BBVA Foundation Honors Pioneers in Biometrics and AI

The BBVA Foundation has awarded its Frontiers of Knowledge Award in Information and Communication Technologies to two pioneering researchers who have made fundamental contributions to machine learning, biometrics, and artificial intelligence: Anil K. Jain of Michigan State University and Michael I. Jordan of the University of California, Berkeley.

Jain’s research has significantly advanced pattern recognition and biometric technologies, particularly in fingerprint and face identification systems. His work began at Ohio State University with automated aircraft recognition systems before expanding into medical imaging and postal address recognition. At Michigan State University, where his lab continues to receive major research funding, he later conducted groundbreaking research that quantified fingerprint uniqueness and stability. Using data from 40,000 repeat offenders over 12 years, Jain demonstrated that fingerprints remain consistent over time – research that has become foundational for modern biometric identification systems.

The award committee praised Jain’s “monumental contributions” to biometric recognition, noting that his work has left “an indelible stamp on the fabric of today’s – and tomorrow’s – information-rich society.” His technologies are now widely implemented in criminal investigations and consumer electronics security systems, with law enforcement agencies across Europe and North America increasingly adopting facial recognition and fingerprint matching systems based on his research principles.

Michael I. Jordan developed mathematical and computational techniques that form the foundation of many current AI applications. In the 1990s, he pioneered variational inference methods that enable optimization solutions for complex mathematical problems, which are now essential to deep learning systems. His work in the 2000s on distributed computing algorithms led to the creation of the Ray platform at Anyscale, which underlies technologies like ChatGPT and modern e-commerce systems. This platform has become particularly crucial as AI systems require increasingly sophisticated computational resources to handle complex tasks.

Jordan’s current research focuses on applying machine learning to economic systems, traffic management, and decision-making processes. “Today’s machine learning is not that good at decision-making under uncertainty,” Jordan states. “Uncertainty and the need to reduce it is everywhere, from the decisions made by individual microeconomic agents in local contexts to the dynamics of global markets.”

Jordan emphasizes the importance of human-centric AI development: “I think what artificial intelligence has to do is help us connect better with each other and collaborate more effectively. I want to empower humans, not have the AI tell humans what to do.” His ongoing work includes developing machine learning systems to address congestion in recommender systems and optimize business decision-making processes, contributing to a growing body of research on practical AI applications that prioritize human agency and ethical considerations.

Sources: BBVA