Profiles

Mikhail Moshkov is a professor of Applied Mathematics and Computational Science (AMCS) and an affiliated professor of Computer Science (CS) at KAUST. He is also the principal investigator of the Extensions of Dynamic Programming, Machine Learning, Discrete Optimization (TREES) research group.

Professor Moshkov holds an M.S. summa cum laude in 1977 from the University of Nizhni Novgorod, Russia. He obtained his Ph.D. in 1983 from the University of Saratov, Russia, and a Doctor of Science in 1999 from Moscow State University, Russia.

Before joining KAUST, he held professorships at the University of Nizhni Novgorod, Russia, and the University of Silesia, Poland.

Moshkov received the State Scientific Stipend in Mathematics for Outstanding Scientists from April 2000 to March 2003, awarded by the Presidium of the Russian Academy of Sciences. Additionally, he received the First Degree Research Prize, awarded by the rector of the University of Silesia, Poland, in 2006.

Professor Moshkov's research interests include: (i) The study of time complexity of algorithms in computational models such as decision trees, decision rule systems and acyclic programs with applications to combinatorial optimization, fault diagnosis, pattern recognition, machine learning, data mining, and analysis of Bayesian networks. (ii) The analysis and design of classifiers based on decision trees, reducts, decision rule systems, inhibitory rule systems, and lazy learning algorithms. (iii) Extensions of dynamic programming for sequential optimization relative to different cost functions and for study of relationships between two cost functions with applications to combinatorial optimization and data mining.

Azimkhon Ostonov is a Ph.D. candidate at King Abdullah University of Science and Technology in Saudi Arabia, specializing in Computer Science under the supervision of Professor Mikhail Moshkov. Azimkhon obtained his Bachelor’s degree in Applied Mathematics and Informatics in 2012 and completed his Master’s degree in Computer Systems and their Software in 2014, both from the National University of Uzbekistan. Azimkhon has made considerable contributions to the field, with publications including works on Machine Learning and Compexity Analysis.

Before joining KAUST he worked as a teacher at the National University of Uzbekistan for four years. Before that he started his programming career as a junior programmer at Fido-Biznes in Tashkent.

Azimkhon's research focuses on complexity of decision trees for decision tables.

Kerven Durdymyradov is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), supervised by Professor Mikhail Moshkov. Kerven holds a Master’s degree in Artificial Intelligence from the Moscow Institute of Physics and Technology (2022) and a Bachelor’s degree in Applied Mathematics and Information Technology from Magtymguly Turkmen State University (2017). He has received several bronze and silver medals in the well-known International Mathematical Olympiads, including IMO, IMC, BMO, etc.

Kerven's research focuses on relations between decision trees and decision rule systems.

Manal A. Alshehri is a Doctoral Candidate in Computer Science at King Abdullah University of Science and Technology (KAUST). She holds a B.S. and M.S. degree in Computer Science from King Abdulaziz University, where she also serves as a lecturer. Her research has been published in leading international conferences, including IEEE Big Data and CIKM.

Her research spans a broad range of artificial intelligence applications, with a focus on enhancing recommendation systems and advancing text mining techniques. She employs cutting-edge AI methodologies to address key challenges such as cold-start problems, user privacy, diversity, and filter bubbles. She is also interested in analyzing user behavior across digital platforms and in leveraging generative large language models to create realistic simulations and automate labor-intensive tasks.