Marios Savvides is the founder and director of the Biometrics Center at Carnegie Mellon University and is a research professor in the Department of Electrical & Computer Engineering Department and the CyLab Security and Privacy Institute. He received his B.Eng. in Microelectronics Systems Engineering from UMIST, U.K., his Masters of Science in Robotics from the Robotics Institute at Carnegie Mellon University, and his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University.

Savvides was also one of the researchers chosen to form the Office of the Director of National Intelligence’s (ODNI) 1st Center of Academic Excellence in Science and Technology (CASIS). His research is mainly focused on developing algorithms for robust face and iris biometrics as well as pattern recognition, machine vision, and computer image understanding for enhancing biometric systems performance. He is on the program committee on several Biometric conferences such as IEEE BTAS, ICPR, SPIE Biometric Identification, IEEE AutoID and others as well as organizing and co-chairing Robust Biometrics Understanding the Science & Technology (ROBUST 2008) conference. He was an annual invited speaker at IDGA's main conference on Biometrics for National Security and Defense.

Savvides has authored and co-authored over 170 journal and conference publications, including several book chapters in the area of Biometrics and served as the area editor of Springer’s Encyclopedia of Biometrics. He helped co-develop the IEEE Certified Biometrics Professional (CBP) program and was on the main steering committee of the IEEE CBP program. His achievements include leading the R&D in Carnegie Mellon’s past participation at NIST’s Open Face Recognition Grand Challenge 2005 (CMU ranked #1 in Academia and Industry at hardest experiment #4) and also in NIST’s Iris Challenge Evaluation (CMU ranked #1 in Academia and #2 against iris vendors)—his group was the only one to attempt both challenges.

Savvides is listed in Marqui’ Who’s Who in America and in Marquis’ Who’s Who in Science & Engineering. He has filed over 20 patent applications in the area of Biometrics and is the co-recipient of Carnegie Mellon’s 2009 Carnegie Institute of Technology (CIT) Outstanding Research Award.

B209 Hamerschlag Hall
Google Scholar
Marios Savvides
CyLab Biometrics Center

Demonstration: Long-Range Iris Recognition System


2005 Ph.D., Electrical and Computer Engineering, Carnegie Mellon University

2000 MS, Robotics, Carnegie Mellon University

1997 Bachelor of Engineering, Microelectronics Systems Engineering, University of Manchester Institute of Science and Technology


Media mentions

Popular Science

Savvides quoted on facial recognition

CyLab/ECE’s Marios Savvides was quoted in Popular Science on the caveats of facial recognition technology.


Savvides mentioned on facial recognition

ECE/CyLab’s Marios Savvides was mentioned in CNN on facial recognition’s struggle with identifying faces wearing masks.

The New York Times

Bossa Nova featured in New York Times on robots and retail

A New York Times article exploring the growing role of robots in retail discussed the work Bossa Nova and Carnegie Mellon researchers have conducted with Walmart to design a shelf-scanning robot that they hope both employees and customers will feel comfortable with.

CMU Engineering

Using AI to recycle bottles

A collaborative project in partnership with CMKL University aims to develop an artificial intelligence (AI) system to accurately screen bottles for reuse and recycling.


Bossa Nova improves robots using HawXeye tech

Walmart has expanded its use of CMU startup Bossa Nova’s shelf-stocking robots from 50 to 350 stores nationwide.


Savvides comments on improvements in facial recognition AI

CyLab/ECE’s Marios Savvides recently commented for a piece on the growing prevalence of AI powered facial recognition software.


Savvides on AI and facial recognition

CyLab/ECE’s Marios Savvides spoke with CNET in an article about how AI has helped to drastically improve facial recognition. It is now being used more widely, at airports, in home security systems, and on cruises, with a 99.7 percent accuracy for the most cutting-edge systems. “We live in a time where AI can surpass the human brain’s capability,” he says.

Twin Cities Pioneer Press

Savvides on the future of airport security

CyLab’s Marios Savvides was interviewed by the Twin Cities Pioneer Press about the future of airport security and the role advancing technology will play. “With a facial-recognition system, there would be no need for a TSA agent to check your ID,” Savvides said. “The system captures an individual’s iris and full face as they walk by."

Pittsburgh Post-Gazette

Savvides recognized at Immigrant Entrepreneur Celebration

CyLab/ECE’s Marios Savvides was one of eight people recognized at GlobalPittsburgh’s 3rd Annual Immigrant Entrepreneur Celebration and Award Ceremony. Savvides, who hails from Cyprus, won the Technological Innovation category for his work as the founder and director of the CyLab Biometrics Center.

The New York Times

CyLab researchers quoted in NYT

CyLab's Marios Savvides, Lujo Bauer, Jason Hong, Kathleen Carley, Martin Carlisle, and Carolina Zarate were featured in a New York Times piece about various ongoing research thrusts in CyLab to help combat cyberattacks. “More than 300 researchers and graduate students are working or studying at CyLab this year, making it among the largest cybersecurity training centers in the world,” the article says.

Popular Science

Savvides comments on biometrics in airports

Popular Science quoted CyLab/ECE’s Marios Savvides in an article on incorporating facial recognition in airports to streamline security. Savvides says there is a negative stigma against biometrics but approves their use because they were always meant to be a streamlining tool.

Savvides voices support for TSA biometrics

The TSA announced a plan to increase its use of biometrics, such as facial recognition, to streamline the airport security process. ECE/CyLab’s Marios Savvides voiced his support, stating that automated facial recognition is similar to human judgement and the public is prepared for its implementation.