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Walid MagdyView profile

Professor

• Computational Social Science
• Natural Language Processing
• Social Content Analysis
• +8 more

Walid Magdy is a Professor at the School of Informatics, The University of Edinburgh, where he is a faculty member at the Institute for Language, Cognition and Computation (ILCC). He holds a PhD from Dublin City University's School of Computing and has been a faculty fellow at The Alan Turing Institute. With substantial industry experience, he has worked for Qatar Computing Research Institute (QCRI), Microsoft, and IBM, where he filed nine patents. His research spans computational social science and natural language processing. In computational social science, he focuses on social content analysis, political bias detection, polarization, and users' behavior analysis/prediction, with particular attention to understudied communities. His natural language processing work centers on social applications including sentiment analysis, sarcasm detection, and hate-speech identification, with specialized expertise in Arabic and its dialects as well as Persian. Professor Magdy's recent publications demonstrate a consistent focus on Arabic language processing and social media analysis, with growing attention to cultural factors in NLP systems. His work bridges computational methods with social science questions, particularly regarding misinformation, cultural differences in online behavior, and the impact of platform policies on diverse linguistic communities. He has expanded his research to include Persian language processing and continues to explore social dynamics across different cultural contexts. His significant contributions have been recognized with multiple awards: Best Demo Award for TwiXplorer at CSCW 2024 Outstanding Paper Award at ACL 2024 Best Paper Award Runner-up at SocInfo 2022 Best Paper Award at WANLP-EMNLP 2022 Best Paper Award at AIRS 2015 Best Dataset Award at ICWSM 2013 Professor Magdy serves as an editor for Springer's Social Network Analysis and Mining journal and has held leadership roles in major conferences including ACL 2023, ArabicNLP 2023, ICWSM 2022, and ASONAM 2022. He has co-organized numerous shared tasks focused on Arabic language processing and social media analysis, contributing significantly to community resources and benchmarks. He founded and directs the Social Media Analysis and Support for Humanity (SMASH) research group at the University of Edinburgh, which has organized the Summer School in Computational Social Science (SICSS-Edinburgh) in 2022, 2023, and 2025, training researchers in computational social science methodologies.

Tim AlthoffView profile

Associate Professor

• Artificial Intelligence
• Human-Centered Computing
• Data Science
• +5 more

Tim Althoff is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington, specializing in Artificial Intelligence and Human-Centered Computing. His research focuses on behavioral data science, combining Data Science Natural Language Processing Social Computing Human-Centered AI Ethics & Fairness to extract insights about health and well-being. Recent publications highlight advancements in: Mental health support through AI Wearable sensor health monitoring Online community analysis Reproducibility in data science Public health interventions with notable papers in ACL, Nature Machine Intelligence, and NeurIPS. Scientific recognition includes: ACL 2023 Outstanding Paper Award WWW 2021 Best Paper Award Double ICWSM 2021 Best Paper Awards SIGKDD Dissertation Award 2019 Fulbright Scholarship German National Merit Foundation Actively mentoring postdoctoral researchers and seeking PhD students in areas like neural representation learning, NLP applications to psychology, and mobile health technologies through his Behavioral Data Science Group .

Osman YağanView profile

Research Professor

• Machine Learning
• Data Science
• Network Science
• +7 more

Osman Yağan is a Research Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with affiliate faculty status in the School of Computer Science. He is also a core member of CyLab Security and Privacy Institute. Prior to joining CMU in 2013, he was a Postdoctoral Research Fellow at CyLab. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland (2011) and a B.S. from Middle East Technical University (2007). His research focuses on modeling, analysis, and optimization of computing systems, leveraging applied probability, network science, data science, and machine learning. Key areas include multi-armed bandits, resilient machine learning, contagion processes in networks, and cybersecurity. Research Interests include Machine Learning, Data Science, Network Science, Cybersecurity, and Robustness in Cyber-Physical Systems. He has advised numerous students, including current PhD candidates Yurun Tian, Orkun İrsoy, and Ishank Juneja, as well as notable alumni such as Mansi Sood (now at MIT) and Jun Zhao (Assistant Professor at Nanyang Technological University). Key Awards include the CIT Dean's Early Career Fellowship, IBM Academic Award, and Best Paper Awards at ICC 2021, IPSN 2022, and ASONAM 2023. His work spans theoretical contributions (e.g., contagion models in multi-layer networks) and applied research (e.g., mitigating cascading failures in power systems). He leads or co-leads grants from ONR, NSF, and ARO, focusing on resilient machine learning, network robustness, and pandemic modeling.

Srijan KumarView profile

Assistant Professor

• Data Science
• Applied Machine Learning
• Network Analysis
• +7 more

Srijan Kumar is an Assistant Professor in the School of Computational Science and Engineering at Georgia Institute of Technology's College of Computing. His research focuses on data science, AI for security, and online safety, addressing challenges in detecting malicious users, misinformation, and enhancing AI robustness. His work has been deployed in platforms like Flipkart and Wikipedia, and recognized through awards such as the NSF CAREER and Forbes 30 Under 30. Education: B.Tech from Indian Institute of Technology, Kharagpur Ph.D. in Computer Science from University of Maryland, College Park Postdoctoral training at Stanford University Research Interests: Multi-modal/multi-lingual detection of harmful content and users Adversarial robustness of AI models Graph and network analysis for early detection Responsible recommender systems Awards & Grants: NSF CAREER Award (2023) Kavli Fellow (2022) Facebook/Adobe Faculty Awards NSF Convergence Accelerator Phase II grant ($5M) Advising & Labs: Leads the CLAWS Lab, advising over 20 students. Active in mentoring through conferences and NSF-funded projects.

Salikoko S. MufweneView profile

Professor

• Evolutionary Linguistics
• Creole Languages
• Language Contact
• +9 more

Salikoko S. Mufwene is the Edward Carson Waller Distinguished Service Professor of Linguistics at the University of Chicago. He holds additional appointments on the Committees on Evolutionary Biology, Conceptual and Historical Studies of Science, and African Studies. His research integrates ecological perspectives into evolutionary linguistics, focusing on language contact, creole genesis, language endangerment, and the impact of colonization and globalization on linguistic diversity. Education: PhD in Linguistics, University of Chicago (1979) Key Themes: Language evolution, creole languages, population structure, decolonial linguistics, language policy Mufwene’s work emphasizes the role of population dynamics in language change, drawing parallels with biological evolution. His recent articles examine topics such as the cultural-artifact nature of language, the ecological drivers of creole hybridization, and the decolonization of linguistic paradigms. He has also contributed extensively to debates on language endangerment and multilingualism in super-diverse societies. Scientific Awards: Fellow, Linguistic Society of America (2018) Fellow, American Philosophical Society (2022) Fellow, American Academy of Arts and Sciences (2023) Collège de France lectures (2003, 2023-24) Summer Institute of the Linguistic Society of America (1999, 2005, 2015, 2017)

Ceren BudakView profile

Associate Professor

• Computational Social Science
• Social Media Analysis
• News Media Production and Consumption
• +7 more

Ceren Budak is an Associate Professor at the University of Michigan School of Information and holds a joint appointment as Associate Professor of Electrical Engineering and Computer Science in the College of Engineering. Her work bridges computer science, statistics, and social sciences through computational social science approaches. Her educational background includes a PhD in Computer Science from the University of California, Santa Barbara (2012) and a Bachelors degree in Computer Science from Bilkent University in Turkey (2007). Prior to joining the University of Michigan faculty, she was a Postdoctoral Researcher at Microsoft Research New York. Professor Budak's research centers on computational social science, with particular emphasis on analyzing large-scale datasets to address questions with social, political, and policy implications. Her work spans several interconnected domains: News Media Production & Consumption (examining bias in news outlets and reader preferences), Social Movements & Media (using social media data to study collective action), Social Networks (understanding information diffusion processes), and Measuring and Promoting the Quality of Online Discussions (developing tools to improve online conversations). She teaches SI 608 (Networks) and SI 618 (Data Manipulation and Analysis) at the School of Information. Her publication record demonstrates consistent contributions to understanding how online information ecosystems operate, with recent work focusing on AI-human collaboration, misinformation dynamics, social movement framing, and the application of computational methods to political communication. Her research shows a clear trajectory from foundational work on social network diffusion to increasingly sophisticated analyses of contemporary information challenges. Among her service activities, she has served as Registration chair for COSN (ACM Conference on Online Social Networks) 2015 and as Program Committee Member for numerous prestigious conferences including WWW, ICWSM, WebSci, AAAI, and others. She has also been involved in organizing the MSR NYC Data Science Seminar Series and instructing the Microsoft Research Data Science Summer School.

Gareth RobertsView profile

Associate Professor

• Language Evolution
• Language Change
• Language Variation
• +7 more

Gareth Roberts is an Associate Professor in the Department of Linguistics at the University of Pennsylvania, where he serves as Graduate Chair. He is also a faculty member of the Psychology Graduate Group, founder and director of the Cultural Evolution of Language Lab, and co-director of the Social and Cultural Evolution Working Group at Penn. Roberts earned his PhD in Linguistics from the University of Edinburgh in 2010, following an MSc in Evolution of Language and Cognition (2006) and a BA in German and Russian (2003) from the University of Nottingham. His academic journey includes postdoctoral positions at Yeshiva University and the University of Stirling before joining Penn as an Assistant Professor in 2014, where he was promoted to Associate Professor in 2022. His research focuses on the role of social and communicative pressures in shaping language emergence and evolution. Roberts investigates fundamental questions about linguistic variant spread, phonological system structuring, and how communication shapes linguistic structure. His work bridges linguistics, cognitive science, and cultural evolution through innovative experimental approaches using artificial languages and laboratory simulations. Analysis of Roberts' recent publications reveals a consistent focus on experimental semiotics, with particular attention to social biases in language evolution, phonological organization, indexicality emergence, and the dynamics of linguistic variation. His work often combines computational modeling with human experiments to isolate specific mechanisms driving language change. Linguistic Society of America Cognitive Science Society Philological Society Cultural Evolution Society Roberts has successfully secured substantial research funding including an NSF PAC Grant ($102,648), Penn URF Research Grants ($12,155), MindCORE initiative grant ($600,000), and multiple smaller grants totaling over $20,000. His lab currently includes researchers investigating diverse topics from case and gender marking emergence to AI agent effects on group dynamics, linguistic and genetic data in British history, and phonological space organization. The Cultural Evolution of Language Lab, which Roberts founded and directs, conducts cutting-edge research using experimental semiotics methodologies. Current projects examine how social factors influence language change, the emergence of linguistic structure through communication, and the interaction between iconicity and combinatoriality in communication systems.

Benedict KingView profile

Researcher

• Phylogenetic Analysis
• Evolutionary Biology
• Paleontology
• +4 more

Benedict King is a postdoctoral researcher in the Department of Linguistic and Cultural Evolution at the Max Planck Institute for Evolutionary Anthropology, where he contributes to the Comparative Oceanic Linguistics (CoOL) team. His research focuses on constructing phylogenetic trees of language relationships using Bayesian methods to explore language origins, spread, and evolutionary dynamics. He holds a BA in Natural Sciences from the University of Cambridge (UK), a PhD in Evolutionary Biology from Flinders University (Australia), and previously worked as a Postdoctoral Research Associate at Naturalis Biodiversity Center (Netherlands). King’s research interests bridge evolutionary biology, paleontology, and linguistics. He investigates evolutionary transitions in early vertebrates (e.g., placoderms, coelacanths) and applies computational models to study language evolution. His work emphasizes improving phylogenetic methodologies and integrating fossil evidence with statistical frameworks. Notable projects include analyzing Philippine language migrations and reconfiguring actinistian phylogenies through Devonian fish fossils. His publications reflect interdisciplinary strengths, combining vertebrate paleontology with linguistic phylogenetics. Recent work supports rapid Austronesian expansions and hybrid Indo-European language origins. Awards include the Oxford University Press Prize for Biosciences and recognition for his PhD publication. King actively engages in public science communication through platforms like The Conversation and GitHub repositories.

Timothy R. TangherliniView profile

Professor

• folklore
• Danish culture
• Danish cinema
• +9 more

Timothy R. Tangherlini serves as the Elizabeth H. and Eugene A. Shurtleff Chair in Undergraduate Education and Professor in the Department of Scandinavian and the School of Information at the University of California, Berkeley. A distinguished folklorist and ethnographer, he has pioneered computational approaches to folklore studies, bridging traditional humanities scholarship with cutting-edge digital methods. His research expertise spans multiple interconnected domains: Digital humanities and computational folkloristics Danish and Scandinavian cultural traditions Network analysis of narrative structures Machine learning applications in cultural analysis Conspiracy theory formation and transmission Korean cultural studies and K-Pop analysis Tangherlini's work focuses on how stories circulate across social networks and how individuals use narratives to negotiate ideology within their social groups. He has been instrumental in developing the field of Culture Analytics, co-directing a three-year program at the NSF's Institute for Pure and Applied Mathematics and leading the NEH's Institute for Advanced Topics in Digital Humanities on Network Analysis for the Humanities. His research combines ethnographic depth with computational sophistication, creating novel methodologies for analyzing large cultural corpora. His scholarly contributions have earned him significant recognition: Fellow of the American Folklore Society Fellow of the Royal Gustav Adolf Academy (one of Sweden's Royal Academies) Elizabeth H. and Eugene A. Shurtleff Chair in Undergraduate Education Tangherlini has secured substantial funding from prestigious organizations including the NEH, NSF, NIH, AFOSR, Mellon Foundation, Nordic Council of Ministers, and Google. His work on conspiracy theories, K-Pop choreography analysis, and historical Danish folklore has garnered media attention, demonstrating the public relevance of his research. With extensive international experience including appointments at the University of Copenhagen, University of Iceland, and Harvard University, he maintains a global scholarly perspective while contributing significantly to undergraduate education at Berkeley.

• Business Cycles
• Fiscal Policy
• Monetary Policy
• +3 more

Benjamin Born serves as Professor of Macroeconomics at Frankfurt School of Finance & Management and Research Director at the ifo Institute. He is a Research Fellow at CEPR and CESifo, advises the European Commission's DG ECFIN, serves on the European Parliament's Expert Group on Monetary Policy, and sits on the CEPR–EABCN Euro Area Business Cycle Dating Committee. Starting in September 2025, he will join the University of Bonn as Professor of Macroeconomics. Education PhD in Economics, 2011, University of Bonn, Germany MSc in Econometrics and Economics, 2007, University of York, UK BA/MA in Economics, 2006, University of Siegen, Germany Professor Born's research focuses on business cycles, fiscal and monetary policy, heterogeneous agent models, and empirical methods in macroeconomics. His work bridges theoretical modeling with empirical analysis, often using innovative data sources including firm surveys and social media data. He has made significant contributions to understanding how monetary policy affects different segments of the economy, how fiscal policy transmits through various channels, and how firms form expectations about the future. His recent publications reveal a strong trend toward analyzing heterogeneous effects in macroeconomics, particularly examining how different groups (firms, workers, consumers) respond differently to economic shocks and policies. His work increasingly incorporates social media data and novel survey methodologies to capture real-time economic behavior. A significant portion of his research addresses policy responses to the COVID-19 pandemic, including fiscal stimulus packages and lockdown effects. Professor Born is actively involved in the academic community, serving on the editorial boards of the Journal of Monetary Economics and the European Economic Review. He regularly organizes major academic conferences including the BASEforHANK Winterschool and the ifo Conference on Macroeconomics and Survey Data. Teaching and Supervision Currently teaches Macroeconomics II (first-year Ph.D. course at BGSE) Has taught Macroeconomics and Econometrics at all levels Supervises theses in macroeconomics and applied econometrics

Mona SinghView profile

Professor

• Computational Biology
• Machine Learning
• Algorithms
• +3 more

Mona Singh is a Professor of Computer Science at Princeton University, with affiliations to the Lewis-Sigler Institute for Integrative Genomics and the Department of Molecular Biology. She has been a faculty member since 1999. Ph.D., Massachusetts Institute of Technology, 1995 A.B. and S.M. degrees in Computer Science from Harvard University Her research focuses on computational molecular biology, integrating machine learning and algorithms to analyze biological networks, protein interactions, and mutational impacts. Key areas include DNA/RNA binding prediction, protein structure analysis, and network-based disease gene discovery. Her recent work highlights trends in protein language models, kinase-substrate prediction, and equitable MHC binding algorithms. These span sub-fields like structural bioinformatics, network biology, and functional genomics. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE) Rheinstein Junior Faculty Award ACM Fellow (2019) ISCB Fellow (2018) She has taught an introductory computational biology course with Professor Coleen Murphy, covering sequence analysis, phylogenetics, and network reconstruction. Her group has developed tools like dPUC , nCOP , and DiffMut . Her lab collaborates with institutions including Carnegie Mellon, Duke University, and the Broad Institute, advancing applications in cancer genomics, metabolic disease, and precision medicine.

Emilio FerraraView profile

Professor

• Artificial Intelligence
• Computational Social Science
• Network Analysis
• +5 more

Dr. Emilio Ferrara is a Professor of Computer Science & Communication at the University of Southern California, holding appointments in the Viterbi School of Engineering, Annenberg School for Communication and Journalism, and Keck School of Medicine. He serves as Associate Director of Applied Data Science at USC, Research Team Leader at the USC Information Sciences Institute, and Principal Investigator at the USC/ISI Machine Intelligence and Data Science (MINDS) group. His educational background includes a PhD in Machine Learning and BSc & MSc in Computer Science. Ferrara's research focuses on the intersection of artificial intelligence and computational social science, specifically using AI to model and predict human behavior in techno-social systems. His work spans social networks, machine learning, and network science with applications to understanding communication dynamics in digital environments. Ferrara has published over 150 articles in prestigious venues including Proceedings of the National Academy of Sciences, Communications of the ACM, and Physical Review Letters. His research has been widely featured in major news outlets and examines topics ranging from social media manipulation to AI ethics and online behavior. His scientific achievements have been recognized with numerous awards: 2019 Viterbi Scientific Award 2018 DARPA Director's Fellowship 2016 DARPA Young Faculty Award 2016 Complex Systems Society Junior Scientific Award 2015 IBM Watson Big Data Influencer Ferrara's research is supported by major funding agencies including DARPA, IARPA, Air Force, and Office of Naval Research. He leads the HUMANS LAB (Humans & Machines + Networks & Social Systems) which has trained numerous PhD students who have gone on to successful careers in academia and industry. His work on social bots, election integrity, and AI ethics continues to shape understanding of digital social dynamics.

• Science and Technology Studies
• Science Policy
• Gender Equity in STEM
• +6 more

Cassidy R. Sugimoto is the Tom and Marie Patton Professor and School Chair at the Jimmy and Rosalynn Carter School of Public Policy at Georgia Institute of Technology. She previously held a professorship in Informatics at Indiana University Bloomington (2010–2021) and served as Program Director for the Science of Science and Innovation Policy at the National Science Foundation (2018–2020). Her research focuses on knowledge production systems, equity in STEM, scientific collaboration dynamics, and research evaluation metrics. She holds degrees from the University of North Carolina at Chapel Hill including a B.Mus. in Music Performance, M.S. in Library Science, and Ph.D. in Information and Library Science. Research interests include: Structural inequities in science and technology Ethical authorship practices Global scientific collaboration patterns Open science initiatives Gender and diversity in academic careers Notable awards include the 2020 Bicentennial Service Award from Indiana University and 2014 Trustees Teaching Award. Her recent work examines intersectional disparities in science, AI ethics, and systemic barriers to equity in academic publishing. Key contributions include co-authoring Equity for Women in Science (2023) and foundational scholarship on alternative metrics beyond citation counts. She advises on science policy matters related to institutional equity and open access publishing.

• Visual Analytics
• Information Visualization
• Geographic Information Science
• +7 more

Jo Wood is Professor of Visual Analytics in the Department of Computer Science at City, University of London, where she has been employed since January 14, 2000. Her work bridges computer science, geographic information science, and human-computer interaction, focusing on innovative methods for visualizing complex spatial and behavioral data. Her research interests center on visual analytics , information visualization , and geovisualization , with applications in transportation, public health, crisis response, and citizen science. She investigates how interactive visual interfaces can support exploratory data analysis, decision-making, and storytelling, particularly through small multiples, faceted views, and sketch-based rendering techniques. The trends in her recent publications reflect a consistent focus on user-centered design , spatial data abstraction , and interactive exploration of multivariate datasets. Her work often integrates real-world behavioral data such as GPS tracks, cycling patterns, and crowd-sourced information to build meaningful visual narratives and support analytical reasoning. Throughout her career, Jo Wood has contributed significantly to the advancement of visual analytics through high-impact publications in top-tier venues such as IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum. Her collaborations with researchers like Jason Dykes and Aidan Slingsby highlight her role in a vibrant research community. She has supervised numerous research projects and mentored students in visualization and geospatial analytics, though specific names are not listed in the provided text. Her work has been supported by various research grants, particularly in domains involving urban mobility, energy modeling, and crisis informatics, though grant details are not specified here. Jo Wood has also contributed to the design of visual analytics systems for applications including disease spread modeling, bicycle-hire scheme monitoring, and persuasive technology for health and leisure, demonstrating a strong commitment to impactful, interdisciplinary research.

Yoel InbarView profile

Associate Professor

• Social Psychology
• Moral Psychology
• Political Ideology
• +3 more

Yoel Inbar is an Associate Professor at the University of Toronto, affiliated with the Department of Psychology and the Morality, Affect, and Politics (MAP) Lab. His research explores the intersection of moral intuitions, emotions, and political/social beliefs, with a focus on disgust sensitivity and its implications. He also investigates public acceptance of emerging technologies like genetic engineering. Contact: yoel.inbar@utoronto.ca . PhD, Cornell University BA, University of California at Berkeley His research spans moral psychology, political ideology, and behavioral responses to technological innovation. Recent studies employ natural language processing to analyze morality in real-world contexts, such as political discourse and environmental attitudes. The MAP Lab emphasizes interdisciplinary approaches, integrating psychology, behavioral economics, and computational methods to study moral decision-making and its societal consequences. Alumni from the lab include researchers now at institutions like UC Berkeley, University of the Fraser Valley, and Cornell University, reflecting his mentorship of advanced psychological and behavioral science scholars.