Dr Surabhi Saxena
Assistant Professor , Department of Computer Science , Christ University , Bangalore · CHRIST ( Deemed to be University )
Biography
Surabhi Saxena received the Ph.D. degree from the Department of Computer Application, Babu Banarasi Das University, Lucknow, India, in 2021. She is currently an Assistant Professor with the Department of Computer Science and Engineering, CHRIST University, Central Campus, Bengaluru, India. She has more than five years of teaching experience and six years of research experience. She has one national patent. Her research has been recorded in over 20 journal publications and international conferences and five international conference reviewers. Her research and publication interests include artificial intelligence, machine learning, security software quality software, software engineering, and soft computing. She is also working in the areas of e-commerce, e-governance, hybrid data security system, voronoi partitioning, deep learning, data science, and the IoT. She is a Life Time Member of IAENG and IACSIT. She is also the Editor-in-Chief and an Editor of Blue Eyes Publications and a Soft
Education
Dr Surabhi Saxena received the Ph.D. degree from the Department of Computer Application, Babu Banarasi Das University, Lucknow, India, in 2021. She is currently an Assistant Professor with the Department of Computer Science and Engineering, CHRIST University, Central Campus, Bengaluru, India. She has more than five years of teaching experience and six years of research experience. She has one national patent. Her research has been recorded in over 20 journal publications and international conferences and five international conference reviewers
Recent Scopus Publications
- Development of a VR-Based Solid Waste Management Awareness Platform Utilizing YOLOv12 and MSCNN
- ANFIS-Based Multi-Sensor Data Fusion Model for Optimized Autonomous Vehicle Navigation Using Big Data and Filtering Techniques
- Visualization of Data Structures and Algorithms with Dynamic Memory Allocation
- Evaluate Machine Learning Techniques for Early Disease of Cardiovascular Disease
- Latency Reduction and Input Prediction for Cloud Gaming Clients
Links
- ORCID https://orcid.org/0000-0002-4518-059X
- Google Scholar https://scholar.google.com/citations?user=0bjilf8AAAAJ
- Scopus https://www.scopus.com/authid/detail.uri?authorId=57208210764
- Personal Weblink https://vidwan.inflibnet.ac.in/profile/244760