The PhD in Statistics and Data Science at the University of Pennsylvania offers students the opportunity to engage with cutting-edge methods in statistical modeling, machine learning, and big data analytics. These research topics represent key areas driving innovation in data science.
Statistical Modeling: Improving Predictive Models with Large-Scale Data
Machine Learning: Investigating the Use of Deep Learning for Image Classification
Big Data Analytics: Analyzing Large-Scale Data for Business Insights
Data-Driven Decision Making: Statistical Methods for Optimizing Business Operations
Bayesian Statistics: Applying Bayesian Methods in Complex Statistical Models
Natural Language Processing: Understanding Text Data Using Statistical Methods
Time Series Analysis: Developing Models for Forecasting Financial Markets
Computational Statistics: Building Scalable Algorithms for Large Data Sets
Quantitative Finance: Applying Statistics to Asset Pricing and Risk Management
Bioinformatics: Using Statistical Models to Analyze Genomic Data
Causal Inference: Developing Methods for Identifying Causal Relationships in Observational Data
Statistical Learning: Using Supervised and Unsupervised Learning for Data Classification
Data Visualization: Developing Tools for Visualizing Complex Statistical Data
Health Data Analytics: Analyzing Medical Data to Improve Patient Outcomes
Social Media Analytics: Using Data Science to Study Social Network Behavior
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