Mary McGlohon

Mary McGlohon is a Site Reliability Engineer at Google who specializes in large-scale Machine Learning (ML) systems.34 She has been working on these systems for the past 6 years.5 Her career path includes:

1. Education:

   • B.S. in Computer Science from the University of Tulsa4
   • Ph.D. in Machine Learning from Carnegie Mellon University (CMU)4

2. Previous Experience:

   • Data mining research4
   • Software development4
   • Work on distributed pipeline systems4

3. Research:

   • While at CMU, she conducted thesis research on finding patterns of network formation, evolution, and diffusion in real networks, applying these patterns to anomaly detection and consumer product reviews1
   • Co-authored a paper titled "OddBall: Spotting Anomalies in Weighted Graphs" with Christos Faloutsos and Leman Akoglu, which won the "Most Influential Paper Award" at PAKDD 20202

4. Current Focus:

   • Interested in how production techniques can improve ML for human operators and users4
   • Presented on "Demystifying Machine Learning in Production: Reasoning about a Large-Scale ML Platform" at SREcon214

McGlohon's expertise lies in bridging the gap between Machine Learning systems and Site Reliability Engineering, focusing on making ML systems more reliable and understandable for SREs and operators.3