Machine Learning Applications CSAIL

Bringing new applications, workforce cohesion and technological vision to industry.

Overview

MIT’s world renowned Computer Science Artificial Intelligence Lab (CSAIL) is launching its newest research initiative, MachineLearningApplications@CSAIL. This initiative will focus on applications of the latest machine learning (ML) technologies, research on the resolution of current challenges limiting the abilities of ML and professional development that will help prepare a company’s workforce for this digital transformation.

Many companies are unsure of how, where, or if they should leverage ML. Awash in data, they are looking to turn that data into intelligence that drives increasingly efficient processes. The valuable insights and impact across all functions from sales, marketing and customer engagement to logistics, cost control, fraud detection, security and more can be transformational.

Organizations who know how to leverage and integrate ML across their business will have a competitive advantage. All industries including retail, food/beverage, travel/tourism, household goods, construction, fashion, agriculture, manufacturing/ packaging, education, pharmaceutical, health care and more will all benefit from the latest ML technologies.

The Challenge

The ability of a machine to learn depends largely on the accuracy of its underlying mathematical model. Developing and maintaining these models is challenging on several fronts. How can machine learning be leveraged for additional insights, but with outcome guarantees or provability? How can organizations analyze more complex data sets? How can the results be trusted? How can training models be updated with new data to keep the ML systems operating most efficiently?

Organizations must have a skilled workforce of people who can build the models, implement the applications, maintain the models and address ongoing privacy/security issues. From the need for new skills sets to rethinking roles and organizational structures due to automation, companies must take a holistic approach to implementing a machine learning strategy.

Our Approach

Our approach is comprehensive and will address the vision for the future of machine learning, its applications in business, research where no commercial products are currently available and skill development for your workforce. Member companies will engage with our world-renowned lab and:

  • participate in future focused innovation sessions with researchers
  • explore machine learning technology development and pathways
  • advise and shape research that addresses the current challenges limiting the abilities of ML
  • have access to a variety of professional development programs designed to increase worker readiness for the adoption of machine learning in their business
  • connect to startups developing and deploying the latest technologies working to jump start machine learning innovation.

This exciting new initiative will help leaders navigate, consume, digest and prepare their company for all machine learning has to offer.

Faculty Director

Daniela Rus
 
  Daniela Rus

Participating Researchers

Hal Abelson
 
  Hal Abelson

Tommi Jaakkola
 
  Tommi Jaakkola

Tamara Broderick 
 
  Tamara Broderick

Boris Katz
 
  Boris Katz
Randall Davis
 
  Randall Davis
John Leonard
 
  John Leonard
Fredo Durand 
 
  Fredo Durand
Ankur Moitra
 
  Ankur Moitra
Manya Ghobadi
 
  Manya Ghobadi
Justin Solomon
 
  Justin Solomon
Polina Golland
 
  Polina Golland
Russell Tedrake
 
  Russell Tedrake