Athresh Karanam

I am an AI researcher at the University of Texas at Dallas, where I recently graduated with my Ph.D. in computer science. My research focuses on deep generative models, tractable probabilistic inference, knowledge-based systems, causal inference, and data- and compute-efficient learning, with an emphasis on building machine learning methods that are both practically effective and theoretically grounded, including applications of AI in healthcare.

I am particularly interested in settings where data are limited, noisy, or costly to acquire, and in developing approaches that make learning more reliable and interpretable. My work also explores applications of AI in healthcare, where these challenges are especially important, as well as methods in explainable AI that help make complex models more transparent and trustworthy. More broadly, I am interested in advancing machine learning systems that are efficient, principled, and impactful in critical real-world domains. My research has been published at various AI/ML conferences including NeurIPS, AAAI, and PGM.