I am a third year at Amrita Vishwa Vidyapeetham, pursuing a Bachelor's of Technology in my desired field of Computer Science. I have been an active member of the open-source community of my college, amFOSS ever since I joined college. I help in mentoring the juniors who join the club, as well as organize several events such as open-source contribution drives and workshops. I am a GitHub Campus Expert for my community, amFOSS.
I am also an active contributor to the organization FOSSASIA, where I was a summer intern in the summer of 2019. I worked as an android developer and helped improve Phimp.me by learning more about openCV and editing images. I also worked on developing the Badge Magic application for FOSSASIA from scratch and am a core developer of that too. I was also invited to the FOSSASIA OpenTech Summit, on March 2019 in Singapore. There I took part in the FOSSASIA-UNESCO hackathon where my team bagged the second prize in the IBM-Cloud category. Currently, I am working in the field of image processing using openCV. My paper on image processing also got selected for ICOL(Internation Conference on Optics and Electro-Optics) at IRDE which is a DRDO establishment. Later, I was also selected as an intern at IRDE, DRDO where I worked on automatic target detection. I completed my Google Summer of Code with the Mifos Initiative this year working on the project, "Computer Vision Based PPI Tool 2.0". Currently, I am working as an MLH Fellow.
Projects
Skills
Experience
- FOSSASIA - InternMay 2019 - August 2019
I overhauled cloud deployment of 2 applications, resulting in reduced run time performance by 30%. I helped in developing the hardware simulation, Badge Magic Android, of a LED name badge, by passing the 2D array into a filter of animation specific algorithm; this enabled people without the hardware to experience the hardware beforehand. My work was also on the Phimp.me Android application which is a photo editing tool using OpenCV. For both of these apps, I automated PlayStore and F-droid deployment process and improved the build time by 5 minutes using Fastlane tool, bash scripting, and continuous integration.
- DRDO - InternNovember 2019 - November 2019
I interned at IRDE, a DRDO establishment. During the internship, my work involved digital image processing, computer vision and automatic target detection using background differencing, frame differencing, and difference fusion. An algorithm was developed by me for automatic detection of moving ground targets, viz. vehicle, human, etc. in image sequences captured by an
infrared (thermal) imaging system. Experimental results demonstrated that the proposed algorithm can detect intruding targets in infrared imaging video with good accuracy. - Google Summer of Code - Student DeveloperMay 2020 - September 2020
My proposal, "Computer Vision Based PPI Tool Version 2.0", under the Mifos Initiative was accepted for GSoC 2020. Over the summer I worked on training models to accurately detect and classify objects in household environments and build an Android app to leverage MLKit for using tflite models and automatically fill PPI surveys. My work also involved collecting data of the needed objects, performing augmentation to increase the dataset size and training and converting models to tflite on the gathered data.
- Major League Hacking - FellowSeptember 2020 - Present
I have been selected as an MLH Fellow under the Explorer Track and will be working on making new projects using new tech stacks in a series of sprints over a period of 12 weeks. The first sprint is already over, and my team won the first prize in that.
- IRDE - InternMay 2020 - July 2020
IRDE(a DRDO establishment), was developing a fever screening system. The system uses a normal camera to capture video and an IR Camera to detect temperature. I worked on developing the software and integrating it with the hardware. My work involved detecting faces in the RGB video and scale these inputs to match the scale of the IR camera such that temperature of only the
facial regions could be extracted for which I used deep learning. A few parameters also change as the temperature of the IR camera changes when it is in use. I developed machine learning algorithms to automatically adjust the parameters so as to give the correct output. I also developed a GUI in python.