Raquib here, a Data Science & Machine Learning expert. Skilled in predictive modelling, classification, forecasting and sentiment analysis across diverse datasets. Expert in machine learning & LLM models. He has a strong background in creating well-researched documents with a clear focus on methodology, technical accuracy and academic integrity. He is good at identifying research gaps by thoroughly studying recent works in a particular domain. His work includes research papers, projects, technical reports, simulation studies, literature reviews, and analytical documentation. I'm good at reviewing recent works in a particular research topic or projects. This includes books, research papers and open-source materials. He has worked on a variety of academic and technical projects involving machine learning, simulations and quantitative modeling. The focus was always on clear methodology and better results. His experience includes building Bayesian Neural Network models for prediction, developing and documenting a 4-DOF Half-Car Suspension Model, and working with advanced system-level simulation models. In financial research, He worked on DCC-GARCH models to study market volatility and returns, conducted data clustering analysis on U.S. state-level electric school bus adoption, and analyzed the relationship between VIX and Forex markets - A Quantitative Look at Global Risk Sentiment. He has also performed sentiment analysis using LLMs (NLP), helping to extract meaningful insights from large volumes of text data. He has experience in Financial Market Analysis.
LinkedIn Profile: linkedin.com/in/md-raquib-hassan