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 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 1 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 1 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 1 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.
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 1 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 1 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
