Machine Learning Department - Carnegie Mellon University

The Verge Interviews Manuela Veloso

Manuela Veloso, Machine Learning Department Head, is one of ten influential leaders in technology and culture featured on The Verge. The Verge, a technology and culture ... Read More ยป

What is Machine Learning (ML)?

A Message from ML Department Head - Manuela Veloso

Manuela VelosoMachine Learning (ML) is a fascinating field of artificial intelligence (AI) research and practice where we investigate how computer agents can improve their perception, cognition, and action with experience. Machine Learning is about machines improving from data, knowledge, experience, and interaction. 

Machine learning techniques to intelligently handle large and complex amounts of information build upon foundations in many disciplines, including statistics, knowledge representation, planning and control, databases, causal inference, computer systems, machine vision, and natural language processing.

AI agents with their core ML aim at interacting with humans in a variety of ways, including providing estimates on phenomena, making recommendations for decisions, and being instructed and corrected.

In our Machine Learning Department, we study and research the theoretical foundations of the field of machine learning, as well as on the contributions to the general intelligence goal of the field of artificial intelligence. In addition to their theoretical education, all our students, advised by faculty, get hands-on experience with complex real datasets.

Machine Learning can impact many applications relying on all sorts of data, basically any data that is recorded in computers, such as health data, scientific data, financial data, location data, weather data, energy data, etc. As our society increasingly relies on digital data, machine learning is crucial for most of our current and future applications.

NOW HIRING

The Machine Learning Department currently seeks qualified applicants for the following positions:

  • Tenure Track Faculty
  • Teaching Track Faculty

Visit the Faculty Hiring page for more information and to apply.