About
In 2009, witnessing the assembly of a computer was a moment of sheer enchantment for me. That experience sparked a profound love for technology. Since then, I've plunged headfirst into the captivating world of programming, tirelessly exploring and unraveling the mysteries of this incredible gadget.
Currently, I am pursuing my joint masters at Åbo Akademi University and University of L'Aquila, being funded by Erasmus Mundus Scholarship. Before this, I did my undergrad from India.
During this summer, I got the amazing opportunity to build a Computer Vision app for a large transport company in Finland. Previously, I have had the joy of working with an innovative DaaS platform provider, and a large multinational company.
When I am not discharging my brain cells or wondering over my life, I usually go biking, play my favorite songs, or look for the deepest mysteries of human behaviour.
An interesting fact about me - I speak 8 languages (no, I am not talking about the programming languages).
Experience
2024 - Present
Software Development Trainee • Ahola Digital Oy Ab
Created a web app to detect cargo truck artifacts using computer vision models and deployed it as a PWA. Also created an algorithm to remove backgrounds from the images and apply user specified enhancements.
2020 - 2023
Software Engineer • EQ Technologic LLC
Developed an NLP-powered search feature, allowing users to quickly find relevant information. Designed, developed and deployed microservices which resulted in substantial reductions in data retrieval times.
Projects
2024
Magnus Gräsbeck website
Built a website for Magnus Gräsbeck, a Finnish musician and trubadur. The website showcases his performances and his extensive career.
2024
Human Activity Recognition Using Smartphones
Developed a machine learning model to cluster human activities such as walking and sitting, recognized through sensor data from smartphones. I employed K-Means and DBSCAN for clustering. Used dimensionality reduction techniques such as PCA, t-SNE, and UMAP to enhance computational efficiency and visualization of clusters.
2024
Playing Pacman using Reinforcement Learning
Developed a Deep Convolutional Q-Learning (DCQN) agent to play the Pac-Man game, leveraging deep learning and reinforcement learning techniques to learn optimal strategies for navigation, ghost avoidance, and score maximization.