a composite image depicting a human eye, fingerprint, and biometric measurements.

CUBS research and development activities in machine learning span two strategic application areas, biometrics and language technologies. The activities range from research on Department of Defense projects and developing prototype devices for the industry, to organizing major technical conferences and training graduate students.

  • Pioneers in AI Systems
    Professor Govindaraju's work in handwriting recognition was at the core of the first handwritten address interpretation system used by the United States Postal Service.
  • Projects
    CUBS projects are funded by industry and government agencies. Federal sponsors include the Army Research Labs, the Central Intelligence Agency, the Defense Intelligence Agency, and the National Science Foundation. Industry sponsors include BBN Raytheon, Google, HP, IBM, and Lockheed Martin.
  • Datasets
    Contactless fingerprint matching using smartphone cameras can alleviate major challenges of traditional fingerprint systems including hygienic acquisition, portability and presentation attacks. However, development of practical and robust contactless fingerprint matching techniques is constrained by the limited availability of large scale real-world datasets. To motivate further advances in contactless fingerprint matching across sensors, we introduce the RidgeBase benchmark dataset.
  • Research Highlights
    Scholarly activities at CUBS include the completion of 39 PhD dissertations, 17 MS theses, 7 patents, 17 books/edited volumes, and over 400 journal, conference, and workshop papers. CUBS alumni are employed at BBN Technologies, Fujitsu Labs, eBay, Google, Siemens Medical Solutions, and Yahoo Research.