AI, automation, and the future of work: Ten things to solve for
Artificial Intelligence
Artificial Intelligence (AI) research explores the nature of intelligence and the ways in which computation can be used to explain and engineer it. Work in AI combines the scale afforded by machine learning with the expressive and organizational power of semantic information-processing and knowledge-based reasoning. Our faculty research programs include work in machine learning, cognitive modeling, language understanding and generation, planning and reasoning, robotics and human-robot interaction, computational journalism, social media analysis, computer audition, computers and education, computational creativity, and legal reasoning.
Brenna ArgallAssociate Professor of Computer Science
Associate Professor of Mechanical Engineering
Associate Professor of Physical Medicine and Rehabilitation
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Chris RiesbeckAssociate Professor of Computer Science
Director, Master of Science in Computer Science Program
Co-Director, Center for Computer Science and Learning Sciences
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Artificial Intelligence And Machine Learning
Self-driving cars, intelligent assistants, and smart-home devices—we work to improve and discover AI technology in the fields of energy, finance, health care, education, transportation and more. We develop interactive decision-making tools, and create algorithms to respond to interdisciplinary fields where uncertainty is present: from construction management to the Mars rover. We investigate complex issues surrounding student persistence, and dig deep into machine learning.
"Students take a construction plan and overlay it with events that cause delays. Then we ask students to react to the scenarios."Nilufer Onder, associate professor, computer science, on developing ICDMA (interactive construction decision-making aid)
Current ProjectProject Title: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity
Investigators: Laura Brown
Sponsors: National Science Foundation
Overview: This CRISP (Computer Retrieval of Information on Scientific Projects) project addresses the challenges associated with the rapid evolution of the electricity grid to a highly distributed infrastructure. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels for delivering electricity to customers, to distribution microgrids, entities that actively manage local production, storage and use of electricity, with participation from individual customers. Distribution microgrids combine the advantages of the traditional electricity grid with the advantages of emerging distributed technologies, including the ability to produce and use power locally in the event of grid outages. The project will result in a unified model that incorporates key aspects of power generation and delivery, information flow, market design and human behavior. The model predictions can be used by policymakers to guide a transition to clean energy via distribution microgrids. The expectation is to enable at least 50% of electric power to come from renewable resources. This cannot be done with either the traditional grid, due to its limited capacity to accommodate intermittent renewable power sources, or with fully decentralized approaches, which would not be affordable for most utility customers.
ResearchersExplore Computer Science Research Research Groups What's New
MEng Computer Science With Artificial Intelligence
MEng Computer Science with Artificial Intelligence combines a focus on the rapidly evolving field of Artificial Intelligence (AI) with a thorough grounding in the fundamentals of computer science, including opportunities to specialise in a range of advanced areas of AI and computer science while gaining skills in system development and enterprise. We review our curriculum constantly to ensure it remains at the leading edge.
Core ideas are introduced in years one and two. You will learn the principles of algorithms and programming, covering three key paradigms: imperative, functional and object-oriented. You will also study the core concepts, tools and methods of artificial intelligence; the mathematics and statistics underpinning modern computer science and artificial intelligence; how a modern computer architecture is organised; and the foundations of human-computer interaction, cybersecurity and theoretical and data-driven computer science.
A key component of year two is the AI software team project in which you work with others to develop an AI application for a real-world client with help from an industrial mentor.
In your final two years, you will choose from a range of optional units in order to specialise in selected advanced areas of computer science and AI. You will undertake another significant team project, focused on the use of AI in immersive entertainment. You will also conduct an individual AI project with a focus on Artificial Intelligence topics such as machine vision, intelligent agents, logic, and machine learning, co-created with a supervising member of staff, with opportunities to work with industrial or research partners.
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