
Marco Cusumano-Towner
Email / GitHub / Google ScholarComputer scientist specializing in probabilistic AI.
I am a research scientist at Apple working with Vladlen Koltun.
I completed my PhD in EECS at MIT, where I was advised by Vikash Mansinghka and Josh Tenenbaum.
During my PhD I created the Gen probabilistic programming system.
Before MIT, I was a technical lead at an early stage molecular diagnostics startup backed by Sequoia Capital,
I completed my MS in computer science at Stanford University
and my BS in electrical engineeering and computer science at UC Berkeley,
where I worked with Pieter Abbeel on probabilistic robotics.
My graduate school research was funded by the NSF graduate research fellowship and the NDSEG graduate fellowship program, among other sources.
PhD Thesis
Gen: A High-Level Programming Platform for Probabilistic Inference (PDF), PhD thesis, Massachusetts Institute of Technology, 2020.
Publications
![]() The 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022)
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![]() The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022)
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![]() Thirty-first Conference on Neural Information Processing Systems (NeurIPS 2021)
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![]() 47th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL 2020)
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![]() 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2019)
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![]() 46th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL 2019)
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![]() NeurIPS 2019 Workshop on Perception as Generative Reasoning.
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![]() 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2018)
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![]() arXiv 2018
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![]() Thirty-first Conference on Neural Information Processing Systems (NeurIPS 2017)
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![]() Journal of the American Medical Informatics Association. 2013.
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![]() 2011 IEEE International Conference on Robotics and Automation (ICRA 2011)
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![]() 2010 IEEE International Conference on Robotics and Automation (ICRA 2010)
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