Researchers

Machine Learning Engineer at tilmoch.ai, where I mostly work on NLP applications for Turkic languages. At tilmoch.ai, I've worked on Tahrirchi Editor, tilmoch.ai Translator and Misollar. We also contribute to the open-source Turkic NLP community with the biggest Uzbek text corpora (UzBooks and UzCrawl), the SOTA Uzbek encode models (tahrirchi-bert-base and tahrirchi-bert-small), Karakalpak and Southern Uzbek Machine Translation models and dataset. At the same time, I am a BSc. in AI student at MBZUAI, where I am digging deeper into fundamentals of AI Engineering.

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Have written courseworks about brain drain in Kazakhstan and its impact to economic growth

Research focus: any sort of evaluation methodologies for GenAI of any modality.

My current research focus is centered on Applied Machine Learning, Deep Learning, and Multimodal AI, with a strong interest in document understanding, OCR, vision-language models, and LLM-based systems. I am currently exploring synthetic data generation for low-resource Turkic languages, especially for OCR and document recognition tasks. This includes building realistic multilingual document datasets, designing generation pipelines, and preparing data for fine-tuning modern OCR/VLM models. Another important direction of my work is the development of practical AI systems based on RAG, LLM agents, and multimodal reasoning. I am interested in turning research ideas into usable AI tools for real-world domains such as document processing, legal technology, education, and urban surveillance.

Currently building a multi-class affect detection pipeline that classifies student emotional states from behavioral and keystroke data across 243 students and 400+ features. Using student-level nested GroupKFold cross-validation to ensure leakage-safe evaluation, with Random Forest and XGBoost as primary models, and addressing feature selection stability via rank-averaging across folds.

AI researcher and machine learning engineer focused on practical AI systems for real-world applications. My interests include AI for finance and neuroscience, applied machine learning, computer vision, healthcare AI, and optimization. I actively participate in research competitions, including Kaggle and NeurIPS, and achieved Kaggle Competitions Master status with a top-14 global ranking. Beyond research, I contribute to AI olympiads, education, and community building.

Я занимаюсь оптимизацией, машинным (федеративным) обучением и теорией обучения. Открыт к коллаборациям!

Interested in geometry

Research and simulations of PDE problems by using Fourier Neural Operator's architecture of neural networks.

Causal representation learning and foundation models for neuroscience

I am a Ph.D. researcher in Computer Science at SDU University, working on NLP, machine learning, and AI-generated text detection. My research focuses on detecting AI-generated and AI-obfuscated text using transformer models, multilingual NLP, and contextual representations.

Life Sciences, AlfaCenter.ai

My research focuses on large language models, reinforcement learning, and AI for education. I am particularly interested in post-training methods for LLMs, including PPO, DPO, and GRPO, as well as retrieval-augmented generation (RAG), efficient model training, and reasoning capabilities. My recent work explores Socratic tutoring with LLMs, reinforcement learning for improving educational dialogue systems, and scalable distributed training of foundation models. I also have experience building diffusion models, reinforcement learning agents, and high-performance AI systems from scratch in PyTorch. I am interested in collaborating on research related to LLM alignment, reasoning, AI agents, and open-source foundation models.

PhD researcher at KTH working on neuromorphic event cameras and low-latency sensor fusion for real-time human-robot collaboration. My work combines deep learning and spiking neural networks for depth estimation and object tracking, using a 7-DOF robotic arm and event cameras as the primary experimental platform.

I am focused on deploying ML models on IoT devices

Evals, datasets

Working as a Research Assistant at Nazarbayev University.

Code-Switching aware STT KK-RU-EN Code-Switching audio dataset OCR for Kazakh Hand-Written Text

My research sits at the intersection of machine learning and clinical medicine, focused on how AI can support doctors in real clinical environments

My research interests include computer vision, multimodal AI, medical image analysis, object detection, vision-language models, and interpretable machine learning. I am particularly interested in developing robust AI systems for real-world applications and healthcare.

Currently i am focused on CV based application on medical domain such as an early breast cancer detection.

I work on CV and NLP for Kazakh and other low-resoruce languages.

Im open for everything, just hit me in tg. Be straight, say what you want.