PhD student at the Center of Excellence for AI, IIT Kharagpur.
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RCAP-dynamic-dataset-pruning
June 11, 2025 – Present
DataCull is a modular, light-weight data pruning library containing many dataset pruning (coreset selection) algorithm including the official Implementation of the paper, titled, RCAP: Robust, Class-Aware, Probab ilistic Dynamic Dataset Pruning
View ProjectAIML-Coding-Lab-Material
February 26, 2024 – April 5, 2024
This Repository contains the lab coding files for machine learning and deep learning.
View ProjectFRUFS
March 10, 2022 – January 6, 2024
An unsupervised feature selection technique using supervised algorithms such as XGBoost
View ProjectPyImpetus
September 19, 2020 – February 26, 2025
PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
View ProjectRegression_ReSampling
June 9, 2020 – August 7, 2020
A python library for repurposing traditional classification-based resampling techniques for regression tasks
View Projectmanual_spellchecker
May 27, 2020 – August 29, 2020
A manual spell checker built on pyenchant that allows you to swiftly correct misspelled words
View ProjectCompetition-code
April 30, 2020 – August 5, 2021
This repository contains code I wrote for all the competitions that I participated in
View ProjectNovel-undersampling-techniques-CROUST-and-ICROUST
July 26, 2019 – July 26, 2019
Code for the work published in the 19th Industrial Conference on Data Mining, ICDM
View ProjectClustering-based-Topic-Recommendation
February 15, 2017 – April 30, 2020
Winter Internship at the Indian Institute of Technology, Kharagpur
View ProjectCultural Fit Analysis
The candidate's profile shows a strong focus on individual technical projects, primarily in Python and Jupyter Notebook, which aligns with the technical demands of a Data Scientist role. However, the lack of diverse project types (e.g., team projects, deployment, different domains) and limited technology stack beyond Python might indicate a narrower scope of experience. The absence of work experience or education details makes it difficult to assess broader cultural fit, adaptability, or experience in diverse work environments.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a strong technical focus and independent work, but collaboration, communication, and problem-solving in a team context cannot be evaluated.