I am a Master’s student in Computer Science & Engineering at UNIST and a researcher at the Interactive Multimodal ML Lab. My passion lies in exploring the frontiers of research and develop cutting-edge algorithms in the area of multimodal learning, particularly in the integration of vision and language. I am also interested in advancing the understanding and transparency of AI models. By bridging the gap between AI and human understanding, I aim to build more trustworthy and ethical AI systems that can be effectively utilized across various domains.

Besides my research interests, I have a broad interest in fintech, data science and the design / deployment of ML systems. I find great fascination in the practical application of machine learning techniques and their potential to solve real-world problems.

I always seek opportunities to expand my knowledge, stay updated with the latest advancements, and participate in meaningful projects that have a positive impact on society. I am enthusiastic about connecting and collaborating with fellow researchers, professionals, and organizations who share a similar vision.

• Programming Languages: Python, C++, JavaScript, R
• Frameworks & Tools: PyTorch, Hugging Face, DeepSpeed, Scikit-learn, OpenCV, NumPy, Pandas, Matplotlib, Git, LaTeX
• AI/ML Expertise:
  • LLMs: LoRA/QLoRA, RLHF/DPO Fine-tuning, Retrieval-Augmented Generation (RAG) Integration, Quantization, Multimodal LLM Adaptation, Synthetic Data Creation, Prompt Engineering
  • Traditional ML: Linear/Logistic Regression, Support Vector Machines (SVM), XGBoost, Principal Component Analysis (PCA), K-means Clustering, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN/LSTM)

• Lotte Scholarship for International Master's Students: Awarded by the Lotte Scholarship Foundation for students with exceptional research potential in Korea, providing KRW 12,000,000 per year for the duration of graduate studies.
• Korean Government Scholarship for Graduate Studies: Comprehensive scholarship including a tuition fee waiver and a stipend of KRW 9,600,000 per year throughout graduate studies at UNIST.
• UNIST Global Dream Scholarship: Covered tuition fees, health insurance, and living expenses during undergraduate studies at UNIST.

• Machine Learning Engineering for Production Specialization – DeepLearning.AI specialization covering scalable production pipelines, ML model deployment, and MLOps best practices.
• Deep Learning Specialization – Taught by Andrew Ng, focusing on neural networks, convolutional networks, and sequence models for real-world AI tasks.
• Applied Data Science with Python Specialization – University of Michigan course series focusing on Python-based data analysis, including Pandas, Matplotlib, and machine learning fundamentals.
• Statistical Learning – Stanford Online course covering supervised and unsupervised learning, linear regression, and classification methods.
• Machine Learning – Classic Coursera course by Andrew Ng, covering algorithms, supervised/unsupervised learning, and neural networks.
• Mathematics for Machine Learning Specialization – Imperial College London specialization focusing on linear algebra, calculus, and statistics for machine learning foundations.

I am fluent in Uzbek, Russian, English, and intermediate in Korean (working on improving it)! 🇺🇿 🇷🇺 🇬🇧 🇰🇷