The University of Massachusetts Amherst

Faculty Research Groups

Joining a faculty research group is an effective way to get feedback on your research and helps you develop a network of like-minded scholars across disciplines. UMass and the College of Social and Behavioral Sciences have many dynamic, active working groups that are open to new members.


Economics and Political Economy

Analytical Political Economy Working Group
Research discussion of articles, as well as presentations of members' work in progress.
For updates and meeting details, please contact the coordinators.
Coordinators: Peter Skott and Arslan Ramzi

Applied Microeconomics Workshop
Paper presentation series.
Dates listed on department website.
Coordinator: Arin Dube and Ina Ganguli

Economic History and Development Workshop
Paper presentation series.
Dates listed on department website.
Coordinators: Mwangi Wa Gĩthĩnji and Vamsi Vakulabharanam

Economic Theory Workshop
Paper presentation series.
Currently on hiatus.
Coordinator: Donald Katzner

Experimental Economics Reading Group (EERG)
The group meets weekly to read and discuss papers in experimental economics. Papers are chosen by group members, and so topics vary by semester and interest. The meeting is open to other disciplines interested in experimental methods and to members of the Five Colleges.
Currently on hiatus.
Coordinators: Sherry Gao

Gender and Economics Working Group
Research discussion of articles and members' work in progress, as well as presentations of work in progress.
For updates and meeting details, please contact the coordinator.
Coordinator: Nancy Folbre

Industrial Organization Reading Group
Presentations and discussions of research papers and members' works in progress.
Fridays, 10:30am to 11:30am, via Zoom. For updates and meeting details, please contact the coordinator.

Coordinator: Christoph Bauner

Political Economy Working Group (PEWG)
Research discussions of work in progress by faculty, grad students and outside visitors working in political economy.
Currently on hiatus.
Coordinators: Kevin Young and Regine Spector 

Political Economy Workshop
Paper presentation series.
Dates listed on department website.

Coordinator: Isabella Weber

Urban, History, and Industrial Organization Working Group
The group meets three times every semester to discuss the group's titular areas.
Currently on hiatus.
Coordinator: Vamsi Vakulabharanam


Environment and Sustainability

Climate Change: Diversity on Human Impacts and Responses
Cutting across the arts and humanities, social and natural sciences, and engineering fields, faculty in this Institute of Diversity Sciences group pursue a wide range of projects that examine the diversity of human impacts and responses in the context of global climate change.
For updates and meeting details, please contact the coordinator.
Coordinator: Ezra Markowitz

Energy Transition Institute
Fall 2020 updates TBD.
Coordinators: Michael Ash and Anna Goldstein

Environmental Working Group
Research discussion of articles and members' work in progress, as well as presentations of work in progress.
Currently on hiatus.
Coordinators: James Boyce and Michael Ash

Social Science and Environment Network
ISSR's cross-college discusses research projects and opportunities for collaboration, building scholarly community, and seed funding for external proposals.
Contact the coordinators to be added to the email list.
Coordinators: Eve Vogel and Regine Spector


Equitable Algorithms and A.I.

EQUATE is an initiative of CICS faculty who are engaged in research and education related to equitable algorithms and systems and welcome social scientists to the table. Our educational efforts include coursework in ethics and algorithm design that respects the values of fairness and transparency. Our research efforts explore EQUATE topics within software systems and programming languages, machine learning, and vision, theory, and data management systems. EQUATE is affiliated with the Center for Data Science.
For updates and meeting details, please contact the coordinator(s) for each group.

Computer Vision
Erik Learned-Miller has been involved in face recognition research since 2005, and has published more than 20 articles on the topic. He and his collaborators created one of the most widely used databases and benchmarks for face recognition, known as Labeled Faces in the Wild. Recently, he has been working to develop standards and principles for the use of face recognition technology in research, in government, and in business. His current interests include the establishment of transparency, intended use, and fairness in the deployment of face recognition algorithms.
Coordinator: Erik Learned-Miller

Disparities in Natural Language Processing
Do language technologies equitably serve all groups of people? The way we speak and write varies across demographics and social communities — but natural language processing models can be quite brittle to this variation. If an NLP system, such as machine translation or opinion analysis, works well for some groups of people but not others, that impedes information access and the ability of authors’ voices to be heard, since media communication is now filtered through search and newsfeed relevance algorithms.
Coordinator: Brendan O'Connor

Safe and Fair Machine Learning
In this project we study how the user of a machine learning (ML) algorithm (method) can place constraints on the algorithm’s behavior. We contend that standard ML algorithms are not user-friendly, in that they can require ML and data science expertise to apply responsibly to real-world applications. We present a new type of ML algorithm that shifts, from the user of the algorithm to the researcher who designs the algorithm, many of the challenges associated with ensuring that the ML method is safe to use. The resulting algorithms provide a simple interface for specifying what constitutes undesirable behavior of the ML algorithm, and provide high-probability guarantees that it will not produce this undesirable behavior.
Coordinator: Yuriy BrunPhilip Thomas, and Shlomo Zilberstein

Engineering Fair Systems
Many diverse factors can cause software bias, including poor design, implementation bugs, unintended component interactions, and the use of unsafe algorithms or biased data. Our work focuses on using the engineering process to improve software fairness. For example, tools can help domain experts specify fairness properties and detect inconsistencies among those requirements; they can automatically generate test suites to measure software bias to identify bias in black-box systems even when the system’s source code and the data used to train it are unavailable; they can help developers and data scientists debug causes of bias, both in the source code and the data; and they can formally verify fairness properties in the implementation. Our work in engineering fair systems combines research in software engineering with machine learning, vision, natural language processing, and theoretical computer science to create tools that help build more fair systems.
Coordinator: Yuriy Brun and Alexandra Meliou

Balancing Privacy and Fairness
Data collected about individuals is regularly used to make decisions that impact those same individuals. For example, statistical agencies (e.g., the U.S. Census Bureau) commonly publish statistics about groups of individuals that are then used as input to a number of critical civic decision-making procedures, including the allocation of both funding and political representation. In these settings there is a tension between the need to perform accurate allocation, in which individuals and groups receive what they deserve, and the need to protect individuals from undue disclosure of their personal information. As formal privacy methods are adopted by statistical agencies and corporations, new questions are arising about the tradeoffs between privacy protection and fairness. We are investigating these tradeoffs and devising new metrics and algorithms to support a favorable balance between these two social goods.
Coordinator: Gerome Miklau

Data Diversity
The big data revolution and advancements in machine learning technologies have revolutionized decision making, advertising, medicine, and even election campaigns. Yet, data is an imperfect medium, often tainted by skews and biases. Learning systems and analysis software learn and amplify these biases. As a result, discrimination shows up in many data-driven applications, such as advertisements, hotel bookings, image search, and vendor services. Since data skew is often a cause of algorithmic bias, the ability to retrieve balanced, diverse datasets can mitigate the underlying problem. Diversification also has usability implications, as it allows us to produce representative samples of a dataset that are small enough for human consumption. Our research focuses on developing methods for producing appropriately diverse subsets of given datasets efficiently and scalably, aiming to alleviate biases in the underlying data and to facilitate user-facing data exploration systems.
Coordinator: Alexandra Meliou and Gerome Miklau

Explainability in Data Analysis
Explanations are an integral part of human behavior: people provide explanations to justify choices and actions, and seek explanations to understand the world around them. The need for explanations extends to technology, as crucial activities and important societal functions increasingly rely on automation. Yet, today’s data is vast and often unreliable and the systems that process data are increasingly complex. As a result, data and the algorithms that process data are often poorly understood, potentially leading to spurious analyses and insights. Many users even shy away from powerful analysis tools whose processes are too complex for a human to comprehend and digest, instead opting for less sophisticated yet interpretable alternatives. The goal of our research is to promote users’ trust in data and systems through the development of data analysis toolsets where explainability and interpretability are explicit goals and priorities of the systems’ function.
Coordinator: Alexandra Meliou and David Jensen


Ethnography

The Ethnography Collective @ UMass
The Ethnography Collective @ UMass supports ethnography in all of its many manifestations, creating a community grounded in the arts and sciences of deep, immersive research that takes seriously the critical importance of embodied, lived, and relational knowledge production. The Ethnography Collective aims to increase advocacy, education, and visibility for ethnographic research.
For updates and meeting details, please contact the coordinator.
Coordinator: Betsy Krause and Sally Galman


Health

Health
Faculty interested in multidisciplinary collaborations in health disparities through this Institute of Diversity Sciences group present their work, receive feedback, comment on others, and self-form into multidisciplinary research teams. Teams may apply for seed grants given out by the Institute to fund small projects that can be leveraged into future bigger external grants.
Fall 2020 meetings will take place on the following Fridays from 2:30pm to 3:30pm: 9/25, 10/30, and 11/25.
For updates and meeting details, please contact Leyla Keough.
Coordinator: Buju Dasgupta (cc. Leyla Keough)


Learning and Diversity

Learning and Work
Faculty in this Institute of Diversity Sciences group pursue research investigating the causes of group differences in learning, as well as individual and group differences in social cognition and linguistics.
Fall 2020 meetings will take place on the following Fridays from 2:30pm to 3:30pm: 9/18, 10/16, and 11/13.
For updates and meeting details, please contact Leyla Keough.
Coordinator: Buju Dasgupta (cc. Leyla Keough)


Legal Studies

Five College Legal Studies Seminar
Research presentations (usually working papers).
For updates and meeting details, please contact the coordinator.

Coordinator: Paul Collins


Media and Communication

Media Effects
The Media Effects working group is comprised of faculty and graduate students who primarily use quantitative methods to study the role of media in individuals’ lives. They meet periodically to share resources, plan projects, and provide feedback on in-progress research.
For updates and meeting details, please contact the coordinator.
Coordinator: Seth Goldman

Media, Technology, and Society
Research discussions among faculty and graduate students examining the role of information and communication technologies (ICTs) in forming relationships, communities and public opinion, and the power dynamics that shape these processes in different institutional, national and transnational contexts.
For updates and meeting details, please contact the coordinator.
Coordinator: Martha Fuentes-Bautista

Social Interaction and Culture Research Group
A group of faculty and students working in ethnographic and cultural approaches to social interaction, intercultural communication, environmental communication, personhood, ethnic and racial identity, power in discourse, management of disagreement, interaction in the media, and mediated interaction.
For updates and meeting details, please contact the coordinator.
Coordinator: Benjamin Bailey


Migration

Migration Working Group
Open to faculty and graduate students working on migration related research. Presentations of works in progress and occasional guest speakers.
For updates and meeting details, please contact the coordinator.

Coordinators: Rebecca Hamlin and Scott Blinder


Public Policy

School of Public Policy Faculty Colloquium Series
Monthly talks by UMass Amherst faculty on policy-related research and works in progress. Designed to stimulate scholarly collaborations among policy-oriented faculty across campus.
For updates and meeting details, please contact the coordinator.
Coordinator: David Mednicoff and Mo Turner

UMass Air
Cross-campus collaboration around the use and policy implications of unmanned aerial systems (UASs).
For updates and meeting details, please contact the coordinator.
Coordinator: Charlie Schweik


Research Funding Discussions

Funding Fridays
Grant funding can be critical to faculty careers, but difficult to pull off on your own given limited time. ISSR invites you to take part in a flexible, year-long series aimed at motivating, informing, and supporting faculty writing grants for submission in 2020. Join ISSR any time. You can stop by each week for remote workshops, writing sprints, and research design office hours that will help you stay on track for your goals, or hop on and off for only the sessions you need. 
To register, click here.
Coordinator: Krista Harper


Sociology

Cluster Brown Bags
Working papers across subfields.
Currently on hiatus.
Coordinator: Amy Schalet