I am particularly interested in computer engineering with a focus on artificial intelligence. I have experience in computer vision, where I explored methods for object detection, and in machine learning, where I applied data analysis techniques. I am now studying deep learning as a main area of interest.
In this lab, I am working on training and evaluating state space models, specifically the Mamba architecture, for protein sequence modeling. I utilize Huggingface frameworks for model implementation and experiment tracking with Wandb. This approach allows me to efficiently analyze sequence data while leveraging recent advances in deep learning architectures.
My research aims to create new solutions for specific fields where AI can be useful. In the future, I am especially interested in world foundation models, which I believe will play crucial role in robotics, and I plan to contribute to their development.