Cognitive Solutions & Foundations at IBM Research - Almaden - Strategy Areas
For more than three decades, IBM Research has produced major contributions to the area of data management. This includes E. F. Codd's seminal work on relational algebra; the System R relational database management system prototype, which led to IBM's DB2's ARIES transaction recovery and logging; Starburst extensible database technology, and DB2 parallel database technology.
The Information Management (IM) group is proud to carry on IBM's rich tradition of excellence with groundbreaking research in data management technology. We utilize our expertise in XML, machine learning, text analysis, artificial intelligence, and application-enabling middleware to tackle the challenges posed by the proliferation of unstructured and semi-structured data in business applications, the life sciences, and personal information management.
Infrastructure for Intelligent Information Systems
Databases must do more than simply store and process the increasing amount of data in our world. They must also effectively organize and streamline the data to best aid users.
The Infrastructure for Intelligent Information Systems (IIIS) group is at the forefront of research into data analytics, search technologies, and integration. Our research ranges from generating innovative information extraction techniques to analyzing data translation to optimizing schema mapping, with the ultimate goal of developing next-generation, responsive information systems. Throughout all of our work, emphasis is placed on adaptability, usability, and scalability.
Principles and Methodologies
The Principles and Methodologies Group (also known as the Theory Group) explores foundational issues that confront the computing industry today. Because theory cuts across every aspect of computer science, we tend to interact with a large number of other research teams.
Thanks to considerable advances in technology, there are significant, rapidly growing sources of information from the biological and physical systems that orchestrate our world. Among these sources are genetic sequence data and data from sensors/devices each of which enable more sophisticated monitoring of ourselves, our environment and our industrial enterprises. The exercise of interpreting and extracting knowledge from these sources has crossed over into the era of ‘big data’. There is great room for innovation in computational systems that can bring the intelligence of the physical world to decision makers charged with solving the most challenging problems in their respective industries.
At the intersection of the Industries & Solutions and Cognitive Computing strategies, our team is amassing core data science skills and researching computational system architectures, data analysis techniques and cryptographic security methods for these emerging information sources.
Despite the rapid advances in medical science, the healthcare delivery system remains plagued with inefficiencies that hinder basic access to quality care at a reasonable price. Soaring costs are placing severe strains on an already overburdened system, and administrators are scrambling to organize an ever-increasing stream of information from a variety of data sources. There is a growing consensus that Information Technology (IT) provides the key to cost-effective quality care for all.
Our research in healthcare informatics applies core computer science and mathematics to complex healthcare domain problems. We look to solve some of healthcare’s greatest IT challenges with new technology and methods that often translate to other industries. Our technologies and inventions focus on the advancement of multi-modal analysis, complex information integration technology, disease and event modeling and genomics.
Our achievements include co-developing one of the first US Nationwide Health Information Network (NHIN) prototypes, authorship, editorship of and software tooling for key healthcare data integration standards and specifications, technological advances in medical image analysis and open source platforms for disease modeling and healthcare information exchange.
Our teams are: Information Integration, Multimodal Mining and Public Health.
User Systems and Experience Research (USER)
The User Systems and Experience Research (USER) Group at IBM Research - Almaden focuses on understanding and improving how people interact with technology and with each other through technology. We analyze existing practices, build novel, interactive technologies and systems, and study their impact on real users, often in the field. Our cross-disciplinary team is comprised of researchers and software engineers with backgrounds in computer science, psychology, social science, design, and user experience. We are a part of the Human Computer Interaction Research community at IBM.