In the Social Innovation Business Development project, I collaborate with the Bayer Foundation and Dockokids, a nonprofit focused on accessible healthcare for children. After analyzing Dockokids’ business model, we identified operational challenges and concluded that a dashboard for day-to-day operations is necessary. We are currently building this dashboard to integrate datasets, aiming for a 30% improvement in data analysis efficiency and a 20% boost in productivity. Additionally, we plan to conduct exploratory data analysis (EDA) to predict patient traffic and, if time allows, develop a chatbot for initial screening.

In the Implementation of Reweighted Models for Robust Deep Learning project, I achieved 96% accuracy on highly imbalanced datasets (200:1) with 25% noise by enhancing CNN training through a class and sample reweighting mechanism. Additionally, I improved the accuracy of VAR foul detection by 30% in datasets with 50% noise while effectively reducing computational overhead during processing. This approach not only strengthened model robustness but also streamlined performance, demonstrating the effectiveness of reweighted models in handling challenging datasets.

In the Stock Exchange Market Analysis project, I conducted data analysis on 20 companies across four sectors to quantify inter-sector relationships, delivering actionable insights for market strategies. Utilizing historical trading data and the Crystal-Ball predictor, I forecasted stock prices with an impressive 80% accuracy. This project honed my expertise in predictive modeling and analysis, enabling me to identify trends and correlations within the market. The insights gained not only informed strategic decision-making but also enhanced understanding of market dynamics across different sectors.

In the Music Genre Detection project, I classified raw audio samples into 10 genres using audio features such as MFCCs and Chroma energy, showcasing advanced signal processing techniques. I developed a machine learning model that employed PCA, ANN, and KNN, demonstrating my proficiency in applying AI models to real-world datasets. This approach enabled me to achieve over 90% accuracy in genre classification, highlighting the effectiveness of combining various techniques in music analysis. The project significantly enhanced my skills in audio processing and machine learning for genre identification.

In the International “Rowboatics” Competition at TechFest, IIT Bombay, I designed and developed an RC boat prototype using SolidWorks, ultimately securing 1st place by optimizing functionality through innovative designs. I managed the project’s timeline and budget, ensuring on-time delivery and successful testing, which showcased my project management skills in a competitive environment. This experience not only honed my technical abilities in design and prototyping but also strengthened my capability to coordinate resources effectively, balancing creativity with practical constraints to achieve outstanding results.

At the Access for All: Hackathon held at Thapathali Institute of Engineering, I collaborated to design and prototype an extendable prosthetic arm using SolidWorks, enhancing functionality for differently-abled users by 40%. Our team secured 3rd place out of over 50 teams by creating a cost-effective and functional solution, showcasing our prototyping and mechanical design capabilities. This experience not only deepened my understanding of inclusive design but also reinforced my ability to work effectively in a team, focusing on innovative problem-solving for real-world challenges.