Profiles

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Anna Talgat is currently a Ph.D. candidate in Applied Mathematics and Computational Sciences at KAUST. She earned her B.S. in Mathematics from Fatih University, Istanbul, with high honors and a full scholarship. Anna continued her studies at KAUST, completing her M.S., focusing on stochastic geometry-based analysis of LEO satellite communication systems. Her early career includes an internship at Cambridge University’s DAMTP and teaching mathematics at Galaxy International School in Kazakhstan. Additionally, she was a Graduate Teaching Assistant at KAUST, supporting academic development and enhancing teaching methodologies.

Anna Talgat's research interests primarily focus on stochastic geometry and its applications in communication systems. Specifically, her work includes the stochastic geometry-based analysis of LEO satellite communication systems, performance analysis and optimization of wireless communications, and enhancing the efficiency and reliability of these networks. Her research aims to advance the understanding and development of satellite communication networks, which are critical for various applications, including IoT (Internet of Things) and secure data transmission in space communications.

Arturo is a Ph.D. candidate in Electrical and Computer Engineering at the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division of King Abdullah University of Science and Technology (KAUST). Following his participation in the KAUST's 2017 Photonics Summer Camp, he started his graduate studies at KAUST in August 2018. Prior to his graduate studies he earned B.Sc. in Engineering Physics from Instituto Tecnológico y de Estudios Superiores de Monterrey (Mexico) in 2017, and conducted a research intership in the Nuclear Sciences Institute (ICN) of the Universidad Nacional Autónoma de México in 2016.

Arturo is the co-founder of Pixeltra Inc., a startup company specializing in multidimensional imaging solutions through metasurfaces. He actively serves as a reviewer for Nature Communications, and has authored ten publications in high-impact factor journals during his Ph.D. He received the Academic Excellence award from KAUST in 2022 and 2023, and was awarded 2nd place at the 2019 Falling Walls international pitching competition.

Arturo's research focuses on the design and fabrication of optical metasurfaces, emphasizing practical applications in remote sensing and hyperspectral imaging.

Ms. Aseel AlNajjar is a Ph.D candidate in the AppliedPDE group of the Applied Mathematics and Computational Science program (AMCS) of CEMSE division at the King Abdullah University of Science and Technology, Saudi Arabia. She graduated from Taibah University in 2019 with a bachelor's degree in Mathematics and received a Master's degree in Applied Mathematics from KAUST in 2021. During 2018 Ms. AlNajjar was a summer research intern in the AppliedPDE group. 

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.

Aznaur obtained his bachelor's degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology in 2023. He joined KAUST in 2024 to pursue his MS and PhD degrees.

Deep Learning, Computer Vision, Reinforcement Learning.

Machine learning, training algorithm, optimization

Natural language processing

My undergraduate and graduate education at the University of Waterloo coupled with a variety of internships and a full-time role solidified my interest and background as a multidisciplinary hands-on mechatronics engineer.

I'm interested in finding mechatronic solutions and taking them from problem to a functional proof-of-concept. I developed a dynamic weighing machine during my master's and currently a novel hybrid-flight mode unmanned aerial system as a PhD Candidate.

https://sites.google.com/view/chlwr

Machine Unlearning