Amogh Joshi

I am an undergraduate student at Princeton University, studying electrical and computer engineering. I am broadly interested in computer vision and graphics, especially applied to robotics and autonomous systems.

At Princeton, I’m in the Computational Imaging Lab, where my research primarily focuses on neural rendering and scene reconstruction for autonomous driving. I also work at Torc Robotics on neural data driven simulation for autonomous trucks.

Previously, I was at Monarch Tractor, where I worked on autonomous navigation in farms and operator safety & awareness. I have also been involved with the AI Institute for Food Systems and principally lead the development of AgML. For an extended bio, click here.

GitHub  /  Google Scholar  /  LinkedIn  /  Contact

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News N Q

  • October 2024 I was invited to give a lecture on AgML and agricultural machine learning at New Mexico State University.
  • July 2024 Neural Light Spheres was accepted to SIGGRAPH Asia 2024.

Research R

For a full background on my research experience, see my extended bio.

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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.

Projects 1 2

The following are major projects which I have been involved in or developed myself.

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AgML: An Open-Source Library for Agricultural Machine Learning


AI Institute for Next Generation Food Systems
project / info

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.

Other 7

I am a huge photography enthusiast, and you can check out some of my work here. You can also check out my travel page for more photos of my frequent travels. I'm also an avid reader; you can check out my reading list for past and current books.


Who could have seen this coming, another Jon Barron clone. This has gone too far.