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Method and Data Processing System for Lossy Image or Video Encoding. Motion translations with flow-based processes for AI video compression.

Method and Data Processing System for Lossy Image or Video Encoding. Motion transformation handling in AI compression processes.

Covering advanced neural compression techniques, optical flow, and video encoding optimization methods.

SciPost Physics

With M. van Beest, S. Schafer-Nameki, J. Sparks

Journal of High Energy Physics

With A. Braun, M. Hubner, S. Schafer-Nameki

University of Oxford

Focused on the intersection of geometry and string theory, exploring higher-dimensional geometric objects that appear in string theory and how their properties manifest in associated physical theories.

Imperial College London

Advanced studies in pure mathematics, building the foundation for doctoral research.

University of Ljubljana

Undergraduate studies in mathematics with a focus on theoretical foundations.

Probability & Statistics

Highly proficient in mathematics, probability theory, and statistics, with a particular interest in generative density models.

Deep Learning

Highly proficient in applied generative AI research both in computer vision and applications of LLMs for internal business infrastructure projects.

Programming

Python (advanced) - 10+ years in software development, data analysis, and AI research. Expert in PyTorch with deep knowledge of model compilation stack (FX, Inductor, Dynamo, Triton).

C++ (working knowledge) - Contributions to model inference libraries and entropy coders.

I'm always interested in discussing machine learning, mathematics, and technology.

• Email sebastjancizel@gmail.com
• LinkedIn /in/scizel
• GitHub @sebastjancizel
• Resume Download PDF