Courses

• STCS 6701: Probabilistic models and machine learning, Fall 2025
• STCS 8401: Field experiments, machine learning, and causality, Spring 2024
• STCS 6701: Probabilistic models and machine learning, Fall 2023
• STAT 8101: Applied causality, Spring 2023
• STCS 6701: Probabilistic models and machine learning, Fall 2022
• STAT 8101: Applied causality, Spring 2022
• STCS 6701: Foundations of graphical models, Fall 2020
• STCS 8101: Representation learning: A probabilistic perspective, Spring 2020
• STCS 6701: Foundations of graphical models, Fall 2019
• STAT 8101: Applied causality, Spring 2019
• STCS 6701: Foundations of graphical models, Fall 2018
• STAT/CS 8101: Applied causality, Spring 2017
• STAT/CS 6701: Foundations of graphical models, Fall 2016
• STAT/CS 6998-4: Probabilistic models of discrete data, Spring 2016
• STAT/CS 6509: Foundations of graphical models, Fall 2015
• STAT/CS 6998-4: Truth in data, Spring 2015
• STAT/CS 6509: Foundations of graphical models, Fall 2014
• COS424: Interacting with data, Spring 2014
• COS597A: Advanced methods in probabilistic modeling, Fall 2013
• COS424: Interacting with data, Spring 2012
• COS597C: Advanced methods in probabilistic modeling, Fall 2011
• COS513: Foundations of probabilistic modeling, Fall 2010
• COS597A: Truth in data, Fall 2009
• COS513: Foundations of probabilistic modeling, Spring 2009
• COS424: Interacting with data, Spring 2008
• COS597C: Bayesian nonparametrics, Fall 2007
• COS424: Interacting with data, Spring 2007
• COS402: Introduction to artificial intelligence, Fall 2006
• COS598C: Approximate inference in graphical models, Spring 2006