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    (Updated Jan 2024)

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About Me

Who Am I?

Hey! I'm Divyansh Aggarwal.

I am currently an Applied Scientist II at Amazon One. Prior to my stint at Amazon, I was a Graduate Research Assistant in the Biometrics Research Group at Michigan State University, supervised by Dr. Anil K. Jain . My main areas of research are Biometric Recognition, Computer Vision, Machine Learning, Federated Learning, Image Synthesis/Manipulation and 3D Image Generation and Reconstruction.




Biometric Recognition


Image Manipulation


3D Image Generation


3D Image Reconstruction

My Specialty

My Skills

Deep Learning

75%

Face Recognition

85%

Python

85%

Tensorflow

70%

Pytorch

80%

C++

80%
Education

Education

Michigan State University

2019 - 2021
Supervisor: Dr. Anil K. Jain
CGPA: 3.95 (on a scale of 4.0)

Indian Institute of Technology Jodhpur

July 2015 - May 2019
CGPA: 9.53 (on a scale of 10.0)
Department and Batch Rank : 1

Delhi Public School Ghaziabad Vasundhara


July 2014 - May 2015
Percentage: 96%
Experience

Work Experience

Applied Scientist II
September 2023 - Present
Organization: Amazon One

Applied Scientist I
September 2021 - September 2023
Organization: Amazon One

Worked on several research and development problems pertaining to the Amazon One palm recognition service spanning different components of the pipeline like improving recognition accuracy, rootcausing of failures, sensor obstruction detection, privacy etc. Also mentored an intern, participated in the hiring process and contributed to operational excellence in the team.

Graduate Research Assistant at Pattern Recognition and Image Processing (PRIP) Lab, Michigan State University
August 2019 - May 2021
Supervisor: Dr. Anil K. Jain

Worked on improving Face Recognition performance under aging, generating realistic 3D faces from 2D in the wild face images and developing a privacy preserving collaborative training framework for face recognition models

Research Intern at University of Bonn
May 2018 - August 2018
Supervisor: Dr. Angela Yao

Worked on learning stylistic compatibility between furniture images and developing visual textual based embedding networks that can answer retrieval queries based on both images and text

Research Intern at Indian Institute of Technology Mandi
May 2017 - August 2017
Supervisor: Dr. Aditya Nigam

Worked on improving the performance of gait recognition under multi-view setting, developing an end to end framework for estimating the quality of knuckle images as well as other applications of computer vision in biometrics

Publications

Recent Work


FedFace: Collaborative Learning of Face Recognition Model

D. Aggarwal, J. Zhou and A. K. Jain
in International Joint Conference on Biometrics (IJCB), 2021


Lifting 2D StyleGAN for 3D-Aware Face Generation

Y. Shi, D. Aggarwal and A. K. Jain
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021


Identifying Missing Children: Face Age-Progression via Deep Feature Aging

D. Deb, D. Aggarwal and A. K. Jain
in IEEE International Conference on Pattern Recognition (ICPR), 2020

PDF   IEEE   Supplementary   Slides   Poster   Video


Learning Style Compatibility for Furniture

D. Aggarwal, E. Valiyev, F. Sener and A. Yao
in German Conference on Pattern Recognition (GCPR), 2018


VGR-Net: A View Invariant Gait Recognition Network

D. Thapar, D. Aggarwal, P. Agarwal and A. Nigam
in IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), 2018

Arxiv   IEEE


FKQNet: A Biometrie Sample Quality Estimation Network Using Transfer Learning

G. Jaswal, R. Nath, D. Aggarwal and A. Nigam
in IEEE International Conference on Image Information Processing (ICIIP), 2017

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