AIM is accelerating knowledge discovery from high-volume data streams by inventing new techniques to help automate the process of creating and validating hypotheses.
In a world where data are continually streaming from distributed and diverse sources—from scientific instruments, to web traffic, to live imagery—making timely discoveries requires computing capabilities that can keep pace with rapidly evolving phenomena. AIM is developing a new analysis paradigm to provide continuous, automated synthesis of new knowledge and to enable measurement systems to be steered in response to emerging knowledge, rebalancing the effort between humans and machines.
Improving How Humans and Machines Interact
We are transforming the feedback loop in joint human and machine reasoning by capturing human background knowledge through new interaction techniques, allowing AIM systems to evaluate candidate hypotheses rapidly and steer models and data collectors in response to evolving knowledge.
Automating Hypothesis Generation and Testing
We are creating automated methods for generating human-useful hypotheses from data, including incremental machine learning from incomplete data and streaming deductive inference to identify and preserve interesting assertions from live data.
Creating New Streaming Analysis Algorithms
We are developing streaming data characterization methods that can identify and tag important features in high rate data streams and exploring the possibility that streaming algorithms can use dynamic sampling strategies to apply more powerful algorithms to increasingly challenging data rates.
February 12–13, 2015.Kerstin Kleese van Dam has been invited to give a keynote speech at the Data Science Innovation Summit, in San Diego, CA. She will be presenting on "How to use Streaming Data for Real Time Discovery and Decision Taking." Visit the website for more information. January 23, 2015.Kerstin Kleese van Dam will be attending the Big Data Strategic Initiative Workshop organized by the Network and Information Technology Research and Development Program's (NITRD) Big Data Senior Steering Group. The NITRD Program provides a framework in which many Federal agencies come together to coordinate their networking and information technology research and development efforts. The goal of this workshop is to bring together a small number of academics and industry partners who provide their expertise, perspective, and vision to help guide this important effort. Learn more...
- The American Association for the Advancement of Science (AAAS), Federal Bureau of Investigation (FBI), and United Nations Interregional Crime and Justice Research Institute (UNICRI) recently completed a year-long study of the benefits and risks of big data, and the related national security implications. Mark Greaves served on the study's panel of experts and was an editor for the report National and Transnational Security Implications of Big Data in the Life Sciences. Read the full article.
November 16, 2014.Kerstin Kleese van Dam was an invited speaker at the 5th International Workshop on Big Data Analytics: Challenges, and Opportunities (BDAC-14), to be held in cooperation with 26th IEEE/ACM International Conference for High Performance Computing, Networking, Storage, and Analysis (SC14) in New Orleans, LA.
Employment and Collaboration Opportunities
Want to join us? We're hiring! We're looking for more world-class machine learning and human-computer interaction researchers to join our team. Contact us; tell us what you're passionate about and discuss the possibilities.
We're also interested in partnering with individuals and organizations. If you have expertise in the areas of machine learning or human-computer interaction, and are interested in partnership opportunities, then we'd like to talk with you. Let's collaborate.