David Dinkevich

I’m a Machine Learning researcher and MSc student at the Hebrew University of Jerusalem, where I work under the supervision of Dani Lischinski. My research focuses on generative models for images and video.
My current work centers on diffusion-based visual world models—systems that represent and simulate environments with applications in visual planning, animation, and AI-driven creativity. I am particularly interested in autoregressive video diffusion models, and in methods for generating long-duration, high-quality video efficiently.
I have experience modifying the internals of existing models—for example, my thesis explores adapting attention mechanisms in transformer-based image models to improve character consistency across frames.
I am motivated by a desire to open the black box and better understand how efficiently modern generative models process information.