MC

Maahi Chaurasiya

B.Tech CSE student · Aspiring Software Engineer / ML & GenAI Intern

Kanpur, Uttar Pradesh, India

@maahi_chaurasiya

0 followers

🎓 B.Tech in Computer Science and Engineering at Pranveer Singh Institute of Technology · Graduating 2028

About

Computer Science undergraduate with strong foundations in Data Structures & Algorithms, OOP, DBMS, and Operating Systems. Built backend systems and AI/ML applications using Python, FastAPI, SQL, LLMs, RAG, and Computer Vision, with experience in REST APIs, automated testing, and end-to-end ML pipelines.

Experience

  • Data Analytics Job Simulation Certificate
    Forage
    — – Present

    Performed forensic data analysis and classified case data as relevant or irrelevant using Microsoft Excel. Created an interactive Tableau dashboard to visualize forensic accounting findings and prepared recommendations based on completed analysis and identified patterns.

Education

  • B.Tech
    Computer Science and Engineering · May 2028
  • Class XII
    Vidyawati Nigam Memorial Public School
    May 2024
  • Class X
    Vidyawati Nigam Memorial Public School
    May 2022

Skills

Tools / apps / platforms

<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Git Pytest SQLite Tableau ChromaDB Microsoft Excel Jupyter Notebook

Projects

  • Python, FastAPI, Streamlit, Pytest, LLMs, HMAC, webhooks

    Designed a backend decision engine combining an LLM classification layer with rule-based logic to generate RETRY/BLOCK decisions for failed transactions. Built fault-tolerant processing with HMAC-secured webhooks, idempotent event handling, automated retry scheduling, retry limits, persistent event-attempt tracking, a monitoring dashboard, and end-to-end tests.

  • FastAPI, Streamlit, ChromaDB, EfficientNet, Grad-CAM

    Architected modular FastAPI REST endpoints for NLP and computer-vision inference services. Built an LLM + RAG prescription tool grounded in clinical guidelines and a skin-disease scanner, and fine-tuned EfficientNet on HAM10000 with Grad-CAM interpretability.

  • Streamlit, StandardScaler

    Built an end-to-end machine learning classification pipeline for loan default prediction, achieving 87.5% accuracy, 79.0% precision, and 80.3% recall on 600+ records. Engineered financial features and developed an interactive dashboard with risk indicators and model-performance metrics.

Courses & certifications

  • Python Programming · Infosys Springboard · 2025
  • AI/ML Course · Apna College

🏆 Achievements & awards

  • Adobe Hackathon Participant

    Participated in the Adobe Hackathon.

  • Flipkart GRiD Round 3

    Reached Round 3 in Flipkart GRiD.

Explore the Broxer community

🤖
Online · instant AI help
Broxer