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Ashish Sinha

Machine Learning Researcher @ Noah's Ark Lab

ashishsinha108 [AT] gmail [DOT] com

Bio

Ashish Sinha is a researcher at Huawei’s Noah’s Ark Lab in the Embodied AI team, where he focuses on perception for robotic manipulation using vision language action models. He holds an MSc (thesis) in Computer Science from Simon Fraser University, where he worked with Prof. Ghassan Hamarneh on representation learning and 3D generative modeling for medical image analysis.
Prior to this, he worked as a Risk Analyst at Wells Fargo upon graduating with a Bachelor’s in Materials Science from Indian Institute of Technology Roorkee (IITR). During his Bachelors, he spent a wonderful summer in Tokyo at Preferred Networks Inc.
He is fortunate to have worked with some wonderful advisors like Prof. Jonghyun Choi GIST Vision Lab (South Korea), and Prof. Jose Dolz at ETS Montréal.

The best way to reach me is via this email.

Publications

Most recent publications on Google Scholar.
* indicates equal contribution.

Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields

Ashish Sinha and Ghassan Hamarneh

MICCAI. 2024

Paper PDF Slides Poster Code

DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images

Ashish Sinha*, Jeremy Kawahara*, Arezou Pakzad*, Kumar Abhishek, Matthieu Ruthven, Enjie Ghorbel, Anis Kacem, Djamila Aouada, Ghassan Hamarneh

Medical Image Analysis. 2024

Paper PDF Poster Code

MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds

Ashish Sinha, Jonghyun Choi

CVPR. Workshop on Learning with Limited Data. 2023

Paper PDF Poster Code

Deep Learning based Dimple Segmentation for Quantitative Fractography.

Ashish Sinha, K.S. Suresh

ICPR. Industrial Machine Learning Workshop. 2020. Spotlight

Paper PDF

Multi-scale self-guided attention for medical image segmentation.

Ashish Sinha, Jose Dolz

JBHI: Journal of Biomedical and Health Informatics. 2020.

Paper PDF Code

GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention.

Ashish Sinha, Yuichiro Hirano, Yohei Sugawara

NeurIPS'19, Workshop on Medical Imaging Meets NeurIPS. 2019.

Paper PDF

Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields

Ashish Sinha and Ghassan Hamarneh

MICCAI. 2024

Paper PDF Slides Poster Code

DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images

Ashish Sinha*, Jeremy Kawahara*, Arezou Pakzad*, Kumar Abhishek, Matthieu Ruthven, Enjie Ghorbel, Anis Kacem, Djamila Aouada, Ghassan Hamarneh

Medical Image Analysis. 2024

Paper PDF Poster Code

MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds

Ashish Sinha, Jonghyun Choi

CVPR. Workshop on Learning with Limited Data. 2023

Paper PDF Poster Code

Deep Learning based Dimple Segmentation for Quantitative Fractography.

Ashish Sinha, K.S. Suresh

ICPR. Industrial Machine Learning Workshop. 2020. Spotlight

Paper PDF

Ntire 2020 challenge on image demoireing: Methods and results.

Yuan et. al., Ashish Sinha

CVPR'20: NTIRE Challenge on Image Demoireing. 2020. (Rank 13)

Paper

Multi-scale self-guided attention for medical image segmentation.

Ashish Sinha, Jose Dolz

JBHI: Journal of Biomedical and Health Informatics. 2020.

Paper PDF Code

GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention.

Ashish Sinha, Yuichiro Hirano, Yohei Sugawara

NeurIPS'19, Workshop on Medical Imaging Meets NeurIPS. 2019.

Paper PDF

Vitæ

Full Resume here | Single Page Resume here.

Ashish Sinha
ashishsinha108 [AT] gmail [DOT] com