About Peter Richtarik Peter Richtarik Professor, Computer Science optimization machine learning big data algorithms Professor Richtárik specializes in big data optimization and machine learning. He is known for his work on randomized coordinate descent algorithms, stochastic gradient descent and federated learning. Articles Related News January 2026 KAUST professor Peter Richtárik receives Charles Broyden Prize for second consecutive year 2 min read · Wed, Jan 21 2026 Awards News optimization machine learning communication efficiency artificial intelligence big data algorithm The prize honors work advancing communication-efficient optimization for large-scale distributed learning systems. November 2025 KAUST advances scalable AI through global collaboration 1 min read · Wed, Nov 12 2025 News Clip News machine learning LLM Federated learning Distributed algorithms KAUST brings global experts together to advance scalable AI and tackle the challenges of training large models. September 2024 KAUST Center of Excellence for Generative AI 1 min read · Thu, Sep 12 2024 News Clip News KAUST has established the Center of Excellence for Generative AI to position Saudi Arabia as a leader in this transformative technology, aligning with Vision 2030's goals for human capital development and economic diversification while focusing on research and applications that span health, sustainability, energy, and future economies, ultimately aiming to cultivate talent and foster innovative solutions tailored to the Kingdom’s needs. October 2021 KAUST paper wins 2020 Computational Optimization and Applications Best Paper Award 1 min read · Tue, Oct 12 2021 News stochastic gradient descent machine learning KAUST Professor of Computer Science Peter Richtárik and his former student Nicolas Loizou, currently a postdoctoral researcher at Mila - Quebec Artificial Intelligence Institute and soon to take up an assistant professorship position at Johns Hopkins University, recently received the 2020 Computational Optimization and Applications (COAP) Best Paper Award. June 2021 KAUST VCC research scientist appointed as Associate Editor of leading IEEE journal 4 min read · Thu, Jun 3 2021 News Laurent Condat, a research scientist based in the KAUST Visual Computing Center, has recently been appointed as an Associate Editor of IEEE Transactions on Signal Processing (TSP). The peer-reviewed journal covers novel theory, algorithms, performance analyses, and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. Algorithmic, Systems and Privacy Aspects of Split Learning 1 min read · Tue, Jun 1 2021 News Federated learning (FL) is a new machine learning setting introduced in 2016 in a sequence of papers resulting from a collaboration between a Google team led by Brendan McMahan and Peter Richtarik’s group. Key idea: Many clients (e.g., mobile phones, IoT devices or organizations) collaboratively train a machine learning model under the orchestration of a central trusted server, while keeping the training data stored on the client devices in a decentralized fashion in order to protect privacy. Split learning (SL) is a new federated learning tool specifically developed for training of deep May 2021 KAUST Ph.D. Student receives 2020 Ilya Segalovich Scientific Prize for Young Researchers 1 min read · Mon, May 10 2021 News KAUST Ph.D. student Dmitry Kovalev has been named one of nine recipients of the 2020 Ilya Segalovich Scientific Prize for Young Researchers. Awarded by the Russian multinational corporation Yandex, Dmitry received the accolade for his “significant advances in computer science.” September 2020 Meet KAUST student: Grigory Malinovsky 2 min read · Mon, Sep 21 2020 News machine learning optimization Grigory Malinovsky joined KAUST this fall as a M.S./Ph.D. candidate and member of Professor Peter Richtarik's Optimization and Machine Learning Lab. Grigory holds a bachelor's degree in applied mathematics and physics from the Moscow Institute of Physics and Technology, Russia. Malinovsky first came to KAUST as a visiting student and was instantly impressed by the research facilities and working atmosphere. His outstanding internship experience was a catalyst in choosing KAUST as the next step in his academic career. Meet KAUST student: Konstantin Burlachenko 1 min read · Wed, Sep 9 2020 News machine learning artificial intelligence Konstantin Burlachenko holds a master’s degree in computer science from Bauman Moscow State Technical University (BMSTU), Russia. After graduating from BMSTU, he worked in several prominent Moscow companies, such as Huawei, NVIDIA, and Yandex. He joined KAUST in August 2020 as a Ph.D. candidate and member of Professor Peter Richtarik's Optimization and Machine Learning Lab. August 2020 Meet KAUST prospective student: Reem Alghamdi 1 min read · Mon, Aug 31 2020 News machine learning Reem Alghamdi is a computer science graduate from Princess Nourah bint Abdulrahman University, Saudi Arabia. Reem will join KAUST this fall as a M.S. candidate under the supervision of Professor Peter Richtarik. Meet KAUST Prospective Student: Igor Sokolov 2 min read · Sun, Aug 9 2020 News machine learning optimization Igor Sokolov, 23, is an applied mathematics and physics graduate who will join KAUST from the Moscow Institute of Physics and Technology, Russia. Igor first came to KAUST as a visiting student in 2019 and was highly impressed by the University's living and working facilities. It was this first impression that prompted him to pursue an M.S. at KAUST. Sokolov will join KAUST in the Fall of 2020 as an M.S. candidate under the supervision of Professor Peter Richtarik. May 2020 KAUST CS student recognized with AAAI Outstanding Program Committee Award 4 min read · Sun, May 3 2020 News artificial intelligence Konstantin Mishchenko, a Ph.D. student under the supervision of Professor Peter Richtárik, has been selected as one of the Association for the Advancement of Artificial Intelligence’s (AAAI) 12 Outstanding Program Committee Members for 2020. Mishchenko was presented with a certificate in recognition of his outstanding service at AAAI-20 held in New York from February 7-12. January 2020 KAUST Ph.D. student Jinhui Xiong wins best paper award 1 min read · Thu, Jan 23 2020 News Spotlight Computer Vision modeling visualization computer graphics KAUST computer science Ph.D. student Jinhui Xiong recently won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization. The symposium took place from September 30 to October 2, 2019, at the University of Rostock, Germany, and provided the opportunity for researchers to discuss a wide range of topics in computer science, including computer graphics, vision, visualization and visual analytics. December 2019 Jinhui Xiong wins Best Paper Award at VMV 2019 2 min read · Mon, Dec 2 2019 News Spotlight computational imaging 3D reconstruction Fourth-year computer science Ph.D. student Jinhui Xiong won the best paper award at this year’s 24th International Symposium on Vision, Modeling, and Visualization (VMV) 2019. November 2019 Machine learning models gather momentum 1 min read · Sun, Nov 24 2019 News algorithms machine learning Computer science New methods for training machine learning models are quicker and more accurate than current approaches, previously considered state-of-the-art. October 2019 Less chat leads to more work for machine learning 2 min read · Wed, Oct 16 2019 News machine learning Computer science Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale. September 2019 KAUST Professor Peter Richtárik wins Distinguished Speaker Award 4 min read · Sun, Sep 15 2019 Awards Spotlight News optimization machine learning big data Peter Richtárik, KAUST professor of computer science, recently received a Distinguished Speaker Award at the Sixth International Conference on Continuous Optimization (ICCOPT 2019) held in Berlin from August 3 to 8. ICCOPT 2019 was organized by the Mathematical Optimization Society and was hosted this year by the Weierstrass Institute for Applied Analysis and Stochastics. July 2019 Accelerating the grapevine effect 1 min read · Sun, Jul 7 2019 News optimization machine learning big data By looking at classical gossip algorithms from a novel perspective, KAUST Professor Peter Richtarik has found a way to significantly speed up gossip-based information sharing, and in the process, he discovered new applications for this efficient mathematical approach. Gossip involves the sharing of information between individuals in a network and can be applied mathematically in both human social networks and data networks, such as distributed sensors. “A network is a collection of nodes, each connected to other nodes via links,” explains Richtarik. “In social networks, for instance October 2018 KAUST master’s degree student wins best poster award at Data Science Summer School 1 min read · Thu, Oct 11 2018 Awards News student award Samuel Horváth, a master's degree student in the University's statistics and optimization M.S./Ph.D. program, recently won a best poster award at the second edition of the Data Science Summer School (DS3). The event took place in Paris from June 25 to 29, and is one of the largest global data science summer schools. It was co-organized by the Data Science Initiative of École Polytechnique and DATAIA Institute. The primary goal of DS3 was to provide a series of courses and practical sessions covering the latest advances in the field of data science. Five hundred students, postdoctoral fellows
KAUST professor Peter Richtárik receives Charles Broyden Prize for second consecutive year 2 min read · Wed, Jan 21 2026 Awards News optimization machine learning communication efficiency artificial intelligence big data algorithm The prize honors work advancing communication-efficient optimization for large-scale distributed learning systems.
KAUST advances scalable AI through global collaboration 1 min read · Wed, Nov 12 2025 News Clip News machine learning LLM Federated learning Distributed algorithms KAUST brings global experts together to advance scalable AI and tackle the challenges of training large models.
KAUST Center of Excellence for Generative AI 1 min read · Thu, Sep 12 2024 News Clip News KAUST has established the Center of Excellence for Generative AI to position Saudi Arabia as a leader in this transformative technology, aligning with Vision 2030's goals for human capital development and economic diversification while focusing on research and applications that span health, sustainability, energy, and future economies, ultimately aiming to cultivate talent and foster innovative solutions tailored to the Kingdom’s needs.
KAUST paper wins 2020 Computational Optimization and Applications Best Paper Award 1 min read · Tue, Oct 12 2021 News stochastic gradient descent machine learning KAUST Professor of Computer Science Peter Richtárik and his former student Nicolas Loizou, currently a postdoctoral researcher at Mila - Quebec Artificial Intelligence Institute and soon to take up an assistant professorship position at Johns Hopkins University, recently received the 2020 Computational Optimization and Applications (COAP) Best Paper Award.
KAUST VCC research scientist appointed as Associate Editor of leading IEEE journal 4 min read · Thu, Jun 3 2021 News Laurent Condat, a research scientist based in the KAUST Visual Computing Center, has recently been appointed as an Associate Editor of IEEE Transactions on Signal Processing (TSP). The peer-reviewed journal covers novel theory, algorithms, performance analyses, and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals.
Algorithmic, Systems and Privacy Aspects of Split Learning 1 min read · Tue, Jun 1 2021 News Federated learning (FL) is a new machine learning setting introduced in 2016 in a sequence of papers resulting from a collaboration between a Google team led by Brendan McMahan and Peter Richtarik’s group. Key idea: Many clients (e.g., mobile phones, IoT devices or organizations) collaboratively train a machine learning model under the orchestration of a central trusted server, while keeping the training data stored on the client devices in a decentralized fashion in order to protect privacy. Split learning (SL) is a new federated learning tool specifically developed for training of deep
KAUST Ph.D. Student receives 2020 Ilya Segalovich Scientific Prize for Young Researchers 1 min read · Mon, May 10 2021 News KAUST Ph.D. student Dmitry Kovalev has been named one of nine recipients of the 2020 Ilya Segalovich Scientific Prize for Young Researchers. Awarded by the Russian multinational corporation Yandex, Dmitry received the accolade for his “significant advances in computer science.”
Meet KAUST student: Grigory Malinovsky 2 min read · Mon, Sep 21 2020 News machine learning optimization Grigory Malinovsky joined KAUST this fall as a M.S./Ph.D. candidate and member of Professor Peter Richtarik's Optimization and Machine Learning Lab. Grigory holds a bachelor's degree in applied mathematics and physics from the Moscow Institute of Physics and Technology, Russia. Malinovsky first came to KAUST as a visiting student and was instantly impressed by the research facilities and working atmosphere. His outstanding internship experience was a catalyst in choosing KAUST as the next step in his academic career.
Meet KAUST student: Konstantin Burlachenko 1 min read · Wed, Sep 9 2020 News machine learning artificial intelligence Konstantin Burlachenko holds a master’s degree in computer science from Bauman Moscow State Technical University (BMSTU), Russia. After graduating from BMSTU, he worked in several prominent Moscow companies, such as Huawei, NVIDIA, and Yandex. He joined KAUST in August 2020 as a Ph.D. candidate and member of Professor Peter Richtarik's Optimization and Machine Learning Lab.
Meet KAUST prospective student: Reem Alghamdi 1 min read · Mon, Aug 31 2020 News machine learning Reem Alghamdi is a computer science graduate from Princess Nourah bint Abdulrahman University, Saudi Arabia. Reem will join KAUST this fall as a M.S. candidate under the supervision of Professor Peter Richtarik.
Meet KAUST Prospective Student: Igor Sokolov 2 min read · Sun, Aug 9 2020 News machine learning optimization Igor Sokolov, 23, is an applied mathematics and physics graduate who will join KAUST from the Moscow Institute of Physics and Technology, Russia. Igor first came to KAUST as a visiting student in 2019 and was highly impressed by the University's living and working facilities. It was this first impression that prompted him to pursue an M.S. at KAUST. Sokolov will join KAUST in the Fall of 2020 as an M.S. candidate under the supervision of Professor Peter Richtarik.
KAUST CS student recognized with AAAI Outstanding Program Committee Award 4 min read · Sun, May 3 2020 News artificial intelligence Konstantin Mishchenko, a Ph.D. student under the supervision of Professor Peter Richtárik, has been selected as one of the Association for the Advancement of Artificial Intelligence’s (AAAI) 12 Outstanding Program Committee Members for 2020. Mishchenko was presented with a certificate in recognition of his outstanding service at AAAI-20 held in New York from February 7-12.
KAUST Ph.D. student Jinhui Xiong wins best paper award 1 min read · Thu, Jan 23 2020 News Spotlight Computer Vision modeling visualization computer graphics KAUST computer science Ph.D. student Jinhui Xiong recently won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization. The symposium took place from September 30 to October 2, 2019, at the University of Rostock, Germany, and provided the opportunity for researchers to discuss a wide range of topics in computer science, including computer graphics, vision, visualization and visual analytics.
Jinhui Xiong wins Best Paper Award at VMV 2019 2 min read · Mon, Dec 2 2019 News Spotlight computational imaging 3D reconstruction Fourth-year computer science Ph.D. student Jinhui Xiong won the best paper award at this year’s 24th International Symposium on Vision, Modeling, and Visualization (VMV) 2019.
Machine learning models gather momentum 1 min read · Sun, Nov 24 2019 News algorithms machine learning Computer science New methods for training machine learning models are quicker and more accurate than current approaches, previously considered state-of-the-art.
Less chat leads to more work for machine learning 2 min read · Wed, Oct 16 2019 News machine learning Computer science Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale.
KAUST Professor Peter Richtárik wins Distinguished Speaker Award 4 min read · Sun, Sep 15 2019 Awards Spotlight News optimization machine learning big data Peter Richtárik, KAUST professor of computer science, recently received a Distinguished Speaker Award at the Sixth International Conference on Continuous Optimization (ICCOPT 2019) held in Berlin from August 3 to 8. ICCOPT 2019 was organized by the Mathematical Optimization Society and was hosted this year by the Weierstrass Institute for Applied Analysis and Stochastics.
Accelerating the grapevine effect 1 min read · Sun, Jul 7 2019 News optimization machine learning big data By looking at classical gossip algorithms from a novel perspective, KAUST Professor Peter Richtarik has found a way to significantly speed up gossip-based information sharing, and in the process, he discovered new applications for this efficient mathematical approach. Gossip involves the sharing of information between individuals in a network and can be applied mathematically in both human social networks and data networks, such as distributed sensors. “A network is a collection of nodes, each connected to other nodes via links,” explains Richtarik. “In social networks, for instance
KAUST master’s degree student wins best poster award at Data Science Summer School 1 min read · Thu, Oct 11 2018 Awards News student award Samuel Horváth, a master's degree student in the University's statistics and optimization M.S./Ph.D. program, recently won a best poster award at the second edition of the Data Science Summer School (DS3). The event took place in Paris from June 25 to 29, and is one of the largest global data science summer schools. It was co-organized by the Data Science Initiative of École Polytechnique and DATAIA Institute. The primary goal of DS3 was to provide a series of courses and practical sessions covering the latest advances in the field of data science. Five hundred students, postdoctoral fellows
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