Program

Wednesday Jan 4

Public Talk

17:00 - Welcome

17:30 - Belén Saldías, Human-AI collaboration for Interpretable Content Moderation and Control in Social Media

18:00 - Maggie Hughes, Grassroots Civic Data Infrastructures with Dialogue-Based Data

18:30 - Mohit Karnani, RCTs Meet Market Design: Treatment Effects and Spillovers in Matching Markets

Thursday Jan 5

9:00 - Opening Remarks

9:30 - 11:00: Lecture, From Words to Online Content Moderation, Belén Saldías

Intended Learning Outcomes

By the end of this session, students will be able to:

• Understand opportunities to develop technology that enables human-centered content moderation.

• Understand text-based sentiment analysis, through interaction with Natural Language Processing (NLP) methods.

• Reflect on ethical considerations that apply to their current research.

11:00 - 11:30: Coffee Break

11:30 - 13:00: Lecture, Data Visualization for Research and Storytelling, Maggie Hughes

Intended Learning Outcomes

By the end of this session, students will be able to:

• Choose ways to visualize data responsive to the qualities of your data

• Be able to use design and storytelling to communicate your findings

• Understand how to find patterns in your data

13:00 - 14:30: Lunch (on your own)

14:30 - 16:00: Lecture, A Crash Course on Causal Inference, Mohit Karnani

Intended Learning Outcomes

By the end of this session, students will be able to:

• Understand the fundamental concepts and mathematical objects that define causality

• Prove how some methods allow for the identification of causal effects

• Explain the underlying assumptions and limitations of these methods

• Apply experimental and quasi-experimental methods to identify causal effects

16:00 - 16:30: Coffee Break

16:30 - 18:00: Lecture, Análisis de encuestas en Python: Encuesta CASEN 2020, Carlos Navarrete

El objetivo es realizar ejercicios simples de limpieza y análisis de datos en Python usando datos publicados por la encuesta CASEN 2020.

18:30: Workshop Students Barbecue

Data Science Unit, UdeC. Edmundo Larenas 310

Friday Jan 6

9:00 - 10:00: Lecture, Deep Learning Basics, Manuel Pérez-Carrasco

10:00 - 11:30: Lecture, AutoML: Automating ML pipelines using H20, Cristóbal Donoso-Oliva

11:30 - 12:00: Coffee Break

12:00 - 13:30: Lecture, Domain Adaptation, Manuel Pérez-Carrasco

Monday Jan 9

8:30 - 9:15: Talk, Understanding Dynamics of Agreements, Disagreements and Polarization in the Population, Carlos Navarrete

9:15 - 10:00: Talk, Anytime Automatic Algorithm Selection for np-hard Problems, Roberto Asín-Acha

10:00 - 10:45: Talk, Computación Afectiva y Reconocimiento de Emociones, Pedro Salcedo

10:45 - 11:15: Coffee Break

11:15 - 12:00: Talk, Machine Learning within the ALeRCE broker, Guillermo Cabrera-Vives

12:00 - 13:00: Keynote, ASTROMER: A Transformer-based Embedding for the Representation of Light Curves, Pavlos Protopapas

13:00: Final remarks