José Bayoán Santiago Calderón is a postdoctoral research associate at the Social and Decision Analytics Division of the Biocomplexity Institute and Initiative at University of Virginia. He specializes in methodology including regression analysis, machine learning, agent-based modeling, geographic information systems, and experiments.
PhD in Economics, 2019
Claremont Graduate University
MA in Economics, 2015
Claremont Graduate University
BA in Economics, 2014
Agent-Based Modeling (ABM)
Geographic Information Systems (GIS)
Natural Language Processing (NLP)
Build Intelligent Applications
In this Specialization, you’ll learn the fundamentals of one of the most exciting and high-demand fields in modern computer science. When you complete the five courses and Capstone Project, you’ll be prepared to analyze large and complex datasets from a variety of sources, make predictions from data, and create adaptable systems to solve real-world problems.
This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.
As a scientific computing intern, I contribute to the data generation and processing tools for various modeling designs (e.g., PK/PD, PBPK, QSP) and for conducting bioequivalence studies. The code will be released in early 2019 as open-source. Projects are under the supervision of professor Vijay Ivaturi and Chris Rackauckas.
Supervisor: Vijay Ivaturi, PhD
I am a member of the team developing and maintaining the QuantEcon lectures for the Julia language and related code (e.g., QuantEcon.jl). The undergraduate and graduate level lectures cover various topics in quantitative economics. The code is available at the Github repository (open-source).
Supervisor: Jesse Perla, PhD
I led two research projects and consulted for a third one. My responsibilities included working with the sponsor and undergraduate students tasked to these projects.
Supervisor: Gizem Korkmaz, PhD
I assisted with analytical modeling and software integration. Some of my experiences include working in the team that developed the data validation and preprocessing for the analytic tools provided in the software. My work focused on the designed and implementation of the algorithms used in prediction and benchmarks for energy and water utility accounts (performed using R).
Supervisor: Hal Nelson, PhD
I performed various roles such as: recruiting participants, conducting design-stage research, piloting laboratory experiments, running experiments, and cleaning and analyzing data. The laboratory experiments included administrating drugs, collecting blood samples, eye-tracking, electroencephalogram (EEG), electrocardiogram (ECG), and standard experimental laboratory studies.
Supervisor: Paul J. Zak, PhD
2016 Advanced Research Methods (Graduate), Michigan State University, for Dr. Lisa Cook, through the AEA Summer Program
2015 Principles of Microeconomics (Undergraduate), Johns Hopkins University, through the Center for Talented Youth
2014 Intermediate Microeconomics (Undergraduate), Southwestern University
2014 Principles of Economics (Undergraduate), Southwestern University