MS & MSEM – Systems Engineering students – Useful information

Here’s some useful information for current and future MS & MSEM students.

  • To Do List” for 1st Year MS & MSEM Systems students
    • Visit the required and elective courses (link above).
    • Discuss intended masters’ duration with your advisor: this influences the number of courses per semester, cost of the program, etc. (INFO below).
    • Decide your technical focus(es): decision and data analysis, network analysis, natural disaster modeling, energy systems, healthcare systems.
    • Compile a list of courses in which you’re interested for the first semester and discuss with the advisor. follow a “gradualist” approach for selecting courses: start with foundational courses and in next semesters move to more advanced courses : More info HERE. Think of courses in terms of 3 “types of courses”: 1) computational/skills, 2) modeling/simulational, 3) policy design. All three areas should be covered!
    • Advisor approval is needed to course registrations in the SIS.
  • EP Courses (how to register)
    • Go to https://support.sis.jhu.edu/case/
    • Log in with your JHED
    • Click on Browse all Topics
    • Go to Records and Registration
    • Go to Interdivisional Registration (IDR)
    • Follow directions under ASEN Students

Research Opportunities for MS/MSEM-SE’s

I have some research project opportunities for Summer semester (and maybe during the year). Topics listed below. In all cases, products must be in Jupyter. Coding skills in one of the following is needed: Matlab, R, Python, Vensim, Blender QGis. If this sounds interesting, email me ([email protected]) your updated resume.

  • Spatial statistics: descriptive and predictive modeling, interpolation keeping statistical structure, etc. applied one or more types of data (damage, agricultural, etc.)
  • Cartography: i.e. create nice-looking maps with R, Matlab, Blender, QGis, etc.
  • Infrastructural condition assessment: work on an existing MCMC model to predict missing condition data.
  • Building vulnerability studies: from data collection, literature survey, to developing system dynamics models, and/or Monte Carlo simulations.