Hi, I'm Vikas,

a Computer Vision Developer.|

I help companies and people build Vision AI Solutions and Agentic chatbot Applications.

About Me

My journey into the world of AI and computer vision began back in college, where I immersed myself in exploring groundbreaking technologies and sharing the fascinating things I learned. What started as a passion for learning quickly evolved into a love for creating content, staying on the cutting edge of innovation, and working on projects that truly excite me.

Fast forward to today, I’m proud to be growing my personal brand while doing what I love—building, creating, and inspiring. I’m actively involved in several exciting ventures: 🚀 YouTube channel simplifying complex AI concepts, 🤝 Freelance projects and impactful collaborations. I’m also developing innovative products: 🤖 Agentic Chatbots for business process automation, 👁️ Real-Time Vision AI Systems powered by AWS and FastAPI

If you’re interested in collaborating, partnering, or exploring opportunities together, feel free to reach out. I’m always excited to connect with like-minded innovators and businesses ready to make an impact.

Code

Want my public code as well?

Check out my Github

Computer Vision, Gen AI, Machine Learning, Django, FastAPI, AWS, PyTorch etc.

Freelance

Youtube

I create videos about AI, Machine Learning, Deep Learning,
Computer Vision & My Life.

Company Collaborations

Syncopation AI

Promotion Videos

Projects

AI Chatbot for Travel Recommendations & Workflow Automation

I developed an intelligent Conversational AI Bot using Streamlit for travel assistance focused on historical monuments. It automates workflows like OTP verification, email-based guide delivery, and database integration, ensuring a seamless user experience.

Parking Spot Detection and Counter

This project implements a real-time system using computer vision and machine learning to detect parking spaces and vehicle occupancy in video streams. It employs efficient techniques like mask overlap, connected components analysis, and an XGBoost classifier for robust classification.

Accident Prevention Using AI/ML

The project builds a hardware-controlled car using Simulink, Raspberry Pi, and sensors, implements reinforcement learning for lane following, and develops a Modified U-Net segmentation model for vehicle identification, setting the stage for future integration to enhance traffic management.

vikaschelluru@gmail.com