Amogh Joshi
I am an undergraduate student at Princeton University, studying electrical and computer engineering. I'm broadly interested in computer vision & graphics, robotics, and cognitive science.
I am a researcher in Princeton's Computational Imaging Lab, where I've worked on various aspects of the imaging pipeline, including neural rendering, scene reconstruction, and optical sensing - for applications ranging from autonomous driving to endoscopic imaging. I'm also a member of the Neuroscience of Cognitive Control Lab, where I develop computational cognitive science approaches to understanding large visual & language models.
I work as an autonomous driving engineer at Monarch Tractor, where I've developed deep learning-based pipelines for autonomous navigation, perception algorithms for operator safety, and more.
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GitHub /
Google Scholar /
LinkedIn
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News
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[Oct 2024]: I was invited to give a lecture on AgML and agricultural machine learning at New Mexico State University.
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[Jul 2024]: Neural Light Spheres was accepted to SIGGRAPH Asia 2024.
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Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem
Declan Campbell, Sunayana Rane, Tyler Giallanza, Nicolò De Sabbata, Kia Ghods, Amogh Joshi, Alexander Ku, Steven M. Frankland, Thomas L. Griffiths, Jonathan D. Cohen, Taylor W. Webb
NeurIPS, 2024
publication / arXiv
We identify that state-of-the-art VLMs fail at basic multi-object reasoning due to the binding problem, which limits simultaneous entity representation, similar to human brain processing.
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Neural Light Spheres for Implicit Image Stitching and View Synthesis
Ilya Chugunov, Amogh Joshi, Kiran Murthy, Francois Bleibel, Felix Heide
SIGGRAPH Asia, 2024
project page / publication / arXiv
We design a spherical neural light field model for implicit panoramic image stitching and re-rendering, capable of handling depth parallax, view-dependent lighting, and scene motion.
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Examining Similar and Ideologically Correlated Imagery in Online Political Communication
Amogh Joshi, Cody Buntain
ICWSM, 2024
publication / arXiv
We investigate how US national politicians' use of various visual media on Twitter reflects their political positions, identifying limitations in standard image characterization methods.
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An Open Source Simulation Toolbox for Annotation of Images and Point Clouds in Agricultural Scenarios
Dario Guevara, Amogh Joshi, Pranav Raja, Elisabeth Forrestel, Brian Bailey, Mason Earles
ISVC, 2023
publication
We present an open-source simulation toolbox designed for the easy generation of synthetic labeled data for both RGB imagery and point cloud information, applicable to a wide array of cultivars.
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Standardizing and Centralizing Datasets for Efficient Training of Agricultural Deep Learning Models
Amogh Joshi, Dario Guevara, Mason Earles
Plant Phenomics, 2023
publication / arXiv
We present methods for enhancing data efficiency in agricultural computer vision, which improves performance and reduces training time, and introduce a novel set of model benchmarks.
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Exploiting the Right: Inferring Ideological Alignment in Online Influence Campaigns Using Shared Images
Amogh Joshi, Cody Buntain
ICWSM, 2022
publication / arXiv / press
We develop models to analyze the ideological presentation of foreign Twitter accounts based on shared images, revealing inconsistencies in ideological positions across different content types.
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Major Projects
The following are major projects which I have either led or significantly contributed to.
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AgML: An Open-Source Library for Agricultural Machine Learning
AI Institute for Next Generation Food Systems
project / info / press
Since its inception, I have led the development of AgML. We have aggregated the world's largest collection of agricultural deep learning datasets, produced benchmarks and pretrained weights for state-of-the-art models, and developed a suite of tools for data preprocessing, model training, and deployment in an easy-to-use API.
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Other
When I'm not working on the development of imaging systems, I enjoy using them to capture photographs of our world: check out my photography page for some highlights from my travels.
I'm also an avid reader (of all genres, though I'm on a particular sci-fi kick right now): to check out my reading list, visit my Goodreads page.
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