Aditya Kaushik
Member Of Technical Staff at Salesforce
Haryana, India
Summary
👤
Senior🎓
Top SchoolAditya Kaushik is a Full Stack Mobile Developer with nine years of engineering experience and five years focused on mobile, currently building Life Sciences Cloud features at Salesforce to modernize healthcare workflows. He previously spent four years at Lowe’s driving cross-platform mobile and backend integrations—working on AR (RealityKit), deep linking, SwiftUI migrations, BFF layer integrations, and performance testing—to improve customer experiences at scale. An NIT Kurukshetra alumnus with top academic standing, Aditya pairs product-minded engineering with hands-on implementation, from networking engines to analytics and SDK integrations. He is also an active open-source contributor to notable Android projects like fossasia/phimpme-android, where he improved UI/UX and polished transitions and navigation. Known for bridging healthcare and e-commerce domains, he focuses on delivering stable, performant apps and automations that meaningfully impact users.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Technology, Computer Engineering, 9.57, Bachelor of Technology, Computer Engineering, 9.57 at NIT Kurukshetra
Github Skills (12)
javas10
uid10
front-end-development10
android10
java10
navigation-drawer9
ui-design9
navigationview9
interface-design9
navigationbar9
user-interface9
transition8
Programming languages (8)
Github contributions (5)
fossasia/phimpme-android
Sep 2017 - Oct 2017
Photo Imaging and Picture Editor
Role in this project:
Mobile Developer (Android)
Mobile Developer (Android)Contributions:20 commits, 21 PRs, 43 comments in 1 month
Contributions summary:Aditya primarily contributed to the user interface and functionality of the Phimp.me Android application. Their work involved fixing bugs related to the status bar, home button, and navigation icons, indicating a focus on improving the user experience. They also addressed issues with the app bar and implemented shared element transitions for a smoother user journey. Furthermore, they made adjustments to the slideshow feature.
imaging
97k/spam-ham-web-app
Aug 2018 - Oct 2018
A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link
Contributions:39 commits, 2 PRs, 14 pushes in 1 month
backendmachine-learningtext-classificationtfidfnlp
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