Skip to main content

February 2027

CFP closes 21 Jan

World Conference on Advanced Machine Learning and Data Science

WCAMLDS 2027

World Conference on Advanced Machine Learning and Data Science is a 2-day event in Toronto, Canada on 22–23 February 2027, organized by IRAJ International. Abstracts are due by 21 January 2027. IRAJ International has 188 other upcoming conferences listed here.

Call for papers open

Important dates

  1. Abstract / full paper deadline

    In 67 days

  2. Conference

    Toronto, Ontario, Canada

All deadlines are as published by the organizer. Check the official website for the time zone.

About this conference

An international platform dedicated to the exploration of advanced methodologies in machine learning and data science, this conference welcomes submissions from various sectors including academia, industry, and government. Key thematic areas encompass model interpretability, scaling machine learning systems, and applications in diverse fields such as healthcare and finance. Participants can look forward to engaging sessions that include expert keynotes, peer-reviewed presentations, and interactive workshops. The event encourages collaboration and discussions on practical implications and future research directions. Please refer to the conference's official website for information on submission guidelines and registration processes.

Call for papers

Abstracts are due by 21 January 2027. Submission details are on the official website.

Where this information comes from

Source
Submitted by the organizer
Listed on
2 November 2026
Verification
Reviewed by an editor before publishing
Reference
FCA2923191

Questions about WCAMLDS 2027

When and where is WCAMLDS 2027?

22–23 February 2027 in Toronto, Ontario, Canada.

Can I attend online?

This listing does not confirm an online option. Check the official website.

What is the submission deadline?

Abstracts are due by 21 January 2027.

How do I register?

Registration and fees are handled by the organizer on the official website.

Visit Website