Nick Landia

Chief Data Scientist

Nick has been working on recommender systems for fashion for over 8 years. His main focus is leading the development and application of algorithms. Over the years he has gained a lot of real-world experience rolling out customer-facing ML products at Dressipi and has developed a keen interest in bringing the worlds of product and research closer together.
Nick is running the 2022 RecSys challenge which is focusing on fashion recommendations. He loves being at the intersection of research and industry, taking new algorithms from the research phase all the way through to customer-facing technology.
Previously, Nick completed a PhD in Computer Science at the University of Warwick and has co-founded two startups.

Building Fashion Recommendation Systems for Ecommerce

22 March 2022

Nick Landia, Dressipi’s Chief Data Scientist, explores the challenges of building intelligent and effective personalized recommendation systems. The goal? To create truly personalized customer experiences.

Dressipi Collaborates with ACM Recommender Systems (RecSys)

10 March 2022

RecSys is the premier international forum for the presentation of new research results, systems and techniques in the field of product recommendation systems.

Nick Landia

Chief Data Scientist

Building Fashion Recommendation Systems for Ecommerce

Nick Landia, Dressipi’s Chief Data Scientist, explores the challenges of building intelligent and effective personalized recommendation systems. The goal? To create truly personalized customer experiences.

Dressipi Collaborates with ACM Recommender Systems (RecSys)

RecSys is the premier international forum for the presentation of new research results, systems and techniques in the field of product recommendation systems.

Why is Fashion Different? Part 2: Fashion Consumer Behavior

Fashion Consumer Behavior

Why is Fashion Different? Part 1: Quantifying Fashion Data

Quantifying Fashion Data