Chethan Parameshwara

I am a researcher at Meta, where I develop real-time diffusion models for personalized AI assistants.

Prior to joining Meta, I was a Member of Technical Staff at WaveForms AI, focusing on multimodal diffusion models. Earlier, as a researcher at Amazon, I was a core contributor to Nova foundational models for multimodal generation.

I earned my Ph.D. in Neuroscience and Artificial Intelligence from the Neuroscience and Cognitive Science (NACS) program at the University of Maryland, College Park (UMD). My PhD research focused on video understanding and 3D computer vision for autonomous vehicles.

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My selected publications are listed here. The complete list of publications can be seen from my Google Scholar page.

Core contributor to Amazon Nova Reel, an advanced video generation model within the Amazon Nova foundation suite, designed to produce high-quality, customizable outputs with fine-grained motion control.

We describe a first step towards learning general-purpose visual representations of physical scenes using only image prediction as a training criterion.

We present a novel bipolar HD encoding mechanism designed for encoding spatio-temporal data of an asynchronous event camera.

We propose a novel differentiable programming technique for camera pose estimation in autonomous driving and flying scenarios.

We propose a bio-inspired neural network for the motion detection problem using an asynchronous event camera.

We present a novel approach to segment never-seen objects by physically interacting with them and observing them from different views.

We propose a hybrid solution to multi-object motion segmentation using a combination of model-based and deep learning approaches with minimal prior knowledge.

We present a deep learning-based solution for detecting propellers (to detect drones) for mid-air landing and following.

We present the first deep learning based solution for dodging multiple dynamic obstacles on a quadrotor with a single event camera and onboard computation.

We present a novel motion compensation approach for moving object tracking with an asynchronous event camera.

Meta
Aug, 2025 -- Present
Researcher

Research on real-time diffusion models for personalized AI assistants.

WaveForms AI
May, 2025 -- Aug, 2025
Member of Technical Staff

Research on real-time multimodal diffusion models for audio-video generation.

Amazon
Aug, 2022 -- May, 2025
Researcher

Research on video diffusion models (text-to-video, image-to-video, video-to-video) and 3D computer vision (NeRF, Gaussian Splatting, Neural Rendering, and SLAM).

University of Maryland, College Park (UMD)
Aug, 2017 -- Aug, 2022
Graduate Research Assistant with Prof. Yiannis Aloimonos and Dr. Cornelia Fermüller

Research on video understanding (object detectiona and segmentation, motion segmentation) and 3D computer vision (pose estimation, SLAM) for autonomous vehicles.

SRI International (formerly Stanford Research Institute)
Summer, 2021
Research Intern with Dr. David Zhang and Michael Piacentino

Research on few-shot deep learning and gradient-free learning algorithms.

Thanks to Jon Barron for this minimalist website template.