Hi, I am Shasvat Desai
Hi, I am Shasvat Desai
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Senior Computer Vision Scientist, Intelligent Retail Labs(IRL), Walmart
Senior Computer Vision Scientist, Intelligent Retail Labs(IRL), Walmart
Turning pixels into insights, one convolution at a time 😀
Turning pixels into insights, one convolution at a time 😀
ABOUT ME
ABOUT ME
I am currently working as a Staff Scientist at Walmart, where I am involved in developing algorithms for sponsored search.
I am currently working as a Staff Scientist at Walmart, where I am involved in developing algorithms for sponsored search.
Previsouly, I worked as a Senior Computer Vision Scientist at the Intelligent Retail Lab (IRL), Walmart, where I was involved in developing algorithms to better understand what’s happening inside the store through an array of sensors, cameras, and processors to reduce retail shrinkage at self-checkout systems (SCO). My work primarily lied in the domain of scene understanding utilizing spatio-temporal scene graphs, multi-view geometry (epipolar and projective), object detection and tracking, and multi-modal retrieval integrating visual, textual, and product catalog data for precise SKU item recognition across Walmart’s extensive catalog.
Previsouly, I worked as a Senior Computer Vision Scientist at the Intelligent Retail Lab (IRL), Walmart, where I was involved in developing algorithms to better understand what’s happening inside the store through an array of sensors, cameras, and processors to reduce retail shrinkage at self-checkout systems (SCO). My work primarily lied in the domain of scene understanding utilizing spatio-temporal scene graphs, multi-view geometry (epipolar and projective), object detection and tracking, and multi-modal retrieval integrating visual, textual, and product catalog data for precise SKU item recognition across Walmart’s extensive catalog.
Previously, I was a Computer Vision Scientist at Orbital Insight, where I worked with satellite, aerial and drone images in the geospatail domain. My work spanned across multiple domains ranging from object detection of military and naval assets, landuse segmentation and monitoring (deforestation, agricultural expansion, infeastructure development) in multispectral imagery to domain-adaptation, super-resolution, and semi-supervised learning.
Previously, I was a Computer Vision Scientist at Orbital Insight, where I worked with satellite, aerial and drone images in the geospatail domain. My work spanned across multiple domains ranging from object detection of military and naval assets, landuse segmentation and monitoring (deforestation, agricultural expansion, infeastructure development) in multispectral imagery to domain-adaptation, super-resolution, and semi-supervised learning.
Before working at Orbital Insight, I was a Masters' student at the University of Massachusetts, Amherst, where I specialized in Machine Learning and Computer Vision. During my time here, I created the one of its kind multimodal salient pedestrian dataset with pixel level-annotation which has since been adopted widely in the automotive and multimodal research domain.
Before working at Orbital Insight, I was a Masters' student at the University of Massachusetts, Amherst, where I specialized in Machine Learning and Computer Vision. During my time here, I created the one of its kind multimodal salient pedestrian dataset with pixel level-annotation which has since been adopted widely in the automotive and multimodal research domain.
In my free time, I enjoy hiking, photography and playing board games!
In my free time, I enjoy hiking, photography and playing board games!
News
News
July 2024: My team's work on developing scene understanding algorithm utilizing spatio-temporal scene graph representation learning to model interactions and identify shopping behaviors and patterns was released to Walmart customers, making the shrink detection and checkout experience even more smoother.
July 2024: My team's work on developing scene understanding algorithm utilizing spatio-temporal scene graph representation learning to model interactions and identify shopping behaviors and patterns was released to Walmart customers, making the shrink detection and checkout experience even more smoother.
April 2023: My work on using synthetic data for pre-training object detection models got accepted for presentation at Walmart AI Summit Conference 2023. I demonstrated this work across the board to engineers, data scientists, and executives, showcasing the impact of synthetic data on improving detection accuracy and efficiency, as well as its potential for scaling AI solutions across Walmart's vast retail ecosystem. This presentation highlighted the technical depth and strategic value of leveraging synthetic pre-training for large-scale retail applications.
April 2023: My work on using synthetic data for pre-training object detection models got accepted for presentation at Walmart AI Summit Conference 2023. I demonstrated this work across the board to engineers, data scientists, and executives, showcasing the impact of synthetic data on improving detection accuracy and efficiency, as well as its potential for scaling AI solutions across Walmart's vast retail ecosystem. This presentation highlighted the technical depth and strategic value of leveraging synthetic pre-training for large-scale retail applications.
May 2022: Started working as a Senior Computer Vision Scientist at the Intelligent Retail Lab, Walmart, Hoboken, NJ
May 2022: Started working as a Senior Computer Vision Scientist at the Intelligent Retail Lab, Walmart, Hoboken, NJ
October 2021: Our paper titled Active Learning for Improved Semi-Supervised Semantic Segmentation in Satellite Images got accepted to the IEEE Winter Conference on Applications of Computer Vision 2022, to be held at Waikoloa, Hawaii.
October 2021: Our paper titled Active Learning for Improved Semi-Supervised Semantic Segmentation in Satellite Images got accepted to the IEEE Winter Conference on Applications of Computer Vision 2022, to be held at Waikoloa, Hawaii.
Spring 2019: Graduated with a Masters in Computer Science from the University of Massachusetts, Amherst
Spring 2019: Graduated with a Masters in Computer Science from the University of Massachusetts, Amherst
April 2019: Our paper Pedestrian Detection in Thermal Images using Saliency Maps accepted to the IEEE Workshop on Perception Beyond the Visible Spectrum at CVPR, 2019 (Long Beach, California) | Spotlight Talk Video | PDF
April 2019: Our paper Pedestrian Detection in Thermal Images using Saliency Maps accepted to the IEEE Workshop on Perception Beyond the Visible Spectrum at CVPR, 2019 (Long Beach, California) | Spotlight Talk Video | PDF
Summer 2018: Received the DAAD RISE Professional Fellowship to pursue an internship at Bayer, Leverkusen, Germany
Summer 2018: Received the DAAD RISE Professional Fellowship to pursue an internship at Bayer, Leverkusen, Germany
Fall 2017: Started a Masters program in Computer Science at the University of Massachusetts, Amherst, USA
Fall 2017: Started a Masters program in Computer Science at the University of Massachusetts, Amherst, USA
Spring 2017: Graduated from Veermata Jijabai Technological Institute (VJTI), Mumbai, India with a Bachelors in Computer Engineering
Spring 2017: Graduated from Veermata Jijabai Technological Institute (VJTI), Mumbai, India with a Bachelors in Computer Engineering
Get in touch at shasvat.desai@gmail. com
Get in touch at shasvat.desai@gmail. com
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