Computer scientist and distinguished expert in biometric presentation attack detection and unconstrained face recognition systems, with over 15 years of leadership experience in U.S. national security and technology sectors. Key specialties include computer vision, 3D biometrics, iris recognition, facial feature analysis, and AI/ML systems for biometric authentication and spoofing detection. Holds a Ph.D. in Computer Science with demonstrated expertise in translating complex technical systems for legal audiences. Recipient of the Presidential Early Career Award for Science and Engineering.
Formal Education
- Ph.D. in Computer Science from University of Notre Dame
- M.S. in Computer Science from University of Notre Dame
- B.S. in Computer Engineering from University of Notre Dame
Career Highlights
- Technical Program Manager and Data Program Lead at a major technology company, currently directing teams of 80+ full-time employees and contractors for next-generation user interaction research including data collection, AI/ML processing, privacy, security, and ethics
- Director of Science and Technology and Deputy Assistant Director at a federal intelligence agency, responsible for legislatively mandated science and technology activities
- Program Manager at a federal research agency, directing over 200 scientists and engineers across 25+ organizations worldwide on large-scale research programs including biometric presentation attack detection and unconstrained face recognition
- Founded and built a specialized research team at a federal research laboratory, growing the team to 7 full-time staff and serving as Principal Investigator on substantial federal research funding spanning 10+ projects
- Successfully transitioned biometric technologies to over 20 Intelligence Community organizations through leadership of major research programs for unconstrained face recognition and biometric presentation attack detection
- Joint Faculty member at a major research university
- Recipient of a prestigious federal award for science and engineering and an early career award from a research institution
Expert Qualifications
- Leading authority on biometric presentation attack detection and anti-spoofing systems with peer-reviewed publications and multiple patents in iris recognition via plenoptic imaging
- Extensive subject matter expertise in supporting U.S. national security operations, having worked at federal intelligence agencies and a federal research laboratory on classified and unclassified intelligence programs
- Proven ability to translate complex technical biometric systems and AI/ML concepts for legal and non-technical audiences, with featured appearances in major media outlets
- Available for expert testimony and litigation support on matters involving biometric authentication systems, facial recognition technology, anti-spoofing systems, iris recognition, and AI/ML applied to biometric systems
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Frequently Asked Questions
What types of cases can this expert support?
This expert handles cases involving facial recognition, iris recognition, and biometric spoofing or anti-spoofing systems. They bring 15+ years of practical experience from national security and federal research work, understanding both how these systems function and where they fail. Moderate litigation readiness means they're testifiable, though not a seasoned courtroom veteran.
What is this expert's technical background?
They came up through Computer Science/Engineering at Notre Dame (Ph.D., M.S., B.S.), then spent 15+ years in national security and tech, progressively taking on bigger leadership roles—directing 200+ scientists on federal biometric research programs, running teams at a major tech company, and holding director positions at federal intelligence and research agencies. They're also a joint faculty member at a major research university and won the Presidential Early Career Award for Science and Engineering.
What technologies does this expert specialize in?
This expert specializes in face recognition, iris recognition, 3D biometrics, and biometric presentation attack detection (anti-spoofing systems). They work across facial feature detection, gaze estimation, plenoptic imaging, sensor fusion, and the machine learning/deep learning algorithms that power these systems. Coverage spans both hardware sensing and algorithmic layers of modern biometric authentication.
- Face recognition systems
- Iris recognition and segmentation
- Biometric presentation attack detection
- 3D face recognition algorithms
- Plenoptic imaging
- Facial feature landmarking
- Gaze estimation and correction
- Computer vision
- Machine learning and deep learning
- Biometric sensor fusion
- U.S. District Courts
- Patent Trial and Appeal Board