Shubham Agrawal

CEO

Palo Alto, California, United States6 yrs 7 mos experience

Most Likely To Switch

Key Highlights

Expert in robotics and machine learning.
Experience at leading tech companies like Tesla and Adobe.
Strong academic background from top universities.

Stackforce AI infers this person is a Robotics and Software Development expert with a focus on Machine Learning.

Contact

agshubh191@gmail.com LinkedIn

Skills

Core Skills

Computer VisionRoboticsSoftware DevelopmentMachine Learning

Other Skills

AlgorithmsCC++Cascading Style Sheets (CSS)Data AnalysisGoHTMLJavaScriptLinuxNatural Language ProcessingNode.jsOptimization TechniquesPythonVimWeb Development

About

I am a Senior Researcher at Samsung Research America in New York City, where I work on robotics, computer vision, and machine learning. I am fortunate to be working under the supervision of Prof. Volkan Isler. Before joining Samsung, I received my CS master's from Columbia University with a focus on robotics and computer vision. During that time, I did several research projects under the supervision of Prof. Shuran Song. I did my Bachelor's in Computer Science from IIT Kanpur. In the past, I also worked at Tesla Inc and Adobe Systems as a software development engineer.

Experience

6 yrs 7 mos

Total Experience

1 yr 7 mos

Average Tenure

2 yrs 2 mos

Current Experience

Tesla

Senior Robotics Engineer

Mar 2024 – Present · 2 yrs 2 mos · Palo Alto, California, United States · On-site

Samsung research america (sra)

2 roles

Senior Researcher, Machine Learning Research

Promoted

Mar 2023 – Feb 2024 · 11 mos · New York, New York, United States

Engineer Machine Learning Research

Jun 2021 – Mar 2023 · 1 yr 9 mos · New York, New York, United States

Tesla

Autopilot Intern

Jun 2020 – Sep 2020 · 3 mos · Remote

Worked on identifying and associating the same objects visible in multiple cameras to create object tracks across time. Implemented and wrote verification scripts for object tracks outlier rejection component.

Columbia university in the city of new york

3 roles

Teaching Assistant (Applied Machine Learning)

Jan 2020 – Apr 2020 · 3 mos · New York, New York, United States

Course link: https://www.cs.columbia.edu/~amueller/comsw4995s20/

Teaching Assistant (Advanced Database Systems)

Jan 2020 – Apr 2020 · 3 mos · New York, New York, United States

Course website: http://www.cs.columbia.edu/~gravano/cs6111/index.html

Head Teaching Assistant (Computational Aspects of Robotics)

Jan 2020 – Apr 2020 · 3 mos · New York, New York, United States

University of southern california

Student Research Assistant

May 2019 – Aug 2019 · 3 mos · Los Angeles Metropolitan Area

Robotics Embedded Research Laboratory (https://robotics.usc.edu/resl/)
Worked on differentiable physics simulator which allows parameter estimation for nonlinear dynamical systems using automatic differentiation. Implemented Adjoint Method for getting fast differentials of integrated ODEs using C++ template metaprogramming.
Implemented simulation visualizer web app using nodejs+gulp+browserify and MVC architecture pattern (without framework). The web app has interactive 3D simulations (Babylon.js), player progress bar, plots, logs, and multi-window support (golden-layout).
Archive link: https://arxiv.org/pdf/2001.08539.pdf

Adobe

2 roles

Member of Technical Staff

Jul 2017 – Jan 2019 · 1 yr 6 mos · Noida, Uttar Pradesh, India

Implemented CRUD operations for highlight/underline/sticky notes for the next generation PDF web view using Javascript.
Formulated an efficient algorithm for modeling an annotation's position across multiple PDF views (with variable structure and content).
Shipped fixes for multiple critical security vulnerabilities (null pointer dereferencing, buffer overflow, JavaScript parameter tampering).

JavaScriptSoftware Development

Research Intern

May 2016 – Aug 2016 · 3 mos · Greater Bengaluru Area

Created a novel end-to-end system for automated design of affinity (user's interest) based smart geofences for selective targeting.
To unsheathe interest from sparse location-tagged browsing data, the three-step user affinity modeling approach sequentially utilizes pair-wise product-product, user-user, and semantic location-location similarities.
Users are segmented based on affinity using K-means clustering and CH-index. Final geofences are created by clustering nearby points using DBSCAN and calculating the boundary using alpha-hull.
US Patent US20180232767A1
Conference paper Smart Geofencing with Location Sensitive Product Affinity. ACM SIGSPATIAL 2017

Pariksha.co

Backend Developer Intern

May 2015 – Jul 2015 · 2 mos · Pune/Pimpri-Chinchwad Area

Engineered an algorithm that adaptively recommends questions depending upon student’s performance and question ratings.
We also modeled and programmed scalable adaptive question recommender system using GO language and MongoDB database as a micro service.
Also, Implemented Pariksha Practice Section for adaptive content and a Gamification engine with impact on 20K students