Aditya Aggarwal

Google | MSCS @ UCSD | Ex Microsoft Research | IIIT Hyderabad |

Aditya Aggarwal is a highly accomplished and driven individual with a diverse range of skills and experiences in the field of computer science. He is currently pursuing a Master's degree in Computer Science at the University of California and is actively seeking internship roles for Summer

3.5

Years of Experience

Education

university of california, iiit

Companies

google summer of code, microsoft, gojek, google summer of code, google summer of code, video analytics lab, iiit hyderabad, iiit hyderabad, iiit hyderabad

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Experience

2021 - 2021
google summer of code
Student Mentor | Robocomp
Mentored the project for the GSoC 2021 Sign Language Recognition: A component able to recognize words and phrases from WLASL dataset.
2021 - 2022
microsoft
Research Intern
Advisors: Dr. Mohit Jain and Dr. Nipun Kwatra Worked on the intersection of computer vision, machine learning, and HCI in the healthcare domain. Developed a mobile application and a video processing pipeline, which tracks retinal reflex and retinoscopic beam to estimate the refractive error of the human eye in smartphone videos without manual intervention.
2020 - 2021
gojek
Product Engineer
As a backend engineer, I worked on the ride-hailing platform (serving 4M+ daily users) in the Transport vertical to add on-demand features and improve the customer booking experience. Built a scheduling microservice with job execution and retry support, allowing users to book future rides.
2020 - 2020
google summer of code
Student Mentor | ROBOCOMP
Mentored the projects for the Google Summer of Code 2020. - Hand Gesture Recognition: A component able to recognize gestures from American Sign Language Dataset in real-time using the detected hand skeleton. - Human Re-Identification System: A component able to identify people using multiple modalities including the face, appearance, and silhouette.
2019 - 2019
google summer of code
Open Source Developer | Google Summer of Code 2019 | Robocomp
Created a People Identification System, able to identify people from very few training images with over 98% accuracy using Incremental and Few shot Learning techniques.
2019 - 2019
video analytics lab
Research Intern
- Advisor: Prof. R. Venkatesh Babu - Implemented an Adversarial Auto encoder conditioned via a discriminator to learn the pose embedding space for 21 skeletal hand joints from RGB images.
2018 - 2020
iiit hyderabad
Undergraduate Research Assistant
- Advisor: Prof. Ravi Kiran Sarvadevabhatla - Worked on Human Activity Recognition using 3D body and hand pose, achieved state-of-the-art accuracy of 88.80% on the NTU-120 dataset. Published at IJCV 2021. - Created a 3D-pose annotated skeletal action recognition dataset with over 125,000 In the Wild videos.
2018 - 2020
iiit hyderabad
Teaching Assistant
Responsible for taking tutorials, creating and evaluating assignments, projects, answer scripts for the following courses: - Computer Vision by Dr. Avinash Sharma (Spring 2020) - Digital Image Processing by Dr. Ravi Kiran Sarvadevabhatla (Fall 2019) - Digital Systems and Microcontrollers by Prof. K Madhava Krishnan (Fall 2018)
2018 - 2020
iiit hyderabad
Undergraduate Research Assistant
- Advisor: Prof. K. Madhava Krishna - Implemented a novel 3D shape and 6D pose estimation pipeline from monocular images using an occupancy network and differentiable renderer. Published at CVPR-Workshop 2020. - Proposed novel trajectory estimation pipeline which jointly optimized camera track, object’s shape and camera pose.