Khushboo Pandey

Assistant Professor

Khushboop@rvu.edu.in

About
Publication & Works
Research Summary
Awards & Achievements

Khushboo Pandey is a dedicated professional currently serving as an Assistant Professor at the School of Computer Science and Engineering at RV University. She has completed her undergraduate degree in Computer Science and Engineering and her postgraduate degree in Computer Science and Engineering from APJ Abdul Kalam Technical University in Lucknow(Uttar Pradesh). She is also pursuing her PhD at Amity University(Noida, UP). She has an overall work experience spanning over 9 years, during which she has dedicated 7 years to teaching. Additionally, she has ventured into entrepreneurship and innovation, which adds a practical dimension to her academic insights. Her pursuit of knowledge and dedication to both teaching and research underscore her role as a promising academician and researcher in her field.

Subject Command: DBMS, Theory of Computation (Automata), Discrete Structures, Data Structure

Computer Programming Language: C, Python, Core Java, JavaScript

Never Give up. (life is a Struggle, Keep on adventure).You only get one life.

Book Chapter on “Integration of IoT in renewable energy for smart cities” Published in the book “Smart Cities: Power Electronics, Renewable Energy, and Internet of Things” CRC Press.

Patent on “AI-Based SMS Spam Detection using Machine Learning Approach”(Published in the Indian Patent Office Journal, Application Number-202231005713)

Patent on “A method & system for safe & secure conveyance schemes in metropolises using Blockchain and IoT”( Published in the Indian Patent Office Journal, Application Number-202211021698)

Patent on “An IOT Based Smart System for Hygiene Monitoring in Realtime” (Published in the Indian Patent Office Journal, Application Number-202211066463)

Patent on “A system for Asset Management on the Rail Network with the Help of AI and ML”(Published in the Indian Patent Office Journal, Application Number-202211067754)

Used MRI images database as Input and find haralick’s features. Using Convolutional Neural Network, determine whether the tumor is present or not in MRI Images along with accuracy. The work was performed in various steps of the CAD System after the image data (MRI) were collected. They were pre-processing, and post-processing of MRI images, statistical feature analysis to extract features from images, and artificial intelligence method designed with supervised learning were applied as an automatic method to classify the images under investigation into having tumors or not.
Research Interests:
Machine Learning

Outstanding Faculty Award 2021 (KIET Group of Institutions, Ghaziabad)
Received AICTE Scholarship for the Post Graduation(M.Tech)
Certified UGC NET(2022)
Academic Excellence Certificate in 2019
GATE (2017)
NPTEL Online Certification on “Problem-Solving through Programming in C”(Got Elite+ Silver)
Course on Interactivity with JavaScript, Web Technologies and Security Specialization on Coursera
Academic Excellence Certificate in 2012