Teaching

Joe lectures academically on topics in business, politics, economics, and statistics. Subfield topics include political behavior, institutions, research methodology, data science, analytics and NLP. His experience includes the instruction of hundreds of undergraduate and graduate students at top universities and academic conferences, most at Columbia and Emory.

Current Students

Current students can find the materials for current courses below:

Course Title Semester Time Place
Special Topics: Data Science for Startups and Enterprise (QTM 385) Spring 2023 Mondays 6:00PM - 8:30PM PAIS 235
Special Topics: Elections and Forecasting (QTM 385) Fall 2022 Wednesdays 6:00PM - 7:00PM PAIS 250
Special Topics: Data Analytics (QTM 385) Fall 2021 Mondays 2:30PM - 5:15PM New Psych Building, #225

Course Offerings

Quality of Instruction. The average student scores Joe’s teaching a 4.8/5 (N=241 reviews submitted, 40% participation rate, 6 courses). His current and previous teaching positions follow.

Special Topics: Data Science for Startups and Enterprise

Level Upper level course for college juniors and seniors.
Objective Students become familiar with a survey of industry business models and ethical dilemmas in data science
Abstract Many executives know they should be using data science, but most have no idea where to start. This seminar trains both functional and technical professionals in the business of data science, so that they may provide that guidance to executives and their teams. As a result, QTM students learn to apply their top-tier training successfully in the business environment. This course is structured as a seminar with invited guest speakers.

Special Topics: Elections and Forecasting

Level Upper level course for college juniors and seniors.
Objective Students will understand how elections work in the U.S., how campaigns view voters, and how to forecast elections
Abstract This Fall, we anticipate the midterm election season. This course will go through the basic theory of elections, teach precinct analysis in Georgia, and then use real data to forecast national and local elections. Additionally, students will learn forecasting and GIS skills in an applied environment. We will also hold an election watch where project groups compete to see who forecasted the results the most accurately. Knowledge of R is required for this course.

Special Topics: Data Analytics

Level Upper level course for college juniors and seniors.
Objective Students practice a range of real-world case studies that apply the skillsets developed in QTM.
Abstract Digital transformation has generated incredible demand for quantitative performance management, machine-driven decision making, and strategic insight discovery. This demand has created immense professional opportunity for college graduates who have the right training. The course has five sections that address digital problems in the pharmaceutical, consumer packaged goods, healthcare, technology, and finance industries. Each section contains 1) an interactive lecture component, which introduces the case study and provides a problem solving framework, and; 2) a group work component, in which students work in groups of 4-5 to tackle the case and present their solution. Students will complete the course prepared for the type of work that applies their educational background to jobs at the world’s leading companies and consulting firms.

Topics in Methodology: Introduction to Text-as-Data

Level Upper level course for college juniors, seniors, and graduate students.
Objective Learn how to conduct applied research using text data.
Abstract Topics include a general approach to descriptive and causal inference using text, classical approaches to content analysis, statistical approaches to content analysis, stylometry, the vector space model, feature extraction, dimension reduction, classifiers, topic models, and selected newer topics.

Research Design and Quantitative Methods

Level Two-semester methodology course for college juniors and seniors.
Objective Learn how to conduct applied research using econometric approaches to identification and inference.
Abstract Students learn how to critique research designs by working with a body of scholarly research published in top-tier journals, and then propose a research project of their own. Substantive topics include scientific research design, DAGs, identification and inference, mechanisms, modes of research, and meta-analysis. Quantitative topics include basic probability theory, sampling theory, mechanisms, survey research, ordinary least squares, data visualization, and R.

Topics in Methodology: Scaling of Latent Traits

Level Upper level course for college juniors, seniors, and graduate students.
Objective Understand the theory and practice of scaling, the method that lets us order politicians by ideology, draw inferences from machine analysis of texts, and personalize content at scale with artificial intelligence.
Abstract In this course, we review foundational estimation practices that stretch all the way back Catholic monasteries of the 1400s and into the modern era. Then, we apply the practices of NOMINATE, natural language processing, and joint scaling to study topics in economics, politics, finance, and marketing.

Introduction to American Politics

Level Introductory course, usually required, for college freshmen and sophomores.
Objective Provide an analytical framework with which students may dissect political situations and draw conclusions about the nature of our nation’s people.
Abstract Topics include collective action problems, principal-agent problems, federalism, institutional history, public opinion, political behavior, and elections. We also examine and contest scholarly debates around the causes and consequences of polarization in American politics.

The American Congress

Level Upper level course for college juniors and seniors.
Objective Understand the making of our nation and its laws by it’s most (in)famous political body, Congress.
Abstract In this course, we review the history of the American Congress, its creation under the Constitution, and how its designed solved collective action problems, focusing on works by the founders, Edmund Burke, and Dick Fenno. We then review procedure, bicameralism, supermajoritarianism, committees, and game theory, focusing particularly on work by Greg Wawro, Eric Schikler, and Keith Krehbiel. Finally, we study ideal point estimation, parties, polarization, gridlock, and trends in congressional organization, focusing on work by Matt McCubbins, Steven Smith, and Sarah Binder.

Topics in Politics: Politics and Modern Computing

Level (New!) Upper level course for college juniors, seniors, and graduate students.
Objective Understand the political implications of our nation’s digital transformation, and consider implications for the future.
Abstract New technology has precipitously reduced the costs of voter engagement, district interaction, and labor. This has upset the participatory and representative equilibria which have to this day evolved at a leisurely rate. In this course, we study how a reduction in the costs of collective action by way of digital transformation and artificial intelligence has changed the ways citizens interact with their political institutions.

Student Feedback

Joe was one of the most impressive instructors I have come across to date, across all the professors I've had. Not only is Joe incredibly knowledgeable in the field of politics, but he also possesses the special skill of presenting these concepts in a fascinating, relatable, and clear manner to his students. I highly recommend him to anyone looking for an instructor who is both brilliant and accommodating.

This class was one of the best courses I have taken at Emory. Dr. Sutherland was so great and really cared about our learning. He really knew how to tailor our learning towards applying it to the future. I really like the occasional special lectures on career building and technology outside of college. I will definitely be recommending this course and Dr. Sutherland to other students. Thanks for a great semester!

Once in a while, you meet an instructor who is amazing. He taught lectures on statistical programming that were excellent, by the way. Every week he explains concepts in a simple, intuitive way. I am probably as non-mathematically inclined as students come, but, thanks to Joe's patient explanations, I UNDERSTAND STATS. He's super nice and encouraging too, and so wonderfully patient when I ask inanely-phrased questions like "what's this Y change when X changes by one unit thing?" Joe's strong at teaching the Stats portion of things, AND the Theory portion of things.

Joe is a fantastic instructor. He is a very intelligent guy who does a great job at explaining every inch of the material very clearly. He is very easy to approach and always helps you if you have a question. Every class is interesting because he brings in relevant information from our current state as examples, and it really helps us to understand how the system works. His teaching style is very effective and he makes it easy to learn important points in the material.