Matthew Gerber

Assistant Professor

Systems and Information Engineering

Research Summary and Bio
Many systems can be accurately characterized using direct observation mediated by electronic sensors. For example, one can collect accurate data for systems ranging from patient health (e.g., blood pressure monitoring) to transportation infrastructure and social networks. However, human-oriented systems also contain a tremendous amount of information stored as unstructured text. For example, medical data are replete with narratives written by physicians and treatment standards written by medical experts. Similarly, the condition of and events associated with our highway infrastructure are often described with written narratives. Social networks have convenient graph-theoretical properties, but their true source of influence (e.g., over consumer habits and national revolutions) lies in the unstructured, textual messages they convey. In all such systems, the complexity and ambiguity of natural (i.e., human) language limit our ability to perform automated observation and analysis. My research removes these limitations by automatically identifying structured information within unstructured text.

I received my Ph.D. in Computer Science from Michigan State University in 2011 and joined the PTL soon thereafter as a research faculty member. I started as Assistant Professor in 2014. (CV / Dissertation)

Current Projects Past Projects




External Sites

  • ResearchGate
  • GitHub

  • View Matthew Gerber's profile on LinkedIn

Contact: msg8u (add "" to end)