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Hi, I'm Shourya Kumar

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Machine Learning Engineer specializing in computer vision, deep learning, and production-grade ML systems. Published researcher & SIH 2024 Finalist.

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About Me

Shourya Kumar

ML Engineer & Researcher

I'm a Computer Science undergraduate (B.Tech 2026) passionate about building intelligent systems that solve real-world problems. I've engineered a production biometric authentication system achieving 96.8% True Acceptance Rate across 120 users with encrypted inference pipelines.

My work spans computer vision, deep learning, and applied ML — from designing multi-stage biometric pipelines with ArcFace embeddings to building IoT-driven agricultural intelligence systems. I'm also a published researcher with a CRC Press book chapter on Generative AI for Healthcare.

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SIH 2024 Finalist

Smart India Hackathon

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Anveshna 2024 Finalist

Research Innovation

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IEEE NGISE Presenter

Conference Speaker

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Published Author

CRC Press Book Chapter

Technical Arsenal

Programming

Python SQL

ML Frameworks

PyTorch TensorFlow Scikit-learn Keras HuggingFace

Machine Learning

Classification Regression NLP Feature Engineering Hyperparameter Tuning

Deep Learning

CNNs Transfer Learning Embeddings Real-time Inference

Computer Vision

OpenCV MTCNN ArcFace Liveness Detection

ML Deployment

Flask REST APIs AES-RSA Encryption Model Inference

Data Analysis

NumPy Pandas EDA Statistical Analysis

Tools & Concepts

Git GitHub DSA System Design OOP

Featured Projects

2025–2026

NiyuktiSetu

AI/ML-Based Government Recruitment Authentication

Engineered a 3-stage biometric pipeline using MTCNN face detection, 128-D ArcFace embeddings, and dual-path liveness classifier for secure government recruitment authentication.

96.8% True Acceptance Rate
96.2% Spoof Rejection
<500ms Response Latency
  • 3-stage biometric pipeline: MTCNN → ArcFace → Liveness
  • Hybrid AES–RSA encryption for 100% data security
  • Flask REST API with sub-500ms end-to-end latency
  • Evaluated across 200-user dataset
Python OpenCV MTCNN ArcFace AES-RSA Flask
GitHub
2024–2025

Irrigo

AI-Based Crop and Water Management System

Built a real-time IoT data pipeline with multi-class ML classification for intelligent irrigation and fertilizer recommendations, reducing estimated water usage significantly.

15-20% Water Reduction
3 IoT Sensors
6 Crop Datasets
  • Real-time 3-sensor IoT pipeline (soil moisture, temp, humidity)
  • Multi-class classification for irrigation recommendations
  • Filtered ~18% noisy/missing readings via EDA
  • 5-minute interval time-series data collection
Python Scikit-learn IoT NumPy Pandas
GitHub

Research & Publications

2025

Data-Driven Agricultural Management System

Patent Application No: 202511017657

An integrated ecosystem designed to empower farmers through resource optimization, providing direct market access and real-time agricultural intelligence.

  • Direct buyer marketplace for fair pricing
  • Location-based crop & fertilizer suggestions
  • Real-time government program updates
  • AI chatbot for personalized advisory
  • Rental service for modern farming tools
Resource Optimization Smart Farming IoT Analytics
View Patent
2026

GenAI in Healthcare Application

CRC Press Publication (ISBN 9781032784847)

Exploration of generative AI pipelines for clinical diagnostics and synthetic data generation for privacy-preserving model training.

  • GenAI pipelines for clinical diagnostics
  • Synthetic medical data generation
  • LLM-based decision support systems
  • Privacy-preserving model training
Healthcare AI GenAI LLMs Data Privacy
View Publication

My Education

Sep 2022 — Apr 2026

B.Tech in Computer Science & IT

Dr. A.P.J. Abdul Kalam Technical University, Lucknow

CGPA 7.38 / 10

Relevant Coursework

Machine Learning Artificial Intelligence Data Structures & Algorithms DBMS Operating Systems Computer Networks

Get In Touch

Interested in collaborating or have an opportunity? Let's connect!

Email

shourya.writes1@gmail.com

Phone

+91 9410002547

GitHub

Shourya-here

LinkedIn

shourya-kumar-here
Noida, India
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