REU Site: Frontier Technologies in Biometrics and Authentication

REU Site Description:

Driving the need of stronger seucrity, biometrics (e.g., face and fingerprint) is replacing traditional passwords and becomes the most preferred authentication approach in daily-life scenarios, including mobile applications, banking, and border security. The trend has led to an impressive upsurge in the industry's need to hire scientists and engineers with biometric computing skills. To harness the biometric technology and meet the increasing industry demand, biometrics and authentication have become a core part of the cybersecurity course curriculum.

Participants in this REU site will work at the north campus location of the University at Buffalo. REU undergraduate students across the nation will work with a group of experienced faculty members and industrial mentors, and conduct cutting-edge research in biometrics and authentication during the 10-week program. This REU site will provide a short-term intensive research training experience to a group of undergraduate researchers, prepare them for the research experience in the field of cybersecurity, and benefit their graduate applications and job opportunities. Particularly, REU site also allows students to dive into and learn sought-after skills in data processing, app/software development or machine learning. Through various activities such as hands-on projects, seminars, demos, presentations, field trips, and other professional development opportunities, undergraduate students will also enhance their professional skills. This REU site aims to broaden the participation of underrepresented students from institutions that offer limited or no research opportunities in Biometrics and Authentication.

REU participants will gain the quality training in technologies and career development, have opportunities to publish/present your research work in academic venues (e.g., journals or conference), and have at least $5,000 in stipends (including meal expense). The REU site will also provide 1) the lake-view on-campus housing, 2) relocation compensation and 3) trips to local sites and industry parks for the on-site REU participants. (Due to the COVID-19, REU 2022 will be organized in a hybrid mode, i.e., in-person and remotely.)


  • This REU site is supported by the U.S. National Science Foundation Research Experiences for Undergraduates Site Program under Grant # CNS-2050910.
  • Eligibility and Applications:

  • 1) U.S. Citizen or Permanent Resident
  • 2) Basic Programming Skills (e.g., Matlab, C/C++/C#, Python or Java)
  • 3) Preferred GPA: 3.0+
  • 4) Major field of study in all engineering and science related disciplines. Exception can be made for good candidates.
  • Application Document List: (Note: a, b and c will be uploaded through the application link below)

  • a) Resume (up to 2-page limit)
  • b) The Copy of College/University Transcripts
  • c) Personal Statement (up to 2-page limit)
  • d) [optional but highly recommended] One letter of recommendation by authority (e.g., the recommender will email the letter to Dr. Wenyao Xu and Dr. Zhanpeng Jin
  • Important Dates and Deadlines:

  • Application Deadline: March 15, 2022 -> Apply Now!
  • Acceptance Notification: April 1, 2022
  • REU Participants Arrive on Campus: May 30, 2022
  • REU Program Date: May 30, 2022 - August 5, 2022 (10 weeks)
  • Contact People:

    Related Publications and Demos:

  • [1]"Cardiac Scan: A Non-Contact and Continuous Authentication System", ACM International Conference on Mobile Computing and Networking (MobiCom'17), Snowbird, Utah, USA, October 2017 [pdf] [Video1] [Video2] [Video3] [Video4]
  • [2]"Brain Password: A Secure and Truly Cancelable Brain Biometrics for Smart Headwear", the 16th ACM International Conference on Mobile Systems, Applications, and Systems (MobiSys'18), Munich, Germany, June 2018 [pdf]

    Prerequisite Lectures & Materials: (Watch them before the REU program starts)

    Categories Lecture Topics Link
    Fingerprint Biometrics Fingerprint basics Link
      Fingerprint features in details Link
    Face Biometrics OpenCV Python: Face Detection Link
      OpenCV Python: Face Recognition and Face Identification Link
      OpenCV Python: Face Landmarks Detection Link
    Micro-Expressions Reading Facial Expressions Link
    Iris Recognition A Great Talk on Iris Recognition Link
    Speaker Identification A student course project review Link
    OpenCV (core) Learn OpenCV in 3 hours with Python Link
    Classification (core) Machine Learning in Python: Classification Link
    MFCC (core) Mel-Frequency Cepstral Coefficients Link