As Big Data become more ubiquitous, it is imperative that we have methods that sufficiently address the complexities and issues often found with such large data. To this end, I have developed a number of methods which can analyze salient features of large databases. Although I have applied them exclusively to health-related situations, I design them to be general enough as to apply to a wide variety of contexts, improving their potential uptake.
Lienert J, Reed-Tsochas F, Koehly L, and Marcum CS. 2019. Using hospital administrative data to infer patient-patient contact via the consistent co-presence algorithm. 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, 2019, pp. 2756-2762.
Lienert J, Koehly L, Reed-Tsochas F, and Marcum CS. 2019. An efficient counting method for the colored triad census. Social Networks 58:136-42.