Dec 2020 – Oct 2021 · 10 mos

Nov 2018 – Nov 2020 · 2 yrs

Mar 2017 – Oct 2018 · 1 yr 7 mos · Bengaluru Area, India

• Projects:
• 1. Moto key, a password manager. It has three components; Android app, windows app and browser extension. User credentials are saved in phone which can be retrieved back by biometric authentication of the user and websites get logged-in in windows browser. Extensions are supported in Google Chrome, Mozilla Firefox and Microsoft Edge. Extensions are developed in typescript (javascript).
• 2. Moto voice, a voice assistant app for Motorola android phones where user can give voice commands to his phone and phone takes action. This app supports system settings (like "turn on Wi-Fi", "increase phone volume" etc), app actions (like "open WhatsApp", "call <contactName>", "open Gmail" etc) and web search (like "how is the weather", "what is the stock price of amazon?" etc).
• Technologies used: JAVA, Android, Nuance grammar, NLP libraries to get STT.

Jun 2015 – Feb 2017 · 1 yr 8 mos · Bengaluru Area, India

• I developed for Mobiquity product in Mobile Financial Services Unit. This product is like a banking software which has number of stack holders and provides a number of services to its users. Its Users use their wallets to do a transaction. Technologies and tools which are used for the project are Java spring boot, struts, hibernate, postgres, oracle, rabbitMQ etc

May 2014 – Jul 2014 · 2 mos · Bangalore

• I worked on Object Detection and Localization (specifically face detection) in images using Machine Learning. I used Visual Studio Platform to write the code and the code was written in C++ with using openCV. Here, I had two phases- Training Phase where machine learns and another was Testing Phase where images are tested on the basis of the model resulted from the training phase. that model is know as Trained Model. In that Train Model, I stored the features for the training images at the time of training and checked for each test image whether the given test image has same features as are stored in model or not. if they matches Positive outcome results else Negative. Training and Testing image Sets were mutually exclusive to each other. Technique used for the detection of objects in image was BING objectness (where objectness defines how easily it is for an image window to cover objects in the image.) Features were the LGP Features.
• Skills: OpenCv | Machine Learning | Windows 8 | Visual Studio 2010 | C++ Language

Jul 2011 – Apr 2015 · 3 yrs 9 mos · Dhanbad

• Projects:
• I worked in Web Development for the backend part. I designed a web portal named 'Timetable Management' for the automation of timetable management in a college. It has four kinds of users each having their different authorization and work. HOD of a branch, Professor of a branch, Student of a branch and Data Entry Operator. HOD may Deny or Accept the request he is getting. He also can decide timetable for a class according to his choice if the given choice is available. Professor can decide timetable for a class according to his choice if the given choice is available. Student can check the timetable for him/her and for any of his/her friends. Data Entry are employed in order to prepare the database including what are the subjects available for a particular student, what subjects can a teacher teach to student, who is the Hod of which branch, how many branches are there and many more.
• Skills: JavaScript | HTML | PHP | MySQL | CSS3