Nihal Dias

Microsoft Learn Student Ambassador

Microsoft Learn•  August 2020 - Present

Microsoft Learn Student Ambassadors are a global group of campus leaders who are eager to help fellow students, create robust tech communities and develop technical and career skills for the future. As a Microsoft Learn Student Ambassador, I: - Contributed to the Microsoft Docs website by co-authoring the 'Language Understanding in the Azure Health Bot' module in the Azure Health Bot Learning Path. - Talked about Language Understanding in the Azure Health Bot as part of a 4 episode learn live series on Microsoft Reactor. - Co-conducted a workshop, ' Microsoft Azure Core Services: Compute' which gave a brief introduction to Azure as well as Cloud Computing concepts and also included a demo on how to create a VM in Azure. - Co-conducted the workshop, ' Deploying Web Apps on the Cloud with Microsoft Azure ' where we explained Cloud Computing concepts, gave a demo on deploying a WordPress website on Azure and also a demo on how to create a Movie Recommendation Web App on Azure.

Flutter UI Developer

ALLSKIER Solutions Pvt Ltd•  July 2021 - September 2021

• As a part of ALLSKIER, I worked on building cross-platform IoT based apps that interface with hardware to create fully-fledged Edge Computing solutions. • Conducted a webinar, "Fly with Flutter" where I explained the basics of Flutter and App Development. • Conducted a webinar, "Cloud Computing with Microsoft Azure" as part of their "7 days 7 stories" event where I explained the basics of Cloud Computing and Creating a VM on Microsoft Azure. • Co-authored a research paper, which is going to be presented at the "International Conference on Artificial Intelligence, Computational Electronics and Communication System (AICECS 2021)"

AI Team Member

RUGVED Systems•  September 2019 - May 2020

RUGVED is a Student Project recognized by MIT Manipal, working in the field of AI Robotics. I worked on implementing the mapping stack of SLAM using ROS on autonomous bots and also made an OpenCV model for lane detection.