Skip to content
View Apumukherjee819's full-sized avatar
🌴
Always On vacation
🌴
Always On vacation

Block or report Apumukherjee819

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Apumukherjee819/README.md

ARPAN MUKHERJEE

B.Sc. STATISTICS · Minor in Computer Science · RKMRC,NARENDRAPUR — CPI 9.45

Codeforces Leetcode LinkedIn ResearchGate


Second-year Undergraduate at RAMAKRISHNA MISSION RESIDENTIAL COLLEGE. I compete on Codeforces,interested in Model fitting , database schema,time series Analysis,hypothesis testing, big data analysis.

 Tech Stack

C++ Python C SQLAlchemy Streamlit NumPy Git


 Competitive Programming

Codeforces Rating-1007  ·  max rating 1007  ·  300+ solved DSA problems in various difficulty levels on LEETCODE

LeetCode Stats

 Projects

IDEAS TIH ISI,Kolkata — a prototype decision-support system for risk-aware flood evacuation. It uses flood-risk indicators and Particle Swarm Optimization (PSO) to identify routes that balance travel cost, flood-risk exposure, and movement toward safer, higher-elevation locations.. AUC-ROC - 94.6 | Stratification Division : (10.84% + 77.13% + 12.03%),Reduction Of Evacuation Time : 33%

ARTHASETU-2.0,FINANCIAL INCLUSION AND ONBOARDING TRUST ANALYSIS - ARTHASETU 2.0 is an adaptive financial inclusion platform built for the BUILD $ BANK 2026,IIT DELHI (Track 1: Financial Inclusion for the Underbanked). It addresses the challenge of 300+ million credit-invisible gig workers in India who lack traditional credit histories — despite having verifiable trust signals like rental payments, medical expenses, and bill payment histories.The platform uses a statistical user-profiling engine that dynamically adapts interface, guidance, and pacing for first-time financial users. It combines machine learning (XGBoost, 99.5% accuracy) with 10-layer post-quantum security (ZKP, FHE, PQC) to build trust while protecting user data.

codeforces-solutions — still contaminate the at the beginner levels.

Pinned Loading

  1. CODEFORCES-PROBLEMS-AND-SOLUTIONS CODEFORCES-PROBLEMS-AND-SOLUTIONS Public

    This repo contains the question and the solution of the problems In the codeforces

    Python 1

  2. Underbanked-and-Financial-Inclusion---ARTHASETU-2.0- Underbanked-and-Financial-Inclusion---ARTHASETU-2.0- Public template

    Adaptive Financial Inclusion Platform for credit-invisible gig workers. Trust scoring using ML (XGBoost, 99.5% accuracy), multi-language onboarding, and a 10-layer post-quantum security architectur…

    JavaScript 3 2

  3. FloodSafePSO-A-Particle-Swarm-Optimization-Model-for-Risk-Aware-Flood-Evacuation FloodSafePSO-A-Particle-Swarm-Optimization-Model-for-Risk-Aware-Flood-Evacuation Public

    FloodSafePSO uses flood-risk data and Particle Swarm Optimization to identify safer evacuation routes. It considers rainfall, water level, elevation, population, and infrastructure to classify risk…

    Jupyter Notebook 1

  4. Apumukherjee819 Apumukherjee819 Public

    This repository demonsrate Who I am

    TypeScript 1