Skill Areas

As a .NET Developer, I created many web applications ranging from simple static websites to sophisticated, multi-layered applications. Apart from .NET, I used various other technologies and frameworks like AngularJS and NHibernate. HTML-CSS and JavaScript are the bread and butter in my domain.

I developed mobile applications for iOS devices using both Objective-C and Swift. By writing custom plugins using Apache Cordova, I extended the native functionality of iOS. During my tenure as a mobile developer, I created both native and hybrid applications. As a result, I am super comfortable with XCode and macOS environment.

I possess hands-on experience in creating, managing, and maintaining databases in Microsoft SQL Server and MySQL on the database side. I can write moderately complex queries, stored procedures, and functions as well.

I have created desktop applications for Windows using the WPF framework. From simple, convenience-based software to intricate, niche desktop programs, the applications I developed cover various uses. I am also familiar with XAML in creating GUIs.

I possess good Cloud technology experience as I have worked on Lambda, Lex, Polly, API Gateway, SNS in AWS and Firebase in Google. I used Lex and Polly to train the chatbot to give responses. Lambda helped me perform business logic on responses and API Gateway acted as a webhook to intercept requests and responses. I set up automatic notifications through SMS and email service using SNS. I used Firebase to test custom push notifications in a sample Android application.

I've dabbled into the field of Artificial Intelligence and Machine Learning as well. Using AWS Lex and Lambda, I created a chatbot for voice-based interaction. The chatbot handles customer service for the organisation by providing basic information to the users through voice. The users can ask the bot about the organisation's work hours or services they offer, and the bot responds with the corresponding information.

I also trained a machine learning model using TensorFlow to identify different sets of images. By giving input of several cheque images, I trained the model to identify whether a cheque was front-side up/back-side up, filled/blank, and signed/unsigned.