Hello, I'm

Atul Kumar

Machine Learning & Data Enthusiast

Building intelligent algorithms, automating data pipelines, and transforming unstructured data into actionable insights.

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Atul Kumar

About Me

Engineering student at Birla Institute of Technology, Mesra (B.Tech Chemical, 2023–Present). Passionate about technology-driven problem-solving and machine learning.

My toolkit includes Python, Scikit-learn, SQL, and Deep Learning. I thrive on processing large datasets and building AI-driven features to deliver innovative digital experiences.

Interests & Focus Areas

Machine Learning Data Pipeline Automation Computer Vision Predictive Modeling
TREND ANALYSIS
DEEP LEARNING
PREDICTIVE MODELS
NLP
COMPUTER VISION
DATA PIPELINES

Experience

Jan 2026 – Present

Machine Learning Intern

Narnetix Ai (Remote)

  • Built 3+ AI-powered autonomous agents using LLMs to automate business workflows, contributing to 95% reduction in manual tasks.
  • Designed and deployed 5+ workflow automation pipelines integrating n8n, Zapier, and REST APIs to streamline operations.
  • Developed 2+ AI-driven data analysis modules for predictive insights and anomaly detection to support business decisions.
  • Integrated AI systems with 4+ enterprise tools (CRM/ERP platforms), achieving 3.5× in operational efficiency.

Education

2023 – Present

B.Tech in Chemical Engineering

Birla Institute of Technology, Mesra

Pursuing Bachelor of Technology in Chemical Engineering.

2021 – 2022

Higher Secondary (Class 11, 12)

Chinmaya Vidyalaya, Bokaro Steel City

Featured Projects

Automated Email Outreach System

Feb 2026

Developed a Python CLI automation tool using Pandas to send emails to 100+ HR contacts. Integrated secure Yagmail SMTP handling and a preprocessing pipeline. Designed rate-limited batch delivery protocols, decreasing manual effort by 90%.

Python Pandas SMTP Validation

Dental Caries Segmentation (YOLOv8s-Seg)

Jan 2026

Built an end-to-end instance segmentation pipeline to detect dental caries from radiographic medical imaging. Trained high-resolution images emphasizing recall optimization using AdamW and cosine learning-rate scheduling.

Deep Learning YOLOv8s-Seg Computer Vision

Market Regime Detection

Dec 2025

Analyzed weekly NIFTY 50 trading data (2018–2025) via rolling 5-week return calculations. Applied unsupervised time-series clustering to algorithmically classify market states based on multi-variate volatility signatures.

Machine Learning Scikit-learn Time Series clustering

Technical Expertise

Languages & ML Tech

Python, C, C++, PyTorch, Scikit-learn, NumPy, Pandas

Machine Learning Concepts

Supervised & Unsupervised Learning, Regression, Classification, Clustering, Model Evaluation, Computer Vision

Data & Cloud

MySQL, Power BI, Tableau, AWS, Google Cloud, Docker

Web & Tools

HTML, CSS, JavaScript, Git, Jupyter Notebook, WordPress

Get in touch

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