Rameen
Abdal
Research Scientist at Snap Inc. working on world models, video generation and control. Research Lead, Multi-Modal Training.
I am a Research Scientist at Snap Inc. (Creative Vision Team, Palo Alto Office) working on world models and video generation and control. I am also the Research Lead for Multi-Modal Training, where I maintain the model and provide the research expertise behind it. I was a postdoc at Stanford Computational Imaging Lab, Stanford University working with Prof. Gordon Wetzstein. I completed my Ph.D. in Computer Science at VCC, KAUST, supervised by Prof. Peter Wonka. I worked closely with Prof. Niloy Mitra (UCL and Adobe Research). Before that, I obtained the MS Computer Science degree from KAUST, and the B.Tech degree from National Institute of Technology (NIT), Srinagar, India. My work focuses on world models and controllable video generation, building systems that capture and reproduce motion, interaction, and dynamics in immersive and collaborative environments. Feel free to reach out to me directly.
Experience and Education
7
Publications
242026
EgoPlay: Event-Triggered Video Editing for Egocentric Streams
MeshLoom: Feed-Forward Non-Rigid Registration of Mesh Sequences
Helix4D: Complex 4D Mesh Generation
NearID: Identity Representation Learning via Near-identity Distractors
ArtifactLens: Hundreds of Labels Are Enough for Artifact Detection with VLMs
Visual Personalization Turing Test
Tuning-free Visual Effect Transfer across Videos
2023 - 2025
Zero-Shot Dynamic Concept Personalization with Grid-Based LoRA
Dynamic Concepts Personalization from Single Videos
Improving the Diffusability of Autoencoders
2022
2021
Barbershop: GAN-based Image Compositing using Segmentation Masks
StyleFlow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows
2020
Patents
2Committee and Reviewer
Ethics and Social Impact
Generative AI, including personalized video generation, opens real opportunities in education, storytelling, virtual production, and accessibility, but it also carries genuine risk of misuse for deepfakes, identity manipulation, and misleading content, as well as the risk of encoding bias into its outputs. We do not condone malicious use of these methods, and we advocate for responsible development and deployment.
Contact
Address
Palo Alto, California