Ankush Gupta

Software Developer Intern

Delhi, India 0+ yrs exp 81 · Excellent

About

Computer Science undergraduate with an 8.56/10 GPA and industrial experience building AI-powered and full-stack applications. Skilled in Python, C++, TypeScript, machine learning, LLMs, computer vision, and backend development, with hands-on experience building and deploying production-ready systems.

Skills & Expertise (30)

Python Intermediate

7.4/10

0.5

Years Exp

OpenCV Intermediate

5.5/10

0.5

Years Exp

GitHub Intermediate

5.5/10

0.5

Years Exp

SQL Intermediate

5.5/10

0.5

Years Exp

Git Intermediate

5.5/10

0.5

Years Exp

C++ Beginner

5.0/10

0.5

Years Exp

MySql Beginner

5.0/10

0.5

Years Exp

Postgresql Beginner

5.0/10

0.5

Years Exp

React.js Beginner

4.9/10

0.5

Years Exp

JavaScript Beginner

4.9/10

0.5

Years Exp

REST APIs Beginner

4.5/10

0.5

Years Exp

Tailwind CSS Beginner

4.5/10

0.5

Years Exp

Node.js Beginner

4.5/10

0.5

Years Exp

Next.js Beginner

4.5/10

0.5

Years Exp

Prisma ORM Beginner

4.5/10

0.5

Years Exp

Express.js Beginner

4.5/10

0.5

Years Exp

Typescript Beginner

4.5/10

0.5

Years Exp

Docker Beginner

4.5/10

0.5

Years Exp

AWS Beginner

4.5/10

0.5

Years Exp

RoboFlow Beginner

4.0/10

0.5

Years Exp

YOLO Beginner

4.0/10

0.5

Years Exp

RAG Beginner

4.0/10

0.5

Years Exp

llm apis Beginner

4.0/10

0.5

Years Exp

Hugging Face Beginner

4.0/10

0.5

Years Exp

scikit-learn Beginner

4.0/10

0.5

Years Exp

TensorFlow Beginner

4.0/10

0.5

Years Exp

PyTorch Beginner

4.0/10

0.5

Years Exp

Streamlit Beginner

4.0/10

0.5

Years Exp

GitHub Actions Beginner

4.0/10

0.5

Years Exp

PGvector Beginner

4.0/10

0.5

Years Exp

Work Experience

Software Developer Intern

Bamigos VR LLP

Oct 2024 - Mar 2025

Engineered real-time interactive wall and floor projection systems, supporting up to 30+ FPS object detection with Python, OpenCV, and machine learning. Integrated Kinect & LiDAR sensors for 3D spatial mapping, enabling detection and tracking across a 1920×1080 projection area with approximately 60 ms processing latency. Developed a depth-based detection pipeline using OpenNI2, Gaussian filtering, morphological operations, contour detection, and homography mapping, achieving approximately 90% detection accuracy. Optimized detection thresholds, depth ranges, object-size filters, and camera parameters, reducing false positives by 90% and cutting detection latency from 300 ms to 60 ms.