Anjali Chennupati

Listed as a conference contribution (title appears in author publication list indicating work on detecting AI-generated text using LoRA fine-tuning approaches on LLMs).

Conference paper proposing a video anomaly detection framework combining Markov Random Fields (MRFs) and autoencoders; reports improved anomaly detection accuracy and a ~60% reduction in computation time versus a conventional frame extraction method (evaluated on the AVENUE dataset).

Conference paper describing a system that acquires intraday stock data and sentiment-laden news via web scraping; uses Apache Spark for sentiment analysis and XGBoost for time-series prediction, integrating predictions and sentiment scores to provide buy/sell recommendations (reported RMSE ≈ 1.2479).

Comparative study of multiple time-series forecasting approaches applied to Bitcoin price prediction, including deep-learning and classical models.