Faculty Co-Director, MIT Future of Data, Trust, and Privacy, Principal Investigator, MIT CSAIL, Professor, MIT CSAIL
MIT CSAIL professor Srini Devadas discusses computer architecture, computer security and their intersection. He gives further insight into the conflict between ease of programming and performance and the communication between these threads through parallel software, such as message passing or shared memory abstraction (e.g. Google Docs).
Professor, MIT EECS, Professor, Mechanical and Ocean Engineering; Associate Department Head for Research, MIT Mechanical Engineering, MIT
While the promise of the Internet of Things (IoT) brings many new business prospects, it also presents significant challenges ranging from technology architectural choices to security concerns. The concept of Internet of Things (IoT), which has roots at MIT, has begun to make an impact in industries ranging from industrial systems to healthcare. MIT researchers continue to conduct ground-breaking research on topics ranging from RFID to cloud technologies, from sensors to the World Wide Web.
A researcher at MIT’s Computer Science and Artificial Intelligence Lab, Stonebraker has founded and led nine different big-data spin-offs, including VoltDB, Tamr and Vertica - the latter of which was bought by Hewlett Packard for $340 million.
Principal Research Scientist, MIT Laboratory for Information and Decision Systems (LIDS)
The Data Science Machine is an end-to-end software system that is able to automatically develop predictive models from relational data. The Machine was created by Max Kanter and Kalyan Verramachaneni at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. The system automates two of the most human-intensive components of a data science endeavor: feature engineering, and selection and tuning of the machine learning methods that build predictive models from those features. First, an algorithm called Deep Feature Synthesis automatically engineers features.
