🚀 Passionate about optimization, deep learning, and cutting-edge research in machine learning.
📊 I have a strong mathematical foundation and a keen interest in solving complex problems through advanced methods.

• 🎓 Background: Strong mathematical education from Moscow Institute of Physics and Technology (MIPT).
• 🔬 Fields of Interest:
  1. Optimization: Focused on transport problems, variational inequalities, and advanced algorithms.
  2. Deep Learning: Exploring architectures, including Graph Neural Networks and Transformers.
• 🧪 Current Role: Researcher at the Laboratory of Mathematical Optimization Methods.

• ✍️ Writing research papers on optimization methods related to transport problems and variational inequalities.
• 🧠 Studying Graph Neural Networks and their applications in machine learning.
• 📖 Regularly reading state-of-the-art papers on optimization and machine learning.

• Programming: Python (NumPy, Pandas, PyTorch, Scikit-learn), C, C++, SQL, YQL.
• Data Visualization: Matplotlib, Seaborn, DataLens.
• Workflow: Git, Nirvana.

1. Just Relax It - Implementation of different relaxation methods [BMM 24-25]
2. Adversarial-Attacks - Application of the adaptive loss scaling algorithm to training classification models on attacked data
3. MLFinance - Surrogate modeling: approximating the Black-Scholes model using neural networks
4. MLNotes - A collection of my notebooks on Deep Learning from various areas of machine learning
5. Computational-mathematics - Homework assignments on computational mathematics
6. Methods-Optimization - Homework assignments on optimization methods
7. CFW-in-ML - Application of Conjugate Frank Wolfe in Machine Learning (project for a paper "Conjugate Frank Wolfe in Machine Learning")
8. Reinforcement_learning - Homework assignments on reinforcement learning
9. Algorithms_and_my_projects - My first project: a collection of various projects I started with

1. Optimization Methods in Transport Problems Citations
   • Modifications of the Frank Wolfe algorithm in the problem of finding equilibrium transport flow distributions.
2. Presentation at OPTIMA 2024
   • Abstracts: Link to Google Drive

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