معرفی
Murat Kocaoglu is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. His work focuses on causal inference, machine learning, generative adversarial networks, information theory, and learning theory. He is affiliated with Purdue's West Lafayette campus, with an office in MSEE 362 and maintains a research webpage at muratkocaoglu.com.
Research interests span causal discovery methods, fair machine learning, and applications in signal processing and communications. His work bridges theoretical foundations with practical algorithms, emphasizing causal reasoning in complex systems and high-dimensional data.
Recent articles explore causal graph learning, counterfactual fairness, and adaptive experimental design. Key contributions include frameworks for efficient causal structure discovery and methods for handling unobserved confounders in bandit problems. His research has been supported by grants such as NSF CAREER and NSF RI Small awards.
No awards or student advisees are explicitly listed in the provided materials. His professional activities include contributions to the CausalGAN framework and collaborative work on causal inference in time series and microservices.
