Alexander Kolker

Expert in Healthcare Management Science, Operations Research, Business Analytics and Operations Management,

Alexander Kolker holds a Ph.D. in applied mathematics. He is an expert in advanced data analytics for operations management, computer simulation, and staffing optimization with the main focus on healthcare applications.

Alexander is the lead editor and author of 2 books, 8 book chapters, 10 journal papers, and a speaker at 18 international conferences & webinars in the area of operations management and data analytics. As an adjunct faculty at the UW-Milwaukee Lubar School of Business, he developed and taught a graduate course Business 755-Healthcare Delivery Systems-Data Analytics. He worked 12 years for GE (General Electric) Healthcare as a Data Scientist and CT Detector design engineer, 3 years for Froedtert Hospital, the largest healthcare facility in Southern state of Wisconsin, and 5 years for Children’s Hospital of Wisconsin as a lead computer simulation and system improvement consultant.

Currently he is teaching a 12-sessions online course “Healthcare Operations Research and Management Science” for the UK, National Health System (NHS).


  • Recorded Webinars

Alexander Kolker

Healthcare Data Analytics: Methods of Matching Scarce Resources with uncertain Patient Demand: Introduction into the Queuing Analytic Models in Healthcare Settings

Waiting lines in healthcare are everywhere. Queuing theory is one of the main tools of Data Analytics/Operations Research. It is a quantitative approach to the analysis of the properties of waiting for lines (queues) when patients’ arrival (demand for service) and service time (supply) are random values. A set of examples from real hospital practice (the radiology department, Froedtert Hospital, WI) and an outpatient clinic with a different number of servers will be presented.

Alexander Kolker

Healthcare Data Analytics: Methods of Matching Scarce Resources with uncertain Patient Demand: Introduction into the Queuing Analytic Models in Healthcare Settings

Waiting lines in healthcare are everywhere. Queuing theory is one of the main tools of Data Analytics/Operations Research. It is a quantitative approach to the analysis of the properties of waiting for lines (queues) when patients’ arrival (demand for service) and service time (supply) are random values. A set of examples from real hospital practice (the radiology department, Froedtert Hospital, WI) and an outpatient clinic with a different number of servers will be presented.

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