Istvan Racz (eu-LISA, France)The Entry-Exit-System - Opportunities and Challenges
The new European Entry-Exit System (EES) is planned to enter into operations in 2022, aiming at further strengthening the internal security of Europe and the Schengen Zone through centralized registration of the entries and exits of third country travellers. EES, by exposing common operations and workflows to its end-users, will connect hundreds of border crossing points into an information exchange network, ensuring high level of verification and identification accuracy through the use of a combination of alphanumeric and live biometric data.
The keynote talk will elaborate on the main principles along which EES, a unique large scale IT system has been built, highlighting the main stumbling blocks as well as identified opportunities during the design and implementation phases. The scope of the presentation will also include the shared Biometric Matching Service connected to EES and the other existing and future eu-LISA core business systems to process biometric identity data.
Istvan Racz is a Senior Information Technology Officer at eu-LISA. After graduating as computer scientist and mathematician, and a master degree in artificial intelligence, he worked for multinational companies in the domain of robotics and data warehouse analytics, playing roles from software architecture up to IT management.
After 10 years’ of active career in the private domain, he joined the European Commission as Project Manager in 2009, taking the role of Head of Sector and responsibility for the European Commission’s central Asset Management System portfolio later. In 2012, at the start of the new European regulatory agency called eu-LISA, he decided to be part of this challenge, joining the initial team which laid down the foundations of the Agency. As a PMP and Prince2 certified project manager, he delivered a large number of IT projects mainly related to biometrics and the Visa Information System, before taking the role of Product Owner for the Shared Biometric Matching Service.
Richa Singh (IIT Jodhpur, India)On Building Dependable Biometric Systems
Biometric systems utilizing modern machine learning and computer vision algorithms have demonstrated superlative performances in various applications and have been utilized in real world scenarios. Despite the enhanced performance, robustness of these algorithms against attacks, explainability, trustability, and fairness/bias are major concerns.
This talk will give an overview of "dependable" aspects of building biometric systems. We will take face recognition as a case study and discuss different types of attacks such as physical attacks, digital adversarial attacks, and morphing/tampering using GANs. We will also discuss the effect of bias on face recognition models and showcase that factors such as age and gender variations affect the performance of modern algorithms. Finally, we will also discuss the explainability models for understanding modern biometric algorithms.
Richa Singh received the M.S. and Ph.D. degree in computer science from West Virginia University, Morgantown, USA. She is currently a Professor at IIT Jodhpur, India, the Vice President (Publications) of the IEEE Biometrics Council, and an Associate Editor-in-Chief of Pattern Recognition.
Her areas of interest are pattern recognition, machine learning, and biometrics. She is a Fellow of IEEE and IAPR. She was a recipient of the Kusum and Mohandas Pai Faculty Research Fellowship at the IIIT-Delhi, the FAST Award by the Department of Science and Technology, India, and several best paper and best poster awards in international conferences. She is/was the Program Co-Chair of ICMI2022, IJCB2020, FG2019 and BTAS 2016, and a General Co-Chair of FG2021 and ISBA 2017.
Brendan Klare (Rank One Computing, U.S.)How a Global Pandemic Altered the Trajectory of Automated Face Recognition Technologies
The COVID-19 pandemic has changed the lives of nearly everyone on the planet. As it relates to automated face recognition, the most direct consequence has been the near ubiquitous facial masks in public spaces and the need for contactless systems. At the same time, several indirect consequences have emerged including a shift from brick-and-mortar businesses to digital services, massive-scale peaceful protests to highlight social injustices, and violent riots across the globe. This talk will highlight how face recognition technologies have played a role in all of these consequences, and focus on areas of improvement needed from academic research in the years ahead.
Brendan is the co-founder, President, and Chief Scientist of Rank One Computing, a leading provider of facial recognition algorithms to the U.S. Government, state and local law enforcement agencies, the financial sector, and a wide range of embedded applications and enterprise systems. Rank One is employee-owned and located in Denver, Colorado, U.S.A. Brendan previously was the CEO of Rank One from 2015 to 2021.
Brendan received his Ph.D. in Computer Science from Michigan State University. He has published dozens of articles on the topic of automated face recognition and pattern recognition algorithms. His publications have an h-index score of 25, though he has not been active in research publications for several years.
Prior to his academic studies Brendan served as an infantryman in the 75th Ranger Regiment, U.S. Army. Prior to founding Rank One, Brendan served as a subject matter expert consultant on the use of automatic face recognition algorithms for the U.S. Dept. of State, the Federal Bureau of Investigations, the Dept. of Defense, and the Intelligence Advanced Research Projects Activity (IARPA)