Pioneers in AI Systems
4/13/20

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.

Face and Facial Expressions
3/30/22
We are creating a new composite biometric that includes the static face appearance features as well as the behavioral expression features that will, in remote authentication applications, verify the humanness, liveness, and the identity of a user in a single interaction.
Historical Documents
3/30/22
We are exploring the development of computational methodologies and applications that will enable user-friendly digital access to literary and historical document images in Sanskrit.
Web Security
11/9/19
We are developing new technologies to beat the spambots by exploiting the difficulty that computers have with recognizing joined-up handwriting. The hope is that switching from text-based verification systems to systems that use computer-generated handwriting will make many web services more secure.
Cancelable Biometrics
3/30/22
Our focus is on Integrating Privacy Preserving Biometric Templates and Efficient Indexing Methods. While people are usually willing to submit their biometric information to government agencies, they are less likely to do so for commercial companies without a guarantee of privacy protection.
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About Us

  • Our Mission
    4/20/20
    The Center for Unified Biometrics and Sensors (CUBS) was established in October 2003 with the mission of advancing the science of biometric technologies for both civilian and homeland security applications by integrating pattern recognition and machine learning algorithms with sensors technology.
  • About the Director
    11/20/19
    Dr. Venu Govindaraju, UB Vice President for Research and Economic Development, is the founding director of the Center for Unified Biometrics and Sensors.
  • Contact Us
    11/20/19
    The Center for Unified Biometrics and Sensors is located in Davis Hall Suite 113 on the University at Buffalo North Campus.
Learn More About Us

What We Do

  • Pioneers in AI Systems
    4/20/20
    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.
  • Multilingual OCR
    3/30/22
    Our objective is to automatically recognize handwritten and mixed-type documents in multiple languages. Our current focus is on pre-processing of documents and development of novel features for handwriting recognition.
  • Historical Documents
    3/30/22
    We are exploring the development of computational methodologies and applications that will enable user-friendly digital access to literary and historical document images in Sanskrit.
  • Tablet and PDA Interfaces
    11/9/19
    We are investigating a new kind of scientific information interface which involves the use of a touch screen device such as a tablet, supporting sketching and handwriting input to access, annotate, store and retrieve research material. Personal research materials can therefore be organized and shared selectively in a reliable social networking environment by academic researchers.
  • Medical Informatics
    11/9/19
    Emergency Medical Systems (EMS) agencies, as first responders in medical emergency scenarios, are uniquely positioned to provide valuable data for surveillance and early warning systems.
  • Web Security
    11/9/19
    We are developing new technologies to beat the spambots by exploiting the difficulty that computers have with recognizing joined-up handwriting. The hope is that switching from text-based verification systems to systems that use computer-generated handwriting will make many web services more secure.
  • Face and Facial Expressions
    3/30/22
    We are creating a new composite biometric that includes the static face appearance features as well as the behavioral expression features that will, in remote authentication applications, verify the humanness, liveness, and the identity of a user in a single interaction.
  • Cancelable Biometrics
    3/30/22
    Our focus is on Integrating Privacy Preserving Biometric Templates and Efficient Indexing Methods. While people are usually willing to submit their biometric information to government agencies, they are less likely to do so for commercial companies without a guarantee of privacy protection.
Learn More About What We Do

Meet Our Members

Meet More Members

Research Highlights

  • Best Paper Awards
    11/20/19

    Fei Xu and Bhargava Urala Kota, both PhD students in the Department of Computer Science and Engineering and part of UB’s Center for Unified Biometrics and Sensors (CUBS), received Best Paper Awards at the 15th International Conference on Document Analysis and Recognition (ICDAR).

  • a stone pillar at Baird point.
    Mentoring Award
    11/9/19

    Dr. Govindaraju is the recipient of UB's “Excellence in Graduate Student Mentoring Award.” The award is given to a member of the UB Graduate Faculty for "truly outstanding and sustained support and development of graduate students from course completion through research and subsequent career placement."

  • Niagara Falls USA.
    IPIAM 2019
    11/9/19

    CUBS is hosting the 8th International Program on Cyber Security for Banks and Financial Sector in Niagara Falls, NY.

  • Publication at BTAS
    11/6/19

    Congratulations to Devansh Arpit, Chetan Ramaiah, and Venu Govindaraju for their publication  "Subspace Learning via Low Rank Projections for Dimensionality Reduction" at the 8th IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS 2016).

  • AI for Social Good
    11/6/19

    Govindaraju postal research highlighted in Keynote by Eric Horvitz at the Computing Community Consortium workshop on AI for Social Good. >> Watch on Youtube

  • human eye with biometric measurements.
    Publication at CVPR
    11/9/19

    Congratulations to Rohit Pandey and Venu Govindaraju for their publication "Deep Secure Encoding for Face Template Protection" at the 2016 CVPR Biometrics Workshop.

  • human brain with machine learning.
    Publications at ICML
    11/9/19

    Congratulations to Devansh Arpit, Yingbo Zhou, Bhargava U. Kota, Hung Ngo, and Venu Govindaraju for their publications in the 33rd International Conference on Machine Learning titled "Why Regularized Auto-Encoders learn Sparse Representation?" and "Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks"

  • code on a computer monitor.
    Publication at DAS Workshop
    11/9/19

    Congratulations to Rathin R. Nair, Nishant Sankaran, Ifeoma Nwogu, and Venu Govindaraju for their publication "Understanding Line Plots Using Bayesian Network" at the 12th IAPR International Workshop on Document Analysis Systems.

See More Research Highlights