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Software Engineer | MS CS @ UMass Amherst | Ex - FIS Global
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KubeHealth
February 3, 2026 – Present
This project was built to understand how real Kubernetes controllers work under the hood, including watches, in-cluster authentication, RBAC, graceful shutdown, and containerized deployment — without relying on higher-level operator frameworks.
View Projectdishachiplonker.github.io
November 10, 2025 – November 10, 2025
My portfolio site: projects, resume, and blog posts
View ProjectQuick-Saver
June 27, 2025 – June 27, 2025
Chrome extension + FastAPI backend for saving text-selected tasks and scheduling reminders.
View ProjectScholar-Companion
April 29, 2025 – May 6, 2025
A web app that lets users upload academic papers (PDFs) and then chat with a generative AI about their contents—answering questions, summarizing sections, or extracting key insights.
View ProjectUniThrift_Frontend
November 20, 2024 – December 13, 2024
University Buy Sell Application Front End
View ProjectMULTITASK-TRANSFORMER
June 8, 2024 – June 8, 2024
Implemented a sentence transformer to handle a multi-task learning setting of Sentiment Verdict (Binary Classification) and Sentiment Intensity (Sentiment Analysis as Numerical Values)
View ProjectMOVIE-RECOMMENDATION-SYSTEM
May 29, 2024 – November 3, 2025
Designed a movie recommendation system to analyze the data and implement a machine learning algorithm to generate movie recommendations for the user. Used Apache Spark to process the data since it is a scalable data processing engine. The data processing and manipulation will be done by using the data-processing engine provided by Spark.
View ProjectAgriculture-Yield-and-Crop-Prediction
March 24, 2024 – March 24, 2024
Modeled the Random Forest Regression to forecast the agricultural production and predication of alternate crop to maximize yield production for a certain location using a variety of criteria, including the crop, the state, the district, the season, and the area of the plot of land. Designed an interactive frontend using HTML and CSS
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and demonstrate a strong interest in self-learning and exploration across various domains, including data science, web development, and even Kubernetes. This indicates a proactive and curious mindset. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative work environment. The diversity of projects, while showing breadth, also suggests a potential lack of deep specialization in a single area, which might require more focused development for a senior role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest an ability to work on self-directed projects.