CLEARANCE LEVEL 5

Dr. Emily Parser

Chief Data Scientist

Dr. Emily Parser pioneered the use of machine learning for threat detection at Cyberez. Starting her research career at Rutgers CBIM working on computational biology, she later shifted to adversarial AI during her doctoral work at Stanford. This unique background in biological pattern recognition proved invaluable for identifying daemon-corrupted behaviors. Dr. Parser's algorithms can distinguish between human and synthetic behavior with 91% accuracy. Her work has become critical as the signal degradation crisis intensifies.

Career Timeline

Chief Data Scientist

Cyberez Systems

2021-Present

Principal Data Scientist

Palantir Technologies

2018-2021

Senior Machine Learning Engineer

Google DeepMind

2015-2018

Data Scientist

Facebook AI Research

2013-2015

Research Assistant

Rutgers CBIM

2011-2013

Graduate Research Fellow

Rutgers University

2009-2011

Daemon Interaction Log

[2025.01.27.08:15:32] ML cluster authentication initiated. GPU resources requested.

[2025.01.27.08:15:45] Behavioral analysis models loading. Pattern recognition active.

[2025.01.27.08:16:02] Synthetic agent detected in training data. TRACE_ID: NEURAL-NET-POISON-7732

[2025.01.27.08:16:18] Access granted. Neural networks synchronized.

Security Certifications

PhD in Computer Science - Stanford University

MS in Machine Learning - Carnegie Mellon

Google Cloud Professional ML Engineer

AWS Certified Machine Learning - Specialty

Cyberez Daemon Protocol Authorization Level 5

Notable Achievements

Published 23 peer-reviewed papers on adversarial AI

Developed behavioral biometrics system with 91% accuracy

Patent holder for "Synthetic Agent Detection via Neural Networks"

MIT Technology Review "35 Under 35" recipient

Lead architect of Cyberez ML threat detection platform