Hello World: Welcome to Sillycon AI Lab

By Sillycon AI Lab

SillyCon AI Lab

Most AI communities talk about ideas. Some build projects. Very few stay long enough to turn those projects into meaningful research.

Sillycon AI Lab exists to do the third.

We are a student-led research lab focused on Artificial Intelligence, Machine Learning, and Deep Learning, with a strong emphasis on solving real-world problems through structured experimentation, not just prototypes.

What We Work On

Our work primarily sits in the space of Computer Vision and Image Restoration, where performance is measurable and competition is global.

We actively participate in challenges and research tracks such as:

• CVPR workshops and associated challenges
• NTIRE benchmarks in image restoration and enhancement

From super-resolution to spectral reconstruction, our focus is simple:

build models that don’t just run — but perform under evaluation.

How We Work

We don’t treat this lab as a casual coding group.

Our workflow typically involves:

• Reading and breaking down recent papers
• Reproducing baselines (properly, not approximately)
• Iterating on architecture and training strategies
• Evaluating results with discipline

A large part of our work is not glamorous: debugging instability, fixing training pipelines, and questioning assumptions.

That’s where most of the learning actually happens.

The Team

The Lab Captains

• Ankit Kumar
• Aagam Jain
• Milan Kumar Singh

The Senior Brains

Venkata Sai, Nikhil Pathak, Hammad, Jenny Bhat, Dimple Sonone, Abhishek Rajak, Hariom Thacker, Vivek, Sarang, Aanchal Maurya, Urja

The New Bloods

Currently onboarding the next batch.

What You’ll Find Here

This publication will serve as our open research log.

We’ll be sharing:

• Competition breakdowns and approaches
• Architecture insights and experimental learnings
• Failures, not just results
• Practical interpretations of research papers

If something works, we’ll explain why. If it doesn’t, we’ll explain that too.

Closing Note

This is not a highlight page. It’s a record of work in progress.

If you’re interested in applied AI research, you’ll probably find something useful here.

— Sillycon AI Lab