Teaching

Columbia Courses

Fall 2024

STCS 6701 GR Probablistic Models & Machine Learning (New Name: Statistical Machine Learning)

Statistical Machine Learning is a PhD-level course on statistical and probabilistic foundations of machine learning. We will cover statistical machine learning methods, theory, and inference as well as how to apply such methods to real problems. We study both the foundations and modern methods in this field. Our goals are to understand statistical machine learning, to begin research that makes contributions to this field, and to develop good practices for building and applying these models in practice.
Lectures: MW 2:40pm - 3:55pm

Data Science & Machine Learning Education

Genevera Allen is a sought after educator in machine learning and data science. She has developed and taught a variety of machine learning courses as well as several novel experiential learning courses in data science. These include an interdisciplinary data science capstone program where students work on real-world challenges and data sets from a variety of industries and disciplines.

Rice Center for Transforming Data to Knowledge (Rice D2K Lab)

In 2018, Genevera Allen founded and served as the Faculty Director of Rice’s data science education center, informally known as the Rice D2K Lab. The D2K Lab is a hub for data science education, providing students with engagement, enrichment, and experiential learning opportunities by connecting them with real-world data science challenges from companies, community organizations, and researchers. As part of these efforts, Genevera developed several new experiential learning courses including a novel data science capstone program that serves as the cornerstone of Rice’s data science undergraduate and masters degree programs.

Education Research

Key Publications:

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