Keith Hunter
April 28th, 2023
Title: TBA
Keith Hunter's primary research interests revolve around organizational networks, culture, and leadership. He is particularly interested in how social networks both influence and reflect the active mental models and power dynamics within organizations. His investigations of the patterns of interaction among people and their implications for human behavior and organizational outcomes are of critical significance to tomorrow's business leaders.
Johanne Saint-Charles
April 21st, 2023
Title: TBA
Dr. Johanne Saint-Charles is a pioneer in the study of the links between health, the environment and society, with a focus on gender and social inequities. She is among the founding members of communities of practice in ecohealth in Latin America and Canada, has contributed to the Ecosanté research chair on urban pollution in West Africa and has been director of an interdisciplinary research center on health, society and the environment.
Jay Pujara
April 14th, 2023
Title: TBA
Jay Pujara is Research Assistant Professor in Computer Science at the University of Southern California. His research interest lies in handling massive amounts of noisy, changing evidence for machine learning, including devising scalable algorithms for big data, designing probabilistic models that gracefully capture uncertainty, and developing techniques for streaming inference that provide theoretical guarantees.
Lucy Lu Wang
April 7th, 2023
Title: TBA
Lucy Lu Wang is an Assistant Professor at the University of Washington Information School. Her research uses natural language processing and data science techniques to make sense of scientific and research output. Specifically, she investigates NLP methods for understanding biomedical text, systems to help us make better and more data-driven care decisions, as well as how text analysis techniques can be used to identify trends in research communication.
Tiffany Callahan
March 31st, 2023
Title: Learning Deep Translational Patient Representations for Rare Disease Classification and Subphenotyping (access)
Dr. Callahan received her Ph.D. in Computational Biology from the University of Colorado Anschutz Medical Campus in 2021 and is currently a Postdoctoral Research Fellow in the Department of Biomedical Informatics at Columbia University Irving Medical Center. Dr. Callahan’s PhD thesis leveraged graph representation learning and neural-symbolic reasoning of large-scale biological knowledge graphs in order to develop realistic estimates of human disease mechanisms. She is currently applying these methods to improve the detection, prediction, and understanding of complex phenomena like phenotyping of pediatric rare disease and adverse event detection.
Tim Clark
March 24th, 2023
Title: Evidence Graphs and AI/ML Explainability (access)
Tim Clark is an Associate Professor of Public Health Sciences, Neurology, and Data Science at the University of Virginia (UVA). He has played a major role in the development and application of FAIR (Findable, Accessible, Interoperable, Reusable) principles and design patterns to scientific publications and repositories. His current research focuses on the development of provenance-aware research data commons environments. He is a co-PI of the NIH Bridge2AI: Cell Maps for Artificial Intelligence project, and Technical Director of UVA’s Center for Advanced Medical Analytics. He holds a Ph.D. in Computer Science from the University of Manchester.
Michael Galkin
March 10th, 2023 (recording)
Title: Towards Neural Graph Databases (access)
Michael is a Research Scientist at Intel AI Labs working on Graph Machine Learning and Geometric Deep Learning. Previously, Michael was a postdoc at Mila - Quebec AI Institute working with Will Hamilton, Jian Tang, and Reihaneh Rabbany on various graph learning tasks ranging from reasoning and knowledge graphs to molecular representation learning.
Robert Hoehndorf
March 3rd, 2023 (recording)
Title: Machine Learning with Biomedical Ontologies (access)
Robert Hoehndorf is an Associate Professor of Computer Science at King Abdullah University of Science and Technology (KAUST), where he is the Principal Investigator of the Bio-Ontology Research Group (BORG). His main academic interests are knowledge representation and symbolic approaches to artificial intelligence and using them to gain novel biological insights. They develop knowledge-based methods for the analysis of large, complex and heterogeneous datasets in biology, and apply them to understanding genotype-phenotype relations.
Emanuel Sallinger
February 24th, 2023 (recording)
Title: Knowledge Graphs in Action: a Tour of Extensions and Real-World Applications of the Vadalog System (access)
Emanuel Sallinger is Assistant Professor of Computer Science at Vienna University of Technology (TU Wien) and Lecturer for Knowledge Graphs and Database Design at Oxford University. His main research focus is on Knowledge Graphs, including all theoretical and practical aspects. In particular, he is interested in reasoning in such systems, including all of the AI methodologies for that. Within such systems, his interest is in achieving scalable solutions, making sure that theory translates into practice.
Erin Leahey
February 17th, 2023 (recording)
Title: Papers and Patents are Becoming Less Disruptive over Time (access)
Erin Leahey is Professor and Director of Sociology at the University of Arizona and an elected member of the Sociological Research Association. She is known largely for her work on science, scientific careers, and inequality therein. Recently she has focused on studying the costs, benefits, and precursors of interdisciplinary research at both the individual and organization levels.
Jennifer D’Souza
February 10th, 2023 (recording)
Title: Semantic Publishing of Scientific Contributions in the Open Research Knowledge Graph (access)
Jennifer D’Souza is a Postdoctoral Researcher at the TIB Leibniz Information Centre for Science and Technology in the R&D Department. Her research interests mainly include developing supervised machine learning techniques for natural language processing to facilitate text mining and automated information extraction. Her current primary research theme is knowledge graph construction from scientific text by NLP methods. Aside from this, she is also interested in scientometrics.
Anita Bandrowski
February 3rd, 2023 (recording)
Title: Can Research Resource Identifiers (RRIDs) be Used to Better Understand Scientific Literature? (access)
Dr. Bandrowski is a researcher in the department of neuroscience at UCSD, a visiting professor at the QUEST center at the Berlin Institute of Health, and the CEO of a technology startup called SciCrunch Inc. She started and runs the Research Resource Identification Initiative, asking authors to put persistent unique identifiers, RRIDs for tools they used in their paper, into their publications as a way to improve parts of reproducibility in science. She is passionate about fixing bits of the reproducibility crisis in science that can be engineered out of existence!
Will Byrd
January 27th, 2023 (recording)
Title: The mediKanren Biomedical Reasoner and the Precision Medicine Case Review Process (access)
Will Byrd is a scientist at the Hugh Kaul Precision Medicine Institute at the University of Alabama at Birmingham. He leads the Precision Medicine Institute's effort to develop mediKanren, biomedical reasoning software funded under the NIH NCATS Biomedical Data Translator Project. Will is one of the creators of the miniKanren family of constraint logic programming languages, and co-author of 'The Reasoned Schemer' (MIT Press, 2018).
Peter A. Gloor
January 20th, 2023 (recording)
Title: Happimetrics - Leveraging AI to Untangle the Surprising Link Between Ethics, Happiness and Business Success (access)
Peter A. Gloor is a Research Scientist at the Center for Collective Intelligence at MIT’s Sloan School of Management where he leads a project exploring Collaborative Innovation Networks (COIN). His research focus is on the analysis of temporal communication patterns of virtual teams to increase knowledge worker innovation and productivity by discovering and optimizing Collaborative Innovation Networks and Collaborative Knowledge Networks.
In Fall 2021, Spring 2022, and Fall 2022, we focused our speaker series on “Responsible Data Science and AI Speaker Series”. In this series, we discussed topics such as equity, fairness, biases, ethics, and privacy. For a list of prior talks please see below.
Fall 2022
Anissa Tanweer
November 18th, 2022 (recording)
Title: Data Science Ethics in Practice and for Practice: An Ethnographic Perspective (access)
Anissa Tanweer is a research scientist at the eScience Institute. She conducts ethnographic research on the practice and culture of data science, and brings a sociotechnical lens to bear on the design and implementation of data science training programs. She is passionate about leveraging action research to foster reflexive, ethical data science practices.
Fariba Karimi
November 11th, 2022 (recording)
Title: Minorities in networks and algorithms (access)
Fariba Karimi is a team leader in computational social science at the Complexity Science Hub Vienna and an assistant professor at the Department of Network and Data Science at Central European University since March 2021. Her research focuses on computational social science, the emergence of biases and inequality in networks and algorithms, and modeling human behavior.
Manish Raghavan
November 4th, 2022 (recording)
Title: The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization (access)
Manish Raghavan is the Drew Houston (2005) Career Development Professor at the MIT Sloan School of Management (in the Information Technology group) and department of Electrical Engineering and Computer Science. His primary interests lie in the application of computational techniques to domains of social concern, including online platforms, algorithmic fairness, and behavioral economics, with a particular focus on the use of algorithmic tools in the hiring pipeline.
Emoke-Agnes Horvath
October 28th, 2022 (recording)
Title: Science on the Web: How networks bias academic communication online (access)
Ágnes Horvát is an Assistant Professor in the Department of Communication Studies, (by courtesy) the Department of Computer Science, and (also by courtesy) the Kellogg School of Management at Northwestern University. Her research seeks to investigate how networks induce biased information production, sharing, and processing on digital platforms.
Vera (Qingzi) Liao
October 21st, 2022 （recording）
Title: Human-Centered Explainable AI (XAI): from Algorithms to User Experiences (access)
Vera Liao is a Principal Researcher at Microsoft Research Montreal where she is part of the FATE group. She is a human-computer-interaction (HCI) scientist by training and have broad interests in human-AI interaction. Most recently she hs been working on explainable AI and responsible AI.
Faculty host: Yun Huang
Karina Rider
October 14th, 2022 (recording)
Title: Building Things that Matter: The Ambivalence of Tech for Good Initiatives (access)
Karina Rider is a sociologist studying how technologists try to build ‘tech for good.’ She is especially interested in how technologists think about the relationship between their careers and the types of technologies–and technological futures–they want to build. Her current project investigates civic technology nonprofits in the San Francisco Bay Area, and she is in the planning phase of a new project exploring grassroots support and opposition for tech campus construction projects.
Pepa Kostadinova Atanasova
October 7th, 2022 (recording)
Title: Towards Explainable and Accountable Fact-Checking (access)
Pepa Atanasova is a last-year Ph.D. student at the Natural Language Processing Section at the University of Copenhagen, supervised by Isabelle Augenstein. Her main research interests lie in the area of explainable machine learning with applications in complex reasoning tasks such as fact checking and question answering.
Jacob Ward
September 30th, 2022 (recording)
Title: The Loop: How Technology is Creating a World without Choices and How to Fight Back (access)
Jacob is a television correspondent and producer. Since 2018 he has been a correspondent for NBC News, reporting on the unanticipated consequences of science and technology in our lives. He was also a former fellow at Stanford University’s Center for Advanced Study in the Behavioral Sciences, a television series host on the science and implications of bias, and the editor-in-chief of Popular Science.
Milena Tsvetkova
September 16th, 2022 (recording)
Title: Inequality and fairness with heterogeneous endowments (access)
Milena Tsvetkova is an Assistant Professor in the Department of Methodology at the London School of Economics and Political Science and completed her PhD in Sociology at Cornell University in 2015. Her research interests lie in the fields of computational and experimental social science. She employs online experiments, network analysis, and agent-based models to study fundamental social phenomena such as cooperation, contagion, and inequality.
Safiya U. Noble
September 9th, 2022
Title: Taking on Big Tech: New Paradigms for New Possibilities (access)
Safiya U. Noble is an internet studies scholar and Professor of Gender Studies and African American Studies at the University of California, Los Angeles (UCLA). In 2021, she was recognized as a MacArthur Foundation Fellow (also known as the “Genius Award”) for her ground-breaking work on algorithmic discrimination.
Spring 2022
Byron Wallace
April 22nd, 2022
Title: Methods to Aid Model Debugging: From Rationales to Influence (access)
Byron Wallace is an associate professor in the Khoury College of Computer Sciences at Northeastern University. His research is primarily in natural language processing (NLP) methods, with an emphasis on their application in health informatics.
Faculty host: Halil Kilicoglu
Katie Shilton
April 15th, 2022
Title: Trustworthiness in social data science: Excavating awareness and power (access)
Katie Shilton is an associate professor in the College of Information Studies at the University of Maryland, College Park, and leads the Ethics & Values in Design (EViD) Lab. Her research explores ethics and policy for the design of information technologies.
Mine Çetinkaya-Rundel
April 8th, 2022
Title: Teaching Data Science, Responsibly (access)
Mine Çetinkaya-Rundel is a Professor of the Practice and the Director of Undergraduate Studies at the Department of Statistical Science and an affiliated faculty in the Computational Media, Arts, and Cultures program at Duke University. Her work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education.
Faculty host: JooYoung Seo
Aisha Walcott-Bryant
April 1st, 2022
Title: AI’s Potential to Transform Global Health (access)
Dr. Aisha Walcott-Bryant is a Senior Technical Staff Member (STSM) and Research Manager at IBM Research - Nairobi, Kenya. She has a strong interest in developing AI tools for Global Health (see our recent work on COVID-19 interventions, and working across sectors to create innovative, sustainable AI solutions that transform emerging economies.
Brooke Foucault Welles
March 25th, 2022 (8:30 - 9:30 am Central Time)
Title: #HashtagActivism: Networks of Race and Gender Justice (access)
Brooke Foucault Welles is an associate professor and interim chair of the Department of Communication Studies, core faculty of the Network Science Institute, and director of the Communication Media and Marginalization (CoMM) Lab at Northeastern University. Combining the methods of network science with theories from the social sciences, Foucault Welles studies power and amplification in online communication networks, with particular emphasis on how these networks mitigate and exacerbate marginalization.
Thema Monroe-White
March 11th, 2022
Title: Emancipatory Data Science (access)
Thema Monroe-White is an assistant professor at Berry College and has over 10 years of combined evaluation, research and data analytics expertise from her years as a consultant, nonprofit leader, and instructor.
Angela Stewart
February 25th, 2022
Title: Scales of Change: Intelligent Systems to Support Social Learning (access)
Angela Stewart is a Postdoctoral Fellow in the Human-Computer Interaction Institute at Carnegie Mellon University, working under Dr. Amy Ogan. She create socio-technical interventions for more equitable and inclusive educational spaces.
Sheena Erete
February 18th, 2022
Title: Co-designing Technologies, Practices, and Policies to Counter Structural Oppression (access)
Sheena Erete is currently an associate professor in the College of Computing and Digital Media at DePaul University. She is also an educator, designer, and community advocate, whose research focuses on co-designing socio-cultural technologies, practices, and policies with community residents to amplify their local efforts in addressing issues such as violence, education, civic engagement and health.
Maarten Sap
February 11th, 2022
Title: Detecting and Rewriting Socially Biased Language (access)(recording)
Maarten Sap is a Postdoc/Young Investigator at the Allen Institute for AI (AI2), working on project Mosaic, and will be starting as an assistant professor at CMU's LTI department. His research focuses on endowing NLP systems with social intelligence and social commonsense, and understanding social inequality and bias in language.
Margaret Hu
February 4th, 2022
Title: Self-Coup, Soft Coup, Silent Coup (access)
Margaret Hu is Professor of Law and International Affairs at Penn State Law and School of International Affairs at the Pennsylvania State University. Her research interests include the intersection of national security, cybersurveillance, and AI and civil rights.
Robin Berjon
January 28th, 2022
Title: Digital Advertising, Privacy, and Competition (access)(recording)
Robin Berjon is an expert in Web technology with almost two decades’ worth of experience in both Web development and driving standardization efforts, notably within W3C. He is in charge of data governance at The New York Times.
Faculty host: Madelyn Sanfilippo
Fall 2021
In Fall 2020, this series was co-hosted by Jana Diesner and Nigel Bosch.
Tjitze Rienstra
December 3rd, 2021
Title: Explanation through Argumentation (access)
Tjitze Rienstra is an assistant professor at the Department of Data Science & Knowledge Engineering, Faculty of Science and Engineering, Maastricht University, The Netherlands. His research focuses on Explainable AI, computational models of argumentation, and reasoning under uncertainty.
Ana-Andreea Stoica
November 19th, 2021
Title: Diversity and Inequality in Social Networks (access)
Ana-Andreea Stoica is a Ph.D. candidate at Columbia University. Her work focuses on mathematical models, data analysis, and inequality in social networks. She is particularly interested in studying the effect of algorithms on people's sense of privacy, community, and access to information and opportunities.
Laura Nelson
November 12th, 2021
Title: Partial Perspective and Situated Knowledge: A Feminist Appraisal of Machine Learning & AI (access)
Laura K. Nelson is an assistant professor of sociology at the University of British Columbia. She uses computational methods – principally text analysis, natural language processing, machine learning, and network analysis techniques – to study social movements, culture, gender, and organizations and institutions
Ceren Budak
November 5th, 2021
Title: Quantifying the Role of Display Advertising in the Disinformation Ecosystem (access)
Ceren Budak is an Assistant Professor of Information at the School of Information at the University of Michigan. Her research interests lie in the area of computational social science. She utilizes network science, machine learning, and crowdsourcing methods and draws from scientific knowledge across multiple social science communities to contribute computational methods to the field of political communication.
Julia Stoyanovich
October 29th, 2021
Title: Teaching Responsible Data Science (access)
Julia Stoyanovich is an Institute Associate Professor of Computer Science & Engineering at the Tandon School of Engineering, Associate Professor of Data Science at the Center for Data Science, and Director of the Center for Responsible AI at New York University (NYU).
Katrin Weller
October 22nd, 2021
Title: Acknowledging potential pitfalls in social media research – between researcher's practices and structured documentation approaches (access)
Katrin Weller is leading the Digital Society Observatory team as part of GESIS’ Computational Social Science department. From 2021-2023 she is also co-leading the Research Data & Methods unit at the Center for Advanced Internet Studies (CAIS). In her work she looks into how researchers across disciplines use data from Web and Social Media Platforms as new types of research data – and how this leads to new challenges along the research process.
Babak Salimi
October 15th, 2021
Title: Generating Post-hoc Explanations for ML Models Using Contrastive Counterfactuals (access)
Babak Salimi is an assistant professor in HDSI at UC San Diego. Before joining UC San Diego, he was a postdoctoral research associate in the Department of Computer Science and Engineering, University of Washington, where he worked with Prof. Dan Suciu and the database group. He received his Ph.D. from the School of Computer Science at Carleton University, advised by Prof. Leopoldo Bertossi.
Alexandra Olteanu
October 8th, 2021
Title: Challenges to the Foresight and Measurement of Computational Harms Time (access)
Alexandra Olteanu is a principal researcher at Microsoft Research Montréal, part of the Fairness, Accountability, Transparency, and Ethics (FATE) group. Her work currently examines practices and assumptions made when evaluating a range of computational systems, particularly measurements aimed at quantifying possible computational harms.
Rainer Böhme
October 1st, 2021
Title: Privacy preferences and choice architecture: the case of consent management on the web (access)
Rainer Böhme is professor of Computer Science and head of the Security & Privacy Lab at the University of Innsbruck in the Austrian Alps. His background is interdisciplinary with degrees in Communication Science, Economics, and Computer Science.
Pardis Emami-Naeini
September 24th, 2021
Title: Designing an Informative and Usable Security and Privacy Label for IoT Devices (access)
Pardis Emami-Naeini is a postdoctoral scholar in the Security and Privacy Research Lab at the University of Washington. Her research is broadly at the intersection of security and privacy, usability, and human-computer interaction.
Lindah Kotut
Semptember 17th, 2021
Title: Amplifying the Griot: (Ancient) Stories Guiding the Design of Fair, Equitable & Transparent Systems (access)
Lindah Kotut is an assistant professor in the Information School at the University of Washington. She completed her Ph.D. in computer science from Virginia Tech where she was advised by Dr. Scott McCrickard. Her research is at the intersection of Human-Computer Interaction (HCI) and Indigenous Knowledge (IK).
Ryan Baker
September 10th, 2021
Title: Algorithmic Bias in Education: From Unknown Bias to Known Bias to Fairness to Equity (access)
Ryan Baker is an Associate Professor at the University of Pennsylvania, and Director of the Penn Center for Learning Analytics. His lab conducts research on engagement and robust learning within online and blended learning, seeking to find actionable indicators that can be used today but which predict future student outcomes.
Allison Morgan
September 3rd, 2021
Title: Faculty hiring, social class, and epistemic inequality (access)
Allison Morgan is currently a data scientist at Twitter. Broadly, she’s interested in using causal inference and network science, joining surveys with big data, and studying fairness and social inequality by building systems.
Su Lin Blodgett
August 27th, 2021
Title: Towards Building Equitable Language Technologies (access)
Su Lin Blodgett is a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics (FATE) group at Microsoft Research Montréal. She is broadly interested in examining the social implications of natural language processing technologies.