Orestis has a master's degree in civil engineering from the National Technical University of Athens and a master’s degree in philosophy of science and technology from the Technical University of Munich. He received a Ph.D. in computer science with a focus in computational social science from the Technical University of Munich. In 2019-20 he was a visiting scholar at the Massachusetts Institute of Technology’s Center for Civic Media, where he used natural language processing methods to evaluate media ecosystems. In 2020-22 Orestis was a postdoctoral research associate at the Center for Information Technology Policy at Princeton University studying issues of algorithmic fairness, platform design & tech policy.
My research showcases political issues and provides ideas, frameworks, and practical solutions towards just, inclusive and participatory socio-algorithmic ecosystems through the application of data-intensive algorithms and social theories. At Sony AI, I focus on understanding, quantifying, and mitigating algorithmic biases and harms in natural and spoken language processing technologies. My goal is to create algorithmic solutions that empower users and promote civic values.
Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit
A significant share of political discourse occurs online on social media platforms. Policymakers and researchers try to understand the role of social media design in shaping the quality of political discourse around the globe. In the past decades, scholarship on political di…
Considerations for Ethical Speech Recognition Datasets
Speech AI Technologies are largely trained on publicly available datasets or by the massive web-crawling of speech. In both cases, data acquisition focuses on minimizing collection effort, without necessarily taking the data subjects’ protection or user needs into considerat…
AI-Competent Individuals and Laypeople Tend to Oppose Facial Analysis AI
Recent advances in computer vision analysis have led to a debate about the kinds of conclusions artificial intelligence (AI) should make about people based on their faces. Some scholars have argued for supposedly ``common sense'' facial inferences that can be reliably drawn …
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