The Memorial Union Terrace at UW-Madison, overlooking Lake Mendota. A beautiful place to sit by the water and listen to live music.
About Me
I am a Ph.D. student in the Mathematics department at the University of Wisconsin-Madison. My research is in mathematical logic - in particular, recursion theory and model theory.
Office
520 Van Vleck Hall
Office Hours
T, 2:30-4pm; Th, 11-1pm
Address
Department of Mathematics University of Wisconsin 480 Lincoln Drive, Madison, WI 53706
Email
(myLastName)@math.wisc.edu
More to come in the following weeks!
Classwork
UW-Madison (2017- ??)
MATH 741 - Abstract Algebra. Finite group theory, representation theory, rings and modules.
MATH 721 - Real Analysis. Measure theory, Lebesgue integration, differentiation, introduction to Hilbert spaces.
Penn State (2016-2017)
MATH 559 - Recursion Theory. Recursive functions, degrees of unsolvability, hyperarithmetic theory, applications to Borel combinatorics. Computational complexity. Combinatory logic and the Lambda calculus. Taught by Jan Reimann.
MATH 574 - Model Theory. Basic results, quantifier elimination, Fraisse limits of random graphs and dense linear orders, graphons, Morleyâ€™s categoricity theorem, O-minimality, forking and independence. Taught by Jan Reimann.
As an undergraduate I was heavily involved with the Penn State Wind research program and the Collegiate Wind Competition, sponsored by the Department of Energy. My capstone design project was a voltage-sourced rectifier to convert the AC output of a wind turbine's generator to the DC needed for a power supply. I also served briefly as the administrative lead on the Penn State Racing Formula SAE team, which builds a Formula One racecar from scratch every year and races it against other collegiate teams at the Michigan International Speedway.
Fall 2017 - TA'ing for two sections of MATH 221, Calculus 1 for scientists and engineers.
In 2015, I spent a summer at Moody's Analytics in NYC. There, I worked for the lead in-house data scientist, Vladimir Agajanov. I supported his research by writing R and Python scripts to analyze company network data to draw conclusions about the capacity and redundancy of the network, and designing browser-based visualization tools for graph data presentations. Under his direction I studied the application of machine-learning methods to fixed-income and capital markets data for the Capital Markets Research Group.
Check out my LinkedIn page for more recent updates.