Prantik Howlader

Applied Scientist II at Stony Brook University

Town of Brookhaven, New York, United States
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Summary

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Prantik Howlader is an Applied Scientist II and PhD researcher with nine years of industry and academic experience building deep learning and multimodal AI systems. His work spans agentic AI and reinforcement learning for tool use, multimodal segmentation with VLMs, and practical deployment of lightweight Transformer-based segmentation on constrained devices. He has driven applied research at Amazon and Zebra Technologies—improving product recommendations and customer return experiences via context-aware visual question generation and multimodal agents—and continues PhD research on low-label, class-imbalanced segmentation for medical and natural images. Early roles in networking and systems at Cisco and Wipro give him a rare combination of production-grade software engineering and cutting-edge CV/ML research. Notably, he has applied VAE data augmentation and token-efficient detector-to-transformer pipelines to tackle class imbalance and resource limits in real deployments.
code9 years of coding experience
job7 years of employment as a software developer
bookDon Bosco School, Liluah
bookBachelor of Technology (B.Tech.) Information Technology, Bachelor of Technology (B.Tech.) Information Technology at West Bengal University of Technology, Kolkata
bookMaster’s Degree Computer Science, Master’s Degree Computer Science at NIT Calicut
bookDoctor of Philosophy - PhD Computer Vision, Doctor of Philosophy - PhD Computer Vision at Stony Brook University
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Stackoverflow

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Github Skills (15)

cert9
phishing8
gradient8
alerts8
malware7
python7
it-security7
visualization7
cybersecurity6
deep-learning6
machine-learning6
security5
queuing5
incident-response5
automation4

Programming languages (1)

Python

Github contributions (5)

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adityac94/Grad_CAM_plus_plus

Oct 2017 - Nov 2017

A generalized gradient-based CNN visualization technique
Contributions:26 commits, 26 pushes in 17 days
visualizationpythondeep-learningmachine-learninggradient
Contributions:18 pushes, 1 branch in 10 days
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