Highlights

Research, recognition, and moments along the way.

2026

  • Al-Farabi Kazakh National University,

    Graduation with honours

    I graduated with honours in Computer Science from KazNU. With my degree, I also received recognition for contributions to research and innovative startup projects.

  • Al-Farabi Kazakh National University,

    Teaching AI from first principles

    I taught a four-week course in AI and machine learning at KazNU. It covered first principles, model evaluation, generative AI, and responsible use.

  • Certificate for English-language volunteering.

    Al-Farabi Kazakh National University,

    English-language volunteering

    Recognition for supporting students in KazNU’s English Language Group through conversation practice. The sessions focused on confidence, fluency, and academic communication.

  • Almaty TV News,

    AI-Sana and artificial intelligence education (opens in a new tab)

    Almaty TV News coverage of AI-Sana and students completing AI courses.

  • Al-Farabi Kazakh National University,

    iLearn: support for academic success

    First place in KazNU’s Innovative Startup Projects competition for iLearn, a system I built to model student academic success.

  • Shymkent, Kazakhstan,

    First Congress of Mathematicians of Kazakhstan

    Presenting our group’s research in scientific machine learning at Kazakhstan’s first Congress of Mathematicians in Shymkent. Our work uses physics-informed neural networks to model fluid flow in porous media.

2025

  • Shakarim University, Semey,

    AI-Sana Shakarim Solveathon: AI and agriculture

    First place with the KazNU team at the national solveathon on AI for agriculture in Semey. The certificate recognizes participation in the event.

  • Almaty, Kazakhstan,

    ICMM&IT 2025: second-best report

    Second-place best-report award in the Information Technologies and Artificial Intelligence section at ICMM&IT 2025. My presentation examined Kolmogorov–Arnold representations for scientific computing.

  • Farabi Media – KazNU,

    Predicting students’ academic performance (opens in a new tab)

    A university video about a research project to predict students’ academic performance.

  • Al-Farabi Kazakh National University,

    Farabi Alemi 2025: local session and plenary awards

    My faculty awarded me first place in the local Computer Science and Engineering session. The university rector presented my first-place plenary award at the awards ceremony with winners from all faculties. My research used interpretable Kolmogorov–Arnold models of polymer flooding.

2024

  • Samson standing between the flags of Kazakhstan and Ethiopia.

    The Astana Times,

    Education, Ethiopia, and Kazakhstan (opens in a new tab)

    In 2022, I received a four-year Government of Kazakhstan scholarship through the Bologna Process programme. It covered tuition and a stipend for undergraduate computer science study. This 2024 interview explores education, research opportunities, and what Ethiopia could learn from Kazakhstan.

  • Al-Farabi Kazakh National University,

    Farabi Alemi 2024: local Computer Science session

    First place in the local Computer Science session at KazNU’s Farabi Alemi conference for students and young scientists.

  • Al-Farabi Kazakh National University,

    Farabi Project Challenge 2024

    First place as an individual entrant for my project using machine learning to predict student academic success.

  • Ministry of Science and Higher Education of Kazakhstan,

    National Student Research Competition: Computer Science

    First place in Computer Science (Natural Science) at Kazakhstan’s national student research competition. It brought together hundreds of candidates from 30+ universities. My research examined student academic outcomes. Part of it was carried out with King’s College London.

More highlights

Courses and certifications

Courses I have taken, with the original certificates.

  • Certificate for Data Parallelism: How to Train Deep Learning Models on Multiple GPUs.

    NVIDIA,

    Data Parallelism: How to Train Deep Learning Models on Multiple GPUs

    Certificate of competency in training deep learning models on multiple GPUs, using data parallelism.

  • Certificate for MLx Generative AI: Theory, Agents, Products.

    AI for Global Goals,

    MLx Generative AI: Theory, Agents, Products

    Selected through competitive admission for this 21-hour course on generative AI, agents, foundation models, and building AI products. Attended online, 22–24 August 2024.

  • Certificate for Fundamentals of Deep Learning.

    NVIDIA,

    Fundamentals of Deep Learning

    Certificate of competency in the fundamentals of deep learning.

  • Certificate for Oxford Machine Learning Summer School: Representation Learning and Generative AI.

    AI for Global Goals,

    Oxford Machine Learning Summer School: Representation Learning and Generative AI

    Selected through competitive admission for OxML 2024’s Representation Learning and Generative AI track. Attended online; the 22-hour programme included lectures and practical sessions on language models, vision, and uncertainty.

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