| Ruslan Salakhutdinov | |
| Fields: | Computer science Artificial intelligence |
| Workplaces: | Carnegie Mellon University |
| Alma Mater: | University of Toronto |
| Thesis Title: | Learning deep generative models |
| Thesis Url: | https://librarysearch.library.utoronto.ca/permalink/01UTORONTO_INST/14bjeso/alma991106499151406196 |
| Thesis Year: | 2009 |
| Doctoral Advisor: | Geoffrey Hinton |
Ruslan Salakhutdinov (Russian: Руслан Салахутдинов; born 1980) is a Canadian researcher of Tatar origin working in the field of artificial intelligence.
He specializes in deep learning, probabilistic graphical models, and large-scale optimization.[1]
Salakhutdinov's doctoral advisor was Geoffrey Hinton.[2] Salakhutdinov was considering quitting the field of artificial intelligence when he met Hinton in 2004, but changed his mind after Hinton asked him to take part in a project focused on a new way to train artificial neural networks, which he dubbed "deep belief networks." This research made a large impact on the field of deep learning.[3]
He received his PhD in 2009.[4]
He is well known for having developed Bayesian Program Learning.[2]
Salakhutdinov is a professor of computer science at Carnegie Mellon University.[5]
Since 2009, he has published at least 42 papers on machine learning.[6]
Salakhutdinov joined Apple as its director of AI research in 2016 but left in 2020 to return to Carnegie Mellon University.[7] [8]
In June 2023, Salakhutdinov joined Felix Smart which is a company that uses AI to take care for plants and animals as Board Director.[9]