Academic Paper

Rethinking Streaming Machine Learning Evaluation

May, 2022


While most work on evaluating machine learning (ML) models focuses on computing accuracy on batches of data, tracking accuracy alone in a streaming setting (i.e., unbounded, timestamp-ordered datasets) fails to appropriately identify when models are performing unexpectedly. In this position paper, we discuss how the nature of streaming ML problems introduces new real-world challenges (e.g., delayed arrival of labels) and recommend additional metrics to assess streaming ML performance.

Look-alike humans identified by facial recognition algorithms show genetic similarities

August, 2022


  • Facial recognition algorithms identify “look-alike” humans for multiomics studies
  • Intrapair look-alikes share common genetic sequences such as face trait variants
  • DNA methylation and microbiome profiles only contribute modestly to human likeness
  • The identified SNPs impact physical and behavioral phenotypes beyond facial features