Nathan Kallus

Nathan Kallus is a highly accomplished individual with a diverse background in academia, research, and industry. His interests span various areas such as personalization, optimization, causal inference, algorithm fairness, and more. Nathan holds a PhD in Operations Research from the Massachusetts Institute of Technology (MIT), a BS in Computer Science and Engineering, and a BA in Mathematics from the University of California, Berkeley.

Having worked at prestigious institutions, Nathan has held positions like Associate Professor at Cornell University, Research Director and Senior Research Scientist at Netflix, and Machine Learning Consultant at Cuebiq. His academic journey includes roles like Assistant Professor at Cornell University, Visiting Scholar at the University of Southern California, and Postdoctoral Associate at MIT. Nathan has also contributed to industry in roles such as Data Scientist at Recorded Future, Software Development Engineer at Microsoft, and Summer Analyst at Goldman Sachs.