 112, Published By ; 2016
2. An outliers detection and elimination framework in classification task of data mining Cited By : 27, Published By ; 2023
3. Design of self-adaptive and equilibrium differential evolution optimized radial basis function neural network classifier for imputed database Cited By : 19, Published By ; 2016
4. DE+ RBFNs based classification: A special attention to removal of inconsistency and irrelevant features Cited By : 18, Published By ; 2019
5. Building a novel classifier based on teaching learning based optimization and radial basis function neural networks for non-imputed database with irrelevant features Cited By : 17, Published By ; 2022
6. Improving software reliability prediction accuracy using CRO-based FLANN Cited By : 17, Published By ; 2019
7. QORA-ANN: quasi opposition based Rao algorithm and artificial neural network for cryptocurrency prediction Cited By : 12, Published By ; 2021
8. On the study of GRBF and polynomial kernel based support vector machine in web logs Cited By : 10, Published By ; 2013
9. Feature selection for designing a novel differential evolution trained radial basis function network for classification Cited By : 9, Published By ; 2013
10. Differential Evolution-Based Optimization of Kernel Parameters in Radial Basis Function Networks for Classification Cited By : 9, Published By ; 2013