Indy iOS Engineer & Android Developer | ML / NN / DL / CV Developer

Objective

An opportunity to work and upgrade oneself, as well as being involved in an organization that believes in gaining a competitive edge and giving back to the community. I'm presently expanding my solid experience in iOS and Android developments. I focus on using my interpersonal skills to build good user experience and create a strong interest in my employers. I hope to develop skills in mobile app developments and my knowledge of computer vision, and become an good and honest asset to boost the business growth. As an individual, I'm self-confident you’ll find me creative, fast worker, and naturally passionate. I’m a forward thinker, which others may find inspiring when working as a team.

What I Do ?

I have been working as an iOS engineer and android app developer since, I have a passion to build clean and interactive UI, elegant styling, and I have lots of experience in the production of swift/objective-c and kotlin/java for native mobile apps. I loving creating awesome as per my clients’ need. I think user experience when I try to craft something for my clients. Making an apps awesome without putting aside the flow side of the business logic. Sometimes I also work with Python, using Flask to deliver the data or machine learning model into an accessible api and sometimes I also use PHP to support it. I always use extreme programming methodology to speed up iterations and improve the quality of the products that I build You can also think of me as a full-stack developer.

• UX/UI Design
• Native iOS app
• Cocoapods / Carthage as dependency manager for Cocoa
• Native Android app
• Gradle as a build systems for Android
• Python with Flask for RESTful API Services & Web App
• Python for Computer Vision
• PHP for RESTful API Services & Web App

Publications

I also have some research which I have poured through scientific papers specifically in the field of deep learning computer vision. You can see all of my publications through the following Google Scholar and ResearchGate accounts.

• G. Scholar
• ResearchGate

You can direct read my scientific paper here:

- Instance-Aware Semantic Segmentation for Food Calorie Estimation using Mask R-CNN (IEEE | ResearchGate)
- Comparison of Supervised Learning Image Classification Algorithms for Food and Non-Food Objects (IEEE | ResearchGate)