Ágnes Horvát, Assistant Professor
Agnes develops network and data science approaches to understand and support collective intelligence in Web-based systems. Capitalizing on her background in physics, computer science, film and media, her work uses a multidisciplinary empirical approach to uncover the dynamics of success in knowledge creation and cultural markets, as well as to identify expressions of the wisdom of crowds that facilitate decision-making and innovation.
Henry Dambanemuya (Technology and Social Behavior)
Henry’s research examines potential ways in which machine learning, complex networks analysis and computational social science can be harnessed for social innovation. The core premise of his work has broad implications for how modern civilisations can effectively coordinate their responses and communication strategies in high-stakes real-world challenges, such as peace agreements and capital allocation in online crowdfunding.
Keywords : Applied Machine Learning, Complex Networks, Computational Social Science
Rod Abhari (Media, Technology, and Society)
Rod Abhari analyzes the diffusion of scientific (mis)information across online platforms. In doing so, he aims to both improve the accuracy of scientific reporting and combat the spread of science-based populism. He holds an M.A. in Communications from the University of Wisconsin – Madison and an M.A. in Science and Technology Studies (STS) from the University of Maastricht in the Netherlands.
Keywords : Science and Health Communication, Methods for Social Change, Hyperlink Analysis
Katherine O’Toole (Technology and Social Behavior)
Katherine’s research focused on the effects that technology and computing have on larger social networks and group behavior, as well as the ability of technology to connect us and change the way ideas are developed and disseminated. Her research focuses on developing a better understanding of creativity, especially within existing social contexts and networks, and applying this knowledge to design tools that will help users be more innovative and creative.
Keywords : Complex Network Analysis, Human-Computer Interaction, Social Computing
Nick Hagar (Media, Technology, and Society)
Nick Hagar is a PhD student working with Dr. Nick Diakopoulos in the Computational Journalism Lab. His research examines the business of news, with a focus on the labor of journalists. His current project uses computational methods to examine the link between freelancer career trajectories and news content. Nick holds a BS in Journalism from Northwestern University.
Julie Barnett (Technology and Social Behavior)
Julia’s research interests lie in natural language processing applications in social contexts, algorithmic transparency and bias, and the intersection of machine learning and music. Her current work examines the ethical impact of algorithmic decision making systems and how we can anticipate these varying impacts through the use of participatory foresight. Julia earned an MS in Data Science from the Barcelona Graduate School of Economics and a BBA from Villanova University.
Yixue Wang (Technology and Social Behavior)
Yixue analyzes human behavioral data as a means to enhance diversity, maintain civility and eliminate biases. She is specifically interested in promoting online deliberation, supporting journalistic sourcing practices via online comments, designing article-level news personalization, and promoting gender equality in the music industry.
Keywords : Computational Journalism, Computational Social Science, Human-Computer Interaction
Sohyeon Hwang (Media, Technology, and Society)
Sohyeon’s research interests center around understanding the complexity of governing heterogeneous online spaces. One line of her work examines the dynamics and significance of localized governance mechanisms and another line focuses on information distortion as content moves across such spaces.
Keywords : Online Governance, Social Computing, Information Distortion, Complexity
Herminio Bodon (Technology and Social Behavior)
Herminio’s research interests are in Science of Science, Applied Machine Learning, and Collective Intelligence. His work applies data science to study scientific discussions on different social media platforms. Currently he is studying who is more likely to share and discuss scientific papers on Twitter.
Johannes Wachs (Vienna University of Economics and Business)
Johannes is an assistant professor at the Vienna University of Economics and Business. He is also a faculty member at the Complexity Science Hub. He studies social, technical, and economic networks and their effects on society using methods of data and network science. Currently he is studying how software systems and their creators shape the digital economy. He has a PhD in Network Science from Central European University, and has been affiliated with RWTH Aachen University and the Oxford Internet Institute.
Orsolya holds a Ph.D in Network & Data Science from the Central European University in Vienna, Austria. She is a Computational Social Scientist with a background in Statistics and Sociology. She is an ambassador and advisory board member of the Global Women in Data Science Initiative at Stanford University, and member of the Data Science for Social Good Alumni. Previously she was a postdoctoral Researcher at the University of Warwick, CIM, currently she is a research fellow at the NETI Lab at Corvinus University of Budapest. Her research focuses on how network and data science can lead to a better understanding of unconscious bias in STEM.
- Orsolya Vásárhelyi, University of Warwick
- Eunseo (Dana) Choi, MIT
- Igor Zakhlebin, 3RedPartners, Chicago
- Gaoyuan (Louis) Huang, Visa Inc.
- Isabella Loaiza-Saa, MIT Media Lab
- Melanie De Vincentiis, Sciences Po
- Kyosuke Tanaka, Aarhus University
- Haomin Lin, Georgia Institute of Technology