An overview of my academic research and data science projects.
A Python software package that uses deep learning and symmetry preserving neural networks to enhance existing methods for simulating molecular systems, making them faster and more accurate.
Skills: deep learning, software development, TensorFlow, PyTorch
Web-app that lets users explore recent arXiv publications based on their research interests.
Skills: AWS, Docker, dash/plotly, spectral-clustering, recommender systems, gensim
Web-app to track twitter users' sentiments towards topics and gain insights into market and cultural trends
Skills: AWS, Apache Spark, Databricks, ETL, streaming data, sentiment analysis, dash/plotly
Finding (Pareto) optimal neighborhoods in NYC
Skills: (polynomial, k-NN, random forest)-regression, data visualization, scikit-learn, dash/plotly
Data analysis workflow of a saturation spectroscopy study on Rubidium. The experiment was conducted as part of the Graduate Laboratory course at Stony Brook University.
Skills: scientific data analysis, dashboards
Analysis of the US political twitter landscape.
Skills: ETL, sentiment analysis, hypotheses testing, data visualization, bokeh, networkx