MDS Alumni

I’m broadly interested in understanding how public data curators embed socially desirable values like privacy and confidentiality protections, equity, and reproducibility into their data publishing practices. My methodological research combines tools from theoretical computer science and computational social science to design and characterize complex structured errors induced by these practices. In doing so, I aim ...

The labor market is a setting increasingly disrupted by AI (both in allocation of wages and of jobs) and yet understudied in the ethical AI research space. My research agenda has been focused on the combination of unsupervised learning methods, from network theory, and discrete choice tools, in order to improve the understanding of labor ...

My research focuses on applications of computational methods to better understand human behaviors. One of my main projects applies natural language processing methods to examine interactions in an online substance use recovery group to better understand substance use recovery pathways, mental health, and social relationships. Accomplishments and Awards Sandy Hook Promise, University Of Michigan School ...

My background is in applied mathematics and my primary research interest centers on developing algorithms and methodologies for data science using machine learning. More specifically, I am focused on developing algorithms for multidimensional multimodal big data which find primary application in medicine yet it is generalizable to other branches where bid data emerge.  My current ...

Stephen Ajwang is a Tutorial Fellow in the Department of Informatics and Information Science at Rongo University, Kenya, where he also received his MSc in Information Technology. He is also pursuing a PhD in Information Technology. His research interest lies in the realm of Big data analytics for climate smart agriculture. The increasing volume of ...

efrén studies the way algorithms reproduce bias and discrimination. Automated procedures are often designed to mimic the historical data humans have generated. Therefore, unintendedly, they have learned to discriminate based on class, race, gender, and other vulnerable groups. Such a phenomenon has serious consequences, as it may lead to furthering economic inequality, depriving the poor ...

Intelligent systems behaviors, usually concealed, are almost everywhere nowadays: human-like virtual interactions, responsive financial systems, flexible traffic allocation, and more. Beneath the surface, intelligent systems encompass the developments of learning, abstraction and inference, of which large amounts of data are the core. My research focuses on developing online-data-driven approaches to support theoretical and algorithmic foundations ...