Researchers

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.

Life Sciences, AlfaCenter.ai

Machine Learning, AI, Startups, Publications

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

Evals, datasets

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

Causal representation learning and foundation models for neuroscience

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

I am focused on deploying ML models on IoT devices

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.

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.

Архитектура ИИ моделей и способы их обучения

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

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.

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.

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

Interdisciplinary researcher and developer performing technical coursework and applied research in computer vision and generative models. Experienced in deep learning model fine-tuning, diffusion-based image generation.

recreating the Kazakh heritage and culture

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.

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I have worked on Kazakh language models such as KazBERT(Eraly-ml/KazBERT) and others, recently i won shared task at SemEval workshop it was about how to detect ai in code and how to detect hidden ai code, system paper of our work was accepted and it will be published in ACLAnthology.

idk i research cool stuff

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