This a selection of projects that I have done during my graduate education (i.e., MPP and MA/PhD) on which I have made use of several of my technical skills and domain knowledge.

## Project 16

### The Conceptualization and Measurement of Emotion in Machine Learning: A Critical Appraisal and Recommendations from Psychology

**Type:**Review paper.**Goal/method:**literature review about the conceptualization of emotion in psychology and machine learning, with recommendations for future research.**Role:**Lead researcher.**Software:**LaTeX.

## Project 15

### NumPy Fundamentals for Data Science and Machine Learning

**Type:**Online Interactie Tutorial**Goal/method:**In this document, I review NumPy main components and functionality, with attention to the needs of Data Science and Machine Learning practitioners, and people who aspire to become a data professional. My only assumption is that you have basic familiarity with Python, things like variables, lists, tuples, and loops. Advance Python concepts like Object Oriented Programming are not touched at all.**Role:**Creator.**Software:**Python, Numpy.

## Project 14

### Introduction to the UNIX Shell (Bash)

**Type:**Online Interactie Tutorial (in progress).**Goal/method:**In-depth tutorial about the UNIX shell for researchers.**Software:**Bash.

## Project 13

### Introduction to Linear Algebra for Applied Machine Learning with Python

**Type:**Online Interactie Tutorial**Goal/method::**This document contains introductory level linear algebra notes for applied machine learning. It is meant as a reference rather than a comprehensive review. If you ever get confused by matrix multiplication, don’t remember what was the L2 norm, or the conditions for linear independence, this can serve as a quick reference. It also a good introduction for people that don’t need a deep understanding of linear algebra, but still want to learn about the fundamentals to read about machine learning or to use pre-packaged machine learning solutions. Further, it is a good source for people that learned linear algebra a while ago and need a refresher.**Role:**Creator.**Software:**Python, Numpy, Pandas, Scipy, Altair.

## Project 12

### Introduction to Jupyter Notebooks - set-up, user-guide, and best practices

**Type:**Online Interactie Tutorial.**Goal/method::**In-depth tutorial with video lectures about JupyterLab for researchers and Data Scientists.**Role:**Creator.**Software:**JupyterLab.

## Project 11

### Introduction to Neural Network Models of Cognition - Online Book

**Type:**Online Interactie Book.**Goal/method::**The goal of this project is to implement a selection of canonical models in cognitive science. Theoretical and historical remarks are added along with the mathemtical formulation and code implementation. The algorithms follow a step-by-step code implementation with the aim of maximize conceptual clarity. Models are implemented as Jupyter Notebooks.**Role:**Creator.**Software:**Python, Numpy, Pandas, Altair, Tensorflow/Keras.

## Project 10

### Data Visualization with Altair: a grammar of graphics for Python

**Type:**Workshop and online tutorial.**Goal/method::**This is a interactive tutorial and workshop about Altair 4.0, from the perspective of the grammmar of graphics.**Role:**Lead instructor.**Software:**Python, Pandas, Altair, Jupyter.

## Project 9

### Introducing software development best practices for research in the behavioral and social sciences

**Type:**Workshop and online tutorial.**Goal/method:**In this workshop I provide a few simple principles that require**relatively low effort in exchange of high impact**on improving researchers computational workflows. I also provide a minimal example illustrating the application of this simple principles in a data analysis pipeline.**Role:**Lead instructor**Software:**Python, Numpy, Altair, Keras, Pandas, Scikit-Learn, Scipy.

## Project 8

### Deep Learning for Age-prediction from Features Extracted from Human-Drawings

**Type:**Short research project.**Method:**Combination of (1) Psychological assessments; (2) Machine learning methods: Convolutional Neural Network for feature extraction and Deep Feedforward Neural Networks; (3) and Statistical analysis.**Role:**Lead researcher.**Software:**Python, Tensorflow/Keras.

## Project 7

### Measuring and Assessing the Structure of Human Conceptual Representations using Network Analysis

**Type:**Short research project.**Method:**Combination of (1) Psychological questionnaires; (2) Machine learning methods: Graph-theory and Network Analysis; (3) and Statistical analysis.**Role:**Lead researcher.**Software:**R and Python.

## Project 6

### Exploring the Impact of Early Life Stress on Learning in Dynamic Environments

**Type:**Research paper.**Method:**Combination of (1) Psychological questionnaires; (2) Learning and decision-making task; (3) computational modelling (reinforcement learning delta-rule model); (4) and statistical analysis (multiple linear regression analysis and correlational analysis).**Role:**Lead researcher.**Software:**R and MATLAB.

## Project 5

### Pipeline automation to reproduce and evaluate the variability of genealogical patterns across the genome

**Type:**Class project.**Method:**Python and BASH programming.**Role:**One of three authors.**Software:**Python and BASH.

## Project 4

### Psychological experiment about learning social preferences under stress

**Type:**Class project.**Method:**Python programming using the Psychopy library.**Role:**Lead and only author.**Software:**Python.

## Project 3

### Neurocognitve Basis of Impulsive Buying Behavior

**Type:**Research paper (in progress).**Method:**Combination of (1) Intercept survey to buyers on supermarkets; (2) Decision-making behavioral experiment; (3) and electrophysiological (EEG) recording and analysis.**Role:**Lead researcher. I designed and performed all the stages of the project: field work protocols, survey application, decision-making experiment, and EEG recordings and data cleaning.**Software:**MATLAB, EEG-Lab library and Presentation (Neurobehavioral systems).

## Project 2

### Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task

**Type:**Research paper.**Method:**Combination of (1) Psychological questionnaires; (2) Learning and decision-making task; (3) and statistical analysis (logistic regression, ANOVA and correlational analysis).**Role:**Lead researcher. I collected the data, collaborated on the statistical analysis, and co-authored a research paper as lead-author**Software:**MATLAB and Presentation (Neurobehavioral systems).

## Project 1

### Fitness, Nutrition and Academic Performance in Socioeconomic Context (in Spanish)

**Type:**Master’s thesis in public policy.**Method:**Statistical analysis of large database with educational records of Chilean students (multiple linear regression with and without fixed effects).**Role:**Lead researcher.**Software:**STATA.