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.
Data Analytics and Computational Social Science
DACSS Research Lab
The DACSS Research Lab conducts multi-method research that explores how social networks and social interaction shape individual and organizational decision-making in a wide range of political, social and economic contexts. Data collection and measurement approaches used by lab members include text scraping, text coding, interviews and participatory coding, surveys and survey experiments, networks, corpus linguistics, and construction of new datasets from a combination of existing, meta-analysis, and archival data sources. Our data analysis methods include advanced econometric or statistical approaches (including time series and multilevel models); data science approaches including networks, text, and machine learning; case analysis including process tracing and qualitative comparative analysis (QCA); and computational modeling of social systems and social interaction. We strive to create a safe, inclusive, collaborative, and respectful research environment and welcome students from a diversity of backgrounds and career stages.
For updates and meeting details, please contact the coordinators.
Coordinators: Eunkyung Song
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.
For updates and meeting details, please contact the coordinators.
Coordinator: Arin Dube and Ina Ganguli
Economic History and Development Workshop
Paper presentation series.
For updates and meeting details, please contact the coordinators.
Coordinator: Jayati Ghosh and Shouvik Chakraborty
Economic Theory Workshop
Paper presentation series.
For updates and meeting details, please contact the coordinators.
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: Katherine Moos
Industrial Organization Reading Group
Presentations and discussions of research papers and members' works in progress.
Fridays, 12:00pm to 1:00pm, in 303 Stockbridge Hall. 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: Lawrence King
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
Diversities and Disparities in Climate Change
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: Leyla Keough
Energy Transition Institute
For updates and meeting details, please contact the coordinator.
Coordinators: Michael Ash, Christine Crago, and Krista Harper
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 Brun, Philip 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.
Fall 2021 meetings will take place on September 20, from 11:00am to 12:00pm and October 18, from 11:00am to 12:00pm. 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.
Spring 2021 meetings will take place on the following Fridays from 3:00 to 4:30pm: 2/19, 3/19, and 4/23.
For updates and meeting details, please contact the coordinator.
Coordinator: 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.
Spring 2021 meetings will take place on the following Fridays from 1:30 to 3:00pm: 2/19, 3/12, and 4/16.
For updates and meeting details, please contact the coordinator.
Coordinator: Leyla Keough
Legal Studies
Five College Seminar in Justice, Law, and Societies
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
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: Joya Misra
Sociology
Cluster Brown Bags
Bi-monthly events for intellectual enrichment and engagement organized around (but not restricted to) the Sociology Department’s seven main research clusters: Gender, Sexualities, Families; Race, Immigration, Citizenship; Culture & Identity; Social Demography; Social Networks; Crime, Law, Deviance; Politics, Movements, Global & Transnational Sociologies; and Labor, Work, and Organizations. Programming includes guest seminars, research and professional development workshops, and presentations and discussion of works-in-progress. For updates and meeting details, please contact one of the faculty members of the Colloquia and Special Events Committee (CASEC)
For updates and meeting details, please contact the coordinators.
Coordinator: Joshua Kaiser, Aida Villanueva, and Youngmin Yi
