Doctor of Philosophy (PhD)

Christ University, Bangalore | 2020–2025

• Stock prediction using multimodal learning (tabular, sentiment, time-series, news video)

Post Graduate Diploma in Computer Applications

Indira Gandhi National Open University | 2017–2018

• Focused on C programming, systems analysis, web design
• Learned computer organisation, database management, Java programming

Masters of Commerce – Finance

Chaudhary Charan Singh University, Meerut | 2015–2017

• Studied managerial economics, statistical analysis
• Focus on security analysis, portfolio & financial management

Assistant Professor

Christ University | (May 2025 – Present)

Teaching: Predictive Analytics, Financial Forecasting,Developed automated Excel assignment checker

Teaching Assistant

Christ University | (May 2022 – Dec 2024)

Courses handled: Computer Applications in Business, Excel, E-commerce,Guided practical data analysis projects

MultiModal Machine Learning AutoML

BMMA framework is capable of scaling to multiple modalities such as tabular, sentiment data, time series, and computer vision data...

Hybrid Subset Feature Selection and Importance Framework

Implements MultiSURF, ReliefF, SURF, and more for scalable feature selection...

systematic-reviewpy

An open-source Python framework for systematic review based on PRISMA

Stock Market Prediction Techniques Using Artificial Intelligence: A Systematic Review

Chandravesh Chaudhari, Geetanjali Purswani | Congress on Intelligent Systems, Springer Nature Singapore | 2022

This paper systematically reviews the literature related to stock price prediction systems...

Hybrid Subset Feature Selection And Importance Framework

Chandravesh Chaudhari, Geetanjali Purswani | 2023 IEEE International Conference on Contemporary Computing and Communications (InC4), Bangalore, India, 2023 | 2023

Feature selection algorithms are used in high-dimensional data to remove noise...

Machine Learning for Business

Machine Learning for Business is an interactive and practical learning hub that connects business strategy with modern machine learning techniques.

Programming for Machine Learning and Business

This interactive book is designed to help learners, researchers, and professionals bridge the gap between Python programming, machine learning fundamentals, and real-world business applications.