Gunjan Shrivastava
Software Engineer at Memorial Sloan Kettering Cancer Center
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolGunjan Shrivastava is a software engineer with 10 years of experience applying machine learning, computer vision, and embedded-systems expertise to real-world problems across healthcare and finance. Trained with a Master's in Computer Engineering from Stony Brook University, she built optimized deep learning pipelines for mobile and edge devices (including VGG-16 on ARM) and worked on medical imaging projects at IIT Delhi. Her industry experience spans low-latency trading systems at FlexTrade to production software engineering at Memorial Sloan Kettering Cancer Center, blending research rigor with production-grade engineering. As a Google Summer of Code contributor, she implemented browser-native neural network inference using WebAssembly, demonstrating a knack for squeezing heavy computation into constrained environments. Colleagues describe her as a pragmatic engineer who bridges algorithmic research and systems-level optimization to deliver impactful biomedical and software solutions.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Technology (B.Tech.), Electronics and Communication Engineering, Bachelor of Technology (B.Tech.), Electronics and Communication Engineering at The LNM Institute of Information TechnologyHigh School, High School at St. Joseph's Convent Senior Secondary School, RatlamMaster’s Degree, Computer Engineering, Master’s Degree, Computer Engineering at Stony Brook University
English, Hindi
Stackoverflow
1reputation
301reached
1answer
4questions
Github Skills (24)
denoising10
segmentation10
interactive9
pytorch8
instance-segmentation7
deep-learning7
code-coverage6
powermock6
mongodb6
jacoco6
powermockito6
aws-lambda6
java6
amazon-rds6
mysql6
Programming languages (2)
Github contributions (5)
gunjan-sh/webimg
Jun 2016 - Dec 2016
Contributions:14 commits, 12 pushes, 2 branches in 5 months
nadeemlab/ImPartial
May 2021 - Dec 2022
Interactive deep learning cell segmentation using partial annotations [MICCAI'26]
Contributions:4 reviews, 73 commits, 15 PRs in 1 year 7 months
deep-learningsegmentationinteractivedenoisingcell-segmentation
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