Ashish Sinha
Machine Learning Resident at Amii (Alberta Machine Intelligence Institute)
Earth, Texas, Canada
Summary
👤
Senior🎓
Top SchoolAshish Sinha is a machine learning researcher and practitioner with nine years of experience building and publishing state-of-the-art computer vision and generative models across academia and industry. He has driven research in multi-modal object detection, zero-shot 3D reconstruction, 6DOF pose estimation, and end-to-end robotic manipulation using large vision-language models, with recent work published at CoRL and medical imaging venues like MICCAI and MedIA. Comfortable moving models from theory to product, he has delivered risk models and automated reporting pipelines in finance and developed satellite segmentation and solar prediction systems for applied energy projects. Now a Machine Learning Resident at Amii after a research stint at Noah’s Ark Lab and SFU, he blends rigorous representation learning and differentiable rendering expertise with practical deployment experience. An often-overlooked strength is his cross-domain fluency—from medical CT reconstruction research to robotics and remote sensing—enabling creative solutions at the intersection of perception and actionable systems.
10 years of coding experience
7 years of employment as a software developer
Matriculation, Mathematics and Computer Science, A1, Matriculation, Mathematics and Computer Science, A1 at A.D.L.S Sunshine SchoolIndian Institute of Technology RoorkeeHigh School, Mathematics and Computer Science, A1, High School, Mathematics and Computer Science, A1 at DAV Public School, BistupurMaster's degree, Computer Science, Master's degree, Computer Science at Simon Fraser University
English, Hindi, Japanese
Stackoverflow
1reputation
45reached
1answer
1question
Github Skills (184)
transformers10
euler10
python10
null-safety10
attention-mechanism10
perl10
deep-learning10
gemma10
cpp10
computer-science10
glm10
javascript10
body-parser10
multimodal10
audio10
Programming languages (10)
Github contributions (5)
sinAshish/Rough-Sketch-Simplification-Using-FCNN
Aug 2018 - Oct 2019
This is a PyTorch implementation of the the Paper by Simo-Sera et.al. on Cleaning Rough Sketches using Fully Convolutional Neural Networks.
Contributions:4 commits, 3 pushes, 1 comment in 1 year 2 months
convolutional-neural-networkspytorchsketchessketch-simplificationfully-convolutional-networks
sfu-mial/DermSynth3D
May 2023 - Jul 2024
Official code for "DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images". A data generation pipeline for creating photorealistic in-the-wild synthetic dermatalogical data with rich multi-task annotations for various skin-analysis tasks.
Contributions:2 releases, 1 PR, 20 pushes in 1 year 2 months
3d-graphicsbody-parserdermatologydifferentiable-renderinghuman-anatomy
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