Full Bio

Peter Richtarik is a professor of Computer Science at the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, where he leads the Optimization and Machine Learning Lab. At KAUST, he has a courtesy affiliation with the Applied Mathematics and Computational Sciences program and the Statistics program, and is a member of the Visual Computing Center, and the Extreme Computing Research Center. Prof Richtarik is a founding member and a Fellow of the Alan Turing Institute (UK National Institute for Data Science and Artificial Intelligence), and an EPSRC Fellow in Mathematical Sciences. During 2017-2019, he was a Visiting Professor at the Moscow Institute of Physics and Technology. Prior to joining KAUST, he was an Associate Professor of Mathematics at the University of Edinburgh, and held postdoctoral and visiting positions at Université Catholique de Louvain, Belgium, and University of California, Berkeley, USA, respectively. He received his PhD in 2007 from Cornell University, USA.

Prof Richtarik’s research interests lie at the intersection of mathematics, computer science, machine learning, optimization, numerical linear algebra, and high-performance computing. Through his work on randomized and distributed optimization algorithms, he has contributed to the foundations of machine learning, optimization and randomized numerical linear algebra. He is one of the original developers of Federated Learning – a new subfield of artificial intelligence whose goal is to train machine learning models over private data stored across a large number of heterogeneous devices, such as mobile phones or hospitals, in an efficient manner, and without compromising user privacy. In an October 2020 Forbes article, and alongside self-supervised learning and transformers, Federated Learning was listed as one of three emerging areas that will shape the next generation of Artificial Intelligence technologies.

Prof Richtárik’s works attracted international awards, including the Charles Broyden Prize, a Distinguished Speaker Award at the 2019 International Conference on Continuous Optimization, the SIAM SIGEST Best Paper Award (joint with O. Fercoq), the IMA Leslie Fox Prize (second prize, three times, awarded to two of his students and a postdoc), and a Best Paper Award at the NeurIPS 2020 Workshop on Scalability, Privacy, and Security in Federated Learning (joint with S. Horvath). Several of his works are among the most read papers published by the SIAM Journal on Optimization and the SIAM Journal on Matrix Analysis and Applications. Prof Richtárik regularly serves as an Area Chair for leading machine learning conferences, including NeurIPS, ICML and ICLR, and is an Action Editor of the Journal of Machine Learning Research (JMLR), Associate Editor of Optimization Methods and Software and Numerische Mathematik, and a Handling Editor of the Journal of Nonsmooth Analysis and Optimization. In the past, he served as an Action Editor of Transactions of Machine Learning Research and an Area Editor of Journal of Optimization Theory and Applications.

Medium Bio

Peter Richtárik is a professor of Computer Science at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia, where he leads the Optimization and Machine Learning Lab. His research interests lie at the intersection of mathematics, computer science, machine learning, optimization, numerical linear algebra, and high-performance computing. Through his work on randomized and distributed optimization algorithms, he has contributed to the foundations of machine learning, optimization and randomized numerical linear algebra. He is one of the original developers of Federated Learning. Prof Richtárik’s works attracted international awards, including the Charles Broyden Prize, SIAM SIGEST Best Paper Award, Distinguished Speaker Award at the 2019 International Conference on Continuous Optimization, the IMA Leslie Fox Prize (three times), and a Best Paper Award at the NeurIPS 2020 Workshop on Scalability, Privacy, and Security in Federated Learning. Several of his works are among the most read papers published by the SIAM Journal on Optimization and the SIAM Journal on Matrix Analysis and Applications. Prof Richtárik serves as an Area Chair for leading machine learning conferences, including NeurIPS, ICML and ICLR, and is an Action Editor of JMLR, and Associate Editor of Numerische Mathematik and Optimization Methods and Software. In the past, he served as an Action Editor of TMLR and an Area Editor of JOTA.

Short Bio

Peter Richtárik is a professor of Computer Science at KAUST, Saudi Arabia, where he leads the Optimization and Machine Learning Lab. Through his work on randomized and distributed optimization algorithms, he has contributed to the foundations of machine learning and optimization. He is one of the original developers of Federated Learning. Prof Richtárik’s works attracted international awards, including the Charles Broyden Prize, SIAM SIGEST Best Paper Award, and a Distinguished Speaker Award at the 2019 International Conference on Continuous Optimization. He serves as an Area Chair for leading machine learning conferences, including NeurIPS, ICML and ICLR, and is an Action Editor of JMLR, and Associate Editor of Numerische Mathematik, and Optimization Methods and Software.

Very Short Bio

Peter Richtárik is a professor of Computer Science at KAUST, Saudi Arabia, where he leads the Optimization and Machine Learning Lab. Through his work on randomized and distributed algorithms, he has contributed to the foundations of optimization, machine learning, and federated learning. Prof Richtárik serves as an Area Chair for leading machine learning conferences, including NeurIPS, ICML and ICLR, is an Editor of several journals (e.g., JMLR and Numerische Mathematik), and is the recipient of numerous international awards.

Current Appointments

Past Appointments

Education

  • PhD, Operations Research, Cornell University, 2002–2007, advisor: Mike Todd
  • MS, Operations Research, Cornell University, 2006
  • Mgr, Mathematics, Comenius University, Faculty of Mathematics, Physics & Informatics, 2001 (ranked 1)
  • Bc, Management, Comenius University, Faculty of Management, 2000 (ranked 1)
  • Bc, Mathematics, Comenius University, Faculty of Mathematics, Physics & Informatics, 2000 (ranked 1)

Service (Selected)

CV