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.

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.

Life Sciences, AlfaCenter.ai

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

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

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.

RL, Post training

My primary area of interest is Uncertainty Quantification for LLMs. In very simple terms, I am trying to understand how we can determine when a model knows - and doesn't know - what it is talking about. I also have some interest in LLM safety and trustworthiness, but more so as a casual learner than a practitioner.

idk i research cool stuff

Machine Learning, AI, Startups, Publications

I am focusing on summarization, machine translation, but open to other topics.

I work on information elicitation in goal oriented dialogues. I'm also interested in latent reasoning, knowledge representation and neural memory for LLMs.

Developing supervised and unsupervised methods to classify guppy fish social behavior within population.

My current research focuses on the fundamental aspects of learning, specifically exploring benign overfitting, long-tailed distributions, and the hardness of learning.

Архитектура ИИ моделей и способы их обучения

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!

Causal representation learning and foundation models for neuroscience