This is the personal site of Edgar Jaramillo Rodriguez. I am a PhD candidate in Math at UC Davis; my advisor is Jesus De Loera. My research is in stochastic combinatorial geometry. I earned my MS in Mathematics from UC Davis in 2021, and earned my BA in Applied Mathematics from UC Berkeley in 2018. I am also a passionate educator and an advocate for diversity, equity, and inclusion.
My research can be boiled down to the problem of learning a distribution through sampling. “Learning a distribution” can mean accurately estimating parameters if we assume the underlying distribution is of a special form, such as in Gaussian Mixture Models. However, it can also mean learning other features of the distribution. For example, if we are working with a discrete random process, can we say how many states the process takes and where each state is supported? How likely are we to see the supports of these states intersect and in what configurations? I like to call results of this type probabilistic Tverberg theorems, after the famous theorem of Tverberg.
The main tools I use come from probability theory, convex geometry, mathematical optimization, and topological data analysis, though it feels like I am picking up some new methods every week! I am always interested in meeting others working in these or related fields. Please feel free to reach out if you are looking for collaborators, have questions for me, or just want to say hi!