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Karan Singh Gurjar
Karan Singh Gurjar

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Building AI Projects

#introduction #ai #machinelearning #flutter

Hi everyone, I’m Karan Singh Gurjar, an M.Tech Computer Science Engineering student interested in AI/ML research, software development, and building practical systems that solve real problems.

I recently joined DEV to start documenting my work, sharing my learning process, and connecting with developers, researchers, and builders who are working on meaningful technical projects.

Over the past few years, I have worked on projects across machine learning, research, cross-platform app development, and systems engineering. Some of my major works include SAR to RGB image translation, bird sound classification, CogniPlan, and MeshOS / AetherLink.

1. SAR to RGB Image Translation using Diffusion Models

One of my major research projects is focused on SAR to RGB image translation.

SAR stands for Synthetic Aperture Radar. Unlike normal optical images, SAR images are captured using radar signals. This makes them useful in cloudy weather, low light, and difficult atmospheric conditions. However, SAR images are harder to visually interpret compared to normal RGB images.

The goal of this project is to translate SAR imagery into RGB-like optical images using a transformer-enhanced conditional diffusion model.

This project involves:

  • Remote sensing
  • SAR image understanding
  • Conditional diffusion models
  • Transformer-based feature learning
  • Image-to-image translation
  • Deep learning-based reconstruction
  • Evaluation using PSNR, SSIM, LPIPS, and downstream task utility

This has been one of my most challenging projects because it is not only about generating visually good images. The generated output also needs to preserve useful structure and information from the original SAR data.

I recently presented this work at a Springer conference, which made this project an important part of my research journey.

2. Bird Sound Classification Research

Another research project I worked on is bird sound classification.

The goal of this project was to classify bird species using audio data and machine learning techniques. It helped me understand the complete ML workflow more deeply, from preprocessing to feature extraction, model training, evaluation, and result analysis.

This project gave me practical experience with:

  • Audio signal processing
  • Feature extraction
  • Machine learning classification
  • Dataset preparation
  • Model evaluation
  • Research paper writing

The research paper for this project has been published, and it helped me build confidence in turning a technical idea into a complete research contribution.

3. CogniPlan — Cognitive Task Planning System

Apart from research, I also enjoy building real software products.

One of my important software projects is CogniPlan, a cognitive task planning system built to help users convert goals into structured execution plans.

Most task management apps only store tasks. CogniPlan is designed to go deeper.

It focuses on:

  • Goals
  • Milestones
  • Tasks
  • Routines
  • Focus sessions
  • Adaptive scheduling
  • Missed-task recovery
  • Productivity insights
  • Local-first storage

The project is built using Flutter, with a focus on cross-platform support and offline-first usage.

The core idea behind CogniPlan is simple:

A planning system should not just remind you what to do. It should help you execute better.

This project helped me improve my understanding of product thinking, app architecture, local-first design, and user-centered workflow systems.

4. MeshOS / AetherLink — Personal Digital Mesh and Remote Control System

I am also working on MeshOS, a local-first personal digital mesh project.

The goal is to create a system that connects a user’s laptop, phone, files, clipboard, apps, automations, and remote-control workflows into one private command layer.

A part of this work also involves AetherLink, a remote desktop and device control system.

This project explores:

  • Rust-based host applications
  • Flutter-based clients
  • Secure device-to-device communication
  • Remote screen streaming
  • Remote input control
  • File transfer
  • Clipboard sync
  • Cross-device workflows
  • Local-first design

The main idea is to give an individual better control over their own digital environment across devices.

This project is still evolving, but it has already taught me a lot about system design, networking, performance, cross-platform development, and real-time communication.

Why I’m Writing on DEV

I want to use DEV as a place to document my journey honestly.

Not only the final polished results, but also:

  • what I am building
  • why I am building it
  • what problems I face
  • what technical decisions I make
  • what mistakes I learn from
  • how research ideas become real working systems

I believe that sharing the process is just as important as sharing the final project.

My current focus areas are:

  • AI/ML engineering
  • Deep learning research
  • Remote sensing
  • Flutter app development
  • Rust systems programming
  • Local-first software
  • Cross-platform product development
  • Building useful tools for real users

What I’ll Be Sharing Next

In upcoming posts, I plan to write about:

  • How I built CogniPlan
  • Why I am building MeshOS
  • My SAR to RGB diffusion research journey
  • Lessons from training deep learning models on limited hardware
  • Flutter and local-first app architecture
  • Rust-based remote desktop systems
  • My experience with research paper publication and conference presentation
  • My roadmap as an M.Tech CSE student trying to grow as an AI/ML and software engineer

Connect With Me

I’ll be sharing more updates around AI/ML research, software projects, Flutter, Rust, local-first systems, and my build-in-public journey.

You can find more of my work here:

Final Thoughts

I am still learning, building, improving, and experimenting.

My goal is to become stronger not only at writing code, but also at designing systems, solving real problems, and turning ideas into useful products.

I’m excited to start sharing my journey here and learn from the DEV community.

Thanks for reading.

I’d be happy to connect with anyone interested in AI/ML, research, Flutter, Rust, local-first software, or building real-world developer tools.

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