Joshua Udobang

I am a machine learning engineer specializing in generative AI, large language models (LLMs), and multimodality. My research focuses on advancing the capabilities of AI systems to generate, understand, and interact across multiple modalities, such as text, images, and audio. I am passionate about pushing the boundaries of AI technology and applying my skills to solve complex challenges in this rapidly evolving field.

I am a graduate of the Skolkovo Institute of Science and Technology (Skoltech), where I worked as a researcher in the Laboratory of Computational Intelligence, Center for Artificial Intelligence Technology. My thesis focused on the "Implementation of Diffusion Transformer on NNTile Machine Learning Framework," exploring how to optimize transformer models for diffusion-based tasks. Through this research, I aim to contribute to the growing body of knowledge in AI, enhancing both theoretical insights and practical applications.

I am open-minded, dedicated, and passionate about continuous learning. With a strong work ethic and a collaborative spirit, I thrive in teams that are committed to excellence and innovation. Currently seeking new opportunities in the industry, I am eager to leverage my expertise to bring value to cutting-edge AI projects and drive impactful technological advancements.