Center for Computational Thinking, Carnegie Mellon

The major activity of the Center for Computational Thinking is the PROBE, short for PROBlem-oriented Exploration. A PROBE develops and applies novel computing concepts in ways that vividly illustrate the value of computational thinking while advancing basic research in computer science. Some PROBEs involve applying new research concepts to nontraditional problems, to show how computational thinking can improve our world. Other PROBEs explore new educational concepts, to teach computational thinking. Often a PROBE involves a collaboration between a computer science researcher and a domain expert.

PROBEs typically run for one year and provide funding for faculty, students, postdoctoral fellows, and travel. Usually they involve a collaborator or point of contact from Microsoft Research. To maximize the pay-off, PROBEs seek broadly-applicable solutions to domain problems rather than specialized solutions or commercializable technologies.

Click on the links below to learn more about the current PROBEs in the Center for Computational Thinking.

Computational Thinking for Optimal Kidney Exchange
Organized by Tuomas Sandholm

What would happen if surgeons and medical clinics used computational thinking in order to make organ transplantation decisions? Is it possible to optimize the allocation of organs so that many more people can be saved? In this PROBE, Tuomas Sandholm, in collaboration with Microsoft Research, will make it possible for the United Network for Organ Sharing to use advanced computing concepts to make the best use of donor organs, potentially savings many thousands of lives each year. Along the way, new advances in fundamental algorithms will be developed.

Designing Resistance-Evading Drugs
Organized by Christopher James Langmead

A key challenge in the treatment of viral and bacterial pathogens is the emergence of drug-resistant mutations. What if we applied computational thinking to this problem? Could advanced algorithms help in the design of new drugs that not only are effective against specific disease agents, but also against any variants that are likely to arise due to drug-induced evolution? In this PROBE, Chris Langmead will explore the use of machine learning techniques to predict likely mutations and thus allow better drugs to be designed.

Computational Thinking for Improved Control Over Privacy

Empowering Lay Users to Control Complex Privacy and Communication Policies
Organized by Norman Sadeh, Lorrie Cranor, and Jason Hong

Privacy Optimizations
organized by Anupam Gupta

Improving Privacy via History Independence
organized by Guy Blelloch and Daniel Golovin

With the abundance of information available to us nowadays, the question of data privacy has become increasingly important. This means that everyone needs to understand privacy in more contexts than ever before. Computational thinking will be essential for coping with these new realities.

In 2007, the Center for Computational Thinking organized a Mindswap on Data Privacy, bringing together researchers from Microsoft and Carnegie Mellon, as well as other academic and industry researchers. The researchers highlighted the idea of privacy as a computational resource, to be optimized by algorithms and data structures, and managed by computational thinking. The outcome of the MindSwap is a set of three PROBEs:

Parallel Thinking
organized by Guy Blelloch

The Performer, an Interactive Music System for Live Performance,
organized by Roger Dannenberg

Understanding and Harnessing Ensemble Behavior
Organized by Seth Copen Goldstein

Symposium

Computational Thinking for Arts and Education
Organized by Golan Levin