Graduate Student
CurrentCutting-edge Master of Information in Data Science (MIDS) program focused on machine learning, statistics, and analysis of big data problems.Capstone Project:Four-member team delivers a 48-hour forecast of grid carbon intensity so consumers and businesses can plan and make greener energy consumption choices based on current and historical energy demand and supply activity from the California ISO and weather forecasts.Select Coursework:Natural Language Processing with Deep Learning - text classification with statistical methods and neural networks, pre-trained transformer architectures, generative pre-trained models (GPT)Statistics for Data Science - OLS and logistic regression, probability spaces, random sampling, hypothesis testing, comparing groups, descriptive vs. explanatory model building, maximum likelihood estimationResearch Design and Applications for Data and Analysis - question formation, bias, qualitative vs. quantitative approaches, creating narratives with data and visualizationApplied Machine Learning - feature engineering and selection, regularization, gradient descent, neural networks, KNN, decision trees, ensembles, k-Means analysis, PCA, CNNsMachine Learning at Scale - Hadoop and Spark, Map-Reduce approaches, big data systems and pipelines for distributed machine learning, algorithms for graphs, trees, clustering, and recommendation systemsSelect Additional Projects:Comparing BERT and DeBERTa models for Multi-Dimensional Automated Essay ScoringForecasting weather-driven flight delays at least 2 hours prior to departureCloud detection in satellite imagery with semantic segmentation
