Available for Internships / Roles

Hi, I'm Ashutosh Patel

I build |

Computer Science Student specializing in Machine Learning, Deep Learning, and building scalable intelligent systems. Passionate about solving complex legal, healthcare, and software challenges using cutting-edge AI.

View Projects
ai_agent_status.py
import tensorflow as tf
import torch

# Initialize Deep Learning Model
model = tf.keras.models.Sequential([
    tf.keras.layers.Dense(512, activation='relu'),
    tf.keras.layers.Dropout(0.3),
    tf.keras.layers.Dense(4, activation='softmax')
])

print("Initializing RAG Health Tracker...")
print("System Status: ACTIVE")
print("Accuracy: 98.42%")

About Me

Who I Am

I am currently pursuing my B.Tech in Computer Science Engineering at Amity University, Noida (2022 - 2026). I thrive on turning mathematical models and complex algorithms into real-world software applications that deliver tangible value.

My journey in software development has led me to work on various domains including Legal AI systems, computer vision translation models, and Retrieval-Augmented Generation (RAG) architectures. I am always excited to learn, adapt, and build in collaborative environments.

Location: Delhi / Noida, India

Education & Leadership

2022 - 2026

B.Tech in Computer Science Engineering

Amity University, Noida

Volunteer

Alias Tech Club

Amity University

Conducted technical workshops and hands-on sessions on Linux operating systems, Python programming, and Full-Stack Web Development. Provided mentorship and project guidance to junior students.

Skills & Expertise

My technical toolbelt, categorized by my core areas of focus.

Machine Learning & AI

Deep Learning (TensorFlow/PyTorch) RAG (LangChain / LlamaIndex) Hugging Face Transformers Computer Vision (OpenCV/MediaPipe) Scikit-learn & Random Forest NLTK / SpaCy (NLP) Pandas, NumPy & SciPy Matplotlib & Seaborn

Programming

Python C++ C JavaScript (ES6+) TypeScript HTML5 / CSS3 Java SQL Bash / Shell

Databases & Core

SQL / MySQL Data Structures & Algorithms Dynamic Programming & Greedy Graph Algorithms (BFS/DFS/Dijkstra) Search, Sort & Big-O Complexity OOP & Operating Systems Computer Networks

Industry Experience

June - August 2025

Software Engineering Intern

Open Health Systems Laboratory (OHSL)

Noida, India
  • Worked on requirement gathering, system analysis, and architecture design for radiology medical data integration.
  • Integrated radiology storage pipelines utilizing Orthanc (DICOM server) and OHIF Viewer.
  • Analyzed API-based medical image retrieval workflows for displaying PACS images dynamically inside web viewers.
  • Evaluated full data flows, focusing on medical image storage security, accessibility, and high-performance rendering.
  • Assisted in designing user interface wireframes and frontend workflow structures.

Featured Projects

A selection of my work in Artificial Intelligence, Computer Vision, and Predictive Analytics.

AI Agent & RAG

AI Agent Health Tracker

A real-time monitoring and debugging system utilizing Retrieval-Augmented Generation (RAG) to track and self-diagnose system health, log traces, and memory states of active AI agents.

LangChain FAISS Python FastAPI
Natural Language Processing

Legal Document AI System

An NLP platform fine-tuned on the CUAD dataset to analyze contracts and extract critical legal clauses with high reliability, securing EM: 79.15% & AUPR: 74.93%.

PyTorch Scikit-learn Pandas Python
Computer Vision

Hand Sign Recognition

An AI-powered system designed for real-time sign language gestures translation into text and speech, optimizing accessibility for hearing and speech impaired communities.

PyTorch OpenCV MediaPipe TensorFlow
Predictive Analytics

House Price Prediction

A machine learning regression model built to predict real estate prices, performing extensive data preprocessing, feature normalization, and benchmarking multiple algorithms.

Scikit-learn Python Seaborn Pandas

Get In Touch

Have a question or want to collaborate? Drop me a message!

Contact Information

Feel free to reach out to me directly through any of the channels below.

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