D Harish Kumaar

Computer Science Student | AI/ML & Full-Stack Developer
Bhopal, IN.

About

A highly motivated Computer Science student specializing in AI/ML, D Harish Kumaar demonstrates a robust foundation in full-stack development and data science. Proven through impactful projects like a fraud detection system achieving 82% precision and a scalable cross-platform event application. Eager to apply expertise in Python, PyTorch, React, and MongoDB to contribute to innovative technological solutions in a challenging role.

Education

VIT Bhopal University
Bhopal, Madhya Pradesh, India

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Bachelor of Technology

Computer Science and Engineering Specialization in AI and ML

Grade: GPA: 8.99

Standard Public School, Indore
Indore, Madhya Pradesh, India

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12th Grade (CBSE)

CBSE Curriculum

Grade: Percentage: 95%

Standard Public School, Indore
Indore, Madhya Pradesh, India

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10th Grade (CBSE)

CBSE Curriculum

Grade: Percentage: 91%

Awards

Reliance Undergraduate Scholarship Program

Awarded By

Reliance

Selected among the top 100 students nationwide for the prestigious Reliance Undergraduate Scholarship program, recognizing exceptional academic performance and potential.

Adobe India Hackathon Coding Round

Awarded By

Adobe India

Achieved a top 0.56% ranking out of 200,000+ participants in Adobe India Hackathon's competitive coding round, demonstrating advanced problem-solving and algorithmic skills.

Languages

English

Certificates

Salesforce Superbadge – Apex Specialist

Issued By

Salesforce Trailhead

Skills

Programming Languages

Java, Python, SQL, JavaScript, HTML/CSS.

Web Development

React.js, Node.js, Express.js, Tkinter.

Databases

MongoDB, MySQL.

Developer Tools & Cloud

Git, GitHub, VS Code, Visual Studio, AWS (basics).

AI/ML & Data Science

PyTorch, TensorFlow, OpenCV, Pandas, NumPy, Matplotlib, Scikit-learn.

Interests

Hobbies

Problem Solving, Gaming, Cricket.

Projects

Credit Card Fraud Detection

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Summary

Developed an advanced deep learning system to accurately detect fraudulent transactions in highly imbalanced datasets, leveraging autoencoders and optimized classification to enhance financial security and model generalization.

GetTogether

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Summary

Designed and developed a scalable cross-platform event management application, integrating real-time features and secure access control to significantly enhance user engagement and administrative efficiency.

Smart Attendance

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Summary

Created an AI-based attendance system using computer vision and machine learning for automated student tracking, improving accuracy and streamlining administrative processes for educational institutions.