In my 4 years of course work I have had the opportunity to connect and work with professors and peers on various projects varied in domain and specialisation. I have taken part in various hackathons and events that required innovation, on the feet thinking and technical problem solving.
The knowledge and experiences I have acquired in the last few years, helped me realise my true passion lies in Audio Signal Processing and particularly in the field of Music Technology.
'1e0a': A Computational Approach to Rhythm Training
Under the guidance of Dr. Ranjani H.G.
In this work we develop an automated learning application based on feedback from a user to promote the learning of basic rhythmic patterns. The application is built to mimic a teacher-student relationship where, the subsequent levels of pattern complexity are generated based on the performance measured on the current pattern played by the user. The web application built for the project serves as a data collection tool to test my rhythm education hypothesis, kindly do register and help me in my research.
Sound Event Localization Using an End to End Deep Convolutional Neural Network
Under the guidance of Dr. Ajey S.N.R.
As part of my final year thesis project, I am working on implementing a novel end-to-end deep convolutional neural network architecture operating on multi-channel raw audio data to localize multiple simultaneously active acoustic sources in space. As proposed by Dr. Harshavardhan Sundar.
Audio Sense is an Alexa game skill that makes use of Alexa Conversations. It aims to help and train players to cope with Auditory Hypersensitivity and distractive environmental sounds. The skill sets up a game environment that can span over multiple settings and levels. The goal of the game is for the player to zone out auditory disturbances in a given environment to discern only the necessary and valid information from the same.
A web-based musical instrument with a mind of its own.
Uses Google's Magenta.js trained machine learning models to generate it's own sequence of melodies and randomise drum grooves.
[(MK91) SIH FINALS PROJECT] SUB-CENTRE FOCUSED HEALTH CARE SYSTEM FOR THE GOVT. OF UTTARAKHAND
There's acute shortage of accessible health care in smaller towns and remote villages of Uttarakhand. We developed a system solution to this problem with the following points focussed upon :
Generation of a cloud based electronic health record system, implementing aadhar authentication.
Access to medical records and database for medical professionals using Biometric/Facial ID, for emergencies and diagnostic purposes.
Telemedicine / Call Centre setup for doctors implementing DTH or 2 way communication technology without being dependent on ISP.
CRACK ANALYSIS IN BRIDGES AND OTHER STRUCTURES
This project is a mechanism based on IOT-automation that can detect cracks in structures (Living Spaces and Flyovers). The system gathers information from the magnitude of vibrations produced by the structure using vibration sensors which relay information to a database for further data collection, analysis, and future reference. After the gathered data is analysed, the concerned authorities are notified about the condition of the structure.
PESU I/O Courses is a first-ever peer-peer learning system, where students interact with Subject Matter Experts of a plethora of domains ranging from Co-Curriculars to Extra-Curriculars. It implements the concept of a flipped classroom, where the juniors gain insights and aspire to be like the SME, and the SMEs have an intellectually stimulating, worthwhile experience.
I was a Subject Matter Expert (SME) for the certified course 'An Engineer's Guide To Music Technology'. I formulated the whole course material and guided a class of 40 students over 4 weeks (8 sessions) with group discussions and assignments. Along with mentorship for a final project.