Emre Kiciman

I am a Senior Principal Researcher at Microsoft Research AI in the information and data sciences group.  My research interests span causal inference, machine learning, and AI’s implications for people and society.

I am working to broaden the use of causal methods for decision-making across many application domains; and improving current applications of correlational machine learning through causal insights.  My work uses machine learning methods to scale up conventional causal inference techniques to handle larger-scale and higher-dimensional datasets; adapt causal inference methods to new settings; and improve the robustness and bias of prediction and classification algorithms using causal or causal-inspired approaches.

In the broad area of AI’s implications for society, my work promotes positive applications of AI and strives to mitigate its negative implications.  My projects include work at the intersection of security and machine learning, studying new attacks and defenses on security-critical AI-driven systems in an end-to-end setting; questions of data biases and their implications; and infrastructure and methods for developing and maintaining privacy-preserving AI-driven systems; misinformation; and other topics.

I have a  strong interest in computational social science questions and social media analyses, especially that require causal understanding of phenomenon in health, mental health; issues of data bias; and understanding how new technologies affect our awareness of the world and enable new kinds of information discovery and retrieval.

My past research has included the reliability, architecture, and operations of distributed systems, including some of the first work to apply machine learning methods to challenges of fault detection and diagnosis in large-scale systems; monitoring and optimization of web applications; and various information retrieval-related tasks, such as entity-linking and using social context to inform document ranking.  I received my Ph.D. and my M.S. from Stanford University, and my B.S. in Electrical Engineering and Computer Science from U.C. Berkeley.