Faculty
Giannis Daras is an Assistant Professor at MIT Sloan as part of the Operations Research and Statistics group. Giannis obtained his PhD from the computer science Department of UT Austin under the supervision of Alex Dimakis and did his postdoc at MIT under the supervision of Antonio Torralba and Costis Daskalakis.
Giannis works on important practical and theoretical questions around deep generative models with a focus on training and sampling generative models in the presence of data corruption.
He has been nominated as a Rising Star in AI by the University of Michigan, has earned the Best Contribution Award at the Biomedical and Astronomical Signal Processing (BASP) Conference, and has published 23 research papers (including 13 first-author works) at top-tier Machine Learning venues, including one Oral Presentation (top 0.3%) and two Spotlight presentations (top 3.2%) at NeurIPS. Giannis has also been supported by multiple fellowships, including the Graduate Dean’s Prestigious Fellowship (UT Austin), Onassis, Bodossakis, Leventis, and Gerondellis PhD Fellowships. His work has sparked the interest of the public following coverage by news outlets such as The Independent and the New York Post. His work has found applications across scientific fields such as Computer Vision, Computational Biology, Medical Imaging, Robotics, Economics, and Neuroscience.
Featured Publication
"Ambient Diffusion Omni: Training Good Models with Bad Data."Giannis Daras, Adrian Rodriguez-Munoz, Adam Klivans, Antonio Torralba, and Constantinos Daskalakis. In Advances in Neural Information Processing Systems: Spotlight, San Diego, CA: 2025. Download Preprint.
Featured Publication
"Ambient Proteins: Training Diffusion Models on Low Quality Structures."Daras, Giannis, Jeffrey Zhang, Krithika Ravishankar, William Daspit, Costis Daskalakis, Qiang Liu, Adam Klivans, and Daniel Diaz. In Advances in Neural Information Processing Systems: Spotlight, San Diego, CA: 2025. Download Preprint.
Adrian Rodriguez-Munoz, William Daspit, Adam Klivans, Antonio Torralba, Constantinos Daskalakis, and Giannis Daras. In 43rd International Conference on Machine Learning, Seoul, South Korea: July 2026. arXiv.
Wei, Adam, Nicholas Pfaff, Thomas Cohn, Arif Kerem Dayı, Constantinos Daskalakis, Giannis Daras, and Russ Tedrake, MIT Sloan Working Paper 7387-26. Cambridge, MA: MIT Sloan School of Management, June 2026.
Hosseintabar, Danial, Fan Chen, Giannis Daras, Antonio Torralba, and Constantinos Daskalakis, MIT Sloan Working Paper 7386-25. Cambridge, MA: MIT Sloan School of Management, December 2025.
Hui Ren, Joanna Materzynska, Rohit Gandikota, David Bau, and Antonio Torralba. In 39th Annual Conference on Neural Information Processing Systems Creative AI Track: Humanity, San Diego, California: September 2025. arXiv.
Debiased machine learning, the currency of invoicing, and training good models with bad data: Meet the new experts bringing their knowledge and skill sets to the MIT Sloan School of Management.
