yes, geospatial could be interesting. The tools depend on what the university / lecturer prefers, for me it was Julia for programming in math courses, JuMP.jl for optimization modeling, Python for ML courses.
Probably the most elegant math book I have ever seen is Probabilty theory a graduate course by Achim Klenke. A very nice exposition into the abstract, measure theoretic prob. thoery (but it assumes some prior knowledge).
Many applications stem from a simple observation: if two activities must be performed consecutively then the time required to complete both is the sum of the individual times, but if they may be performed concurrently then the time required is the maximum of the individual times.
Hi!
We are a group of students from Germany, searching for interesting projects, where we could contribute and learn a lot. Our interests are: applied category theory, computational + "anything" and more generally any applicable math (optimization, ML etc.). We actively search for interesting non-standard topics that might be in a long-term perspective relevant, could enrich our backgrounds and serve as a source of inspiration for future research.
We would love to hear your ideas & suggestions!
Thank you.
honestly a bit far fetched, my model tries to unify and build on scientific research without trying to make big claims about things we have not formalized yet. I think information is encoded into consistencies (we can and or cannot observe).