2022-01-12 Corvinus workshop on Network and Data Science, BCE NETi Lab [slides] (virtual)
2021-07-29 Core Data Science, Facebook [slides] (virtual)
2021-07-22 Network Inequality Group, Complexity Science Hub Vienna, CSH (virtual)
2020-10-02 WiDS, Escuela Superior Politécnica del Litoral, ESPOL [slides] (virtual - mi doctorado en español)
Inequalities in Networks and Algorithms (new)
May. 2023: Targeted to Master students at TU Wien [see slides]
Social network modeling and applications, a tutorial
Apr. 2023: Targeted to participants of The Web Conference 2023, Austin, TX. [see material]
In Companion Proceedings of the ACM Web Conference 2023, https://doi.org/10.1145/3543873.3587713 (WWW'23)
Designing Academic Posters
Sep. 2022: Targeted to PhD. students at Central European University as part of the Academic Professionalization program.
Introduction to Social Network Science with Python
Sep. 2020: Virtual (zoom) GESIS Methods Seminar [see material]
Graph representations in networkX, I/O operations, visualizations, Hypothesis testing using QAP and MRQAP.
Introduction to Machine Learning using Python
Feb. 2018: Internal CSS workshop [see materials: session1, session2 ]
Data cleaning, pandas, visualization, prediction task, hyper-parameter tuning.
Reviewer: TheWebConf '22 '23, ICWSM '21, '22, '23, WebSci Conference '21 '22 '23, NetSci '23, Advances in Complex Systems '21, Applied Network Science '19, '20, '21, Applied Mathematics and Computation '21, FAT* '20, LXAI-ICML '19, EPJ Data Science '18, LocWeb '17, '18, '19, '20, '21, IC2S2 '17, '21
Sub-reviewer: AAAI'23, Data Mining and Knowledge Discovery '22, Proceedings of the royal society '19, The Journal of Web Science '19, Informatik '19, TheWebConf '18, '19, '20, '21, ACM Hypertext '17, '20, '21, ICWSM '16, WebSci Conference '16, '17, '19, ETCM '16, '17, NordCHI '16.
"Parenthood in Academia" a panel discussion, and "childcare" at NetSci 2023 (new)
"Network Structure" a satellite symposium at Networks 2021, NetSci 2023 (new)
"Diversifying AI" panel at RIIAA 2022
Fairness, Accountability, and Transparency, FAccT '21
Conference in Complex Systems, CCS '21
Networks and Graphs: Classification, Recommendation, and Learning @ TheWebConf '23 (new)
Science of Science@Complex Systems '22
Science Studies@IC2S2 '21
During summer 2018, I did a second internship at the Information Science Institute (ISI) of the University of Southern California (USC). I worked together with Kristina Lerman, Xin-Zeng Wu (Misha) and Buddhika Nettasinghe. Our project focused on the study of network biases in relational classification (e.g., network properties such as assortativity, homophily, density, friendship paradox, majority illusion, that could potentially affect classification).
In summer 2017, I was a 3-month Visiting Research Assistant at the Information Science Institute (ISI) of the University of Southern California (USC). I worked together with Kristina Lerman and Peter Fennell on analyzing the influence of sampling in relational classification.
In January 2017 I was a 2-month Visiting Student Researcher at the Biomedical Informatics Research department (BMIR) at Stanford. I worked on leveraging server logs (users actions through clicks and API requests) to model semantic foraging in BioPortal, a repository of biomedical ontologies. I worked together with Simon Walk and Mark Musen.
Since January 2022, I'm a postdoc at the Network Inequality group at the Complexity Science Hub (CSH) in Vienna. My research at the CSH is part of the Humanized Algorithms project where we want to understand the extent to which the structure of networks biases the outcomes of network-based algorithms. The goal is to propose fairer outcomes---for both minorities and majorities---with or without algorithm interventions. I'm working with Fariba Karimi.
Since January 2021, I'm a postdoc at the Department of Network and Data Science at Central European University (CEU). My research at CEU is part of the SoBigData++ project. In particular, we are interested in producing high-resolution poverty maps using deep learning and multimodal data (e.g., satellite images and mobility networks). The goal is to understand the strengths and limitations of multimodal data and propose interventions (e.g., when data is missing) to accurately predict wealth within and across countries. I'm working with Márton Karsai and János Kertész.
Doctorate (Dr. rer. nat)
In 2022, I defended my PhD. in Computer Science at the University of Koblenz in Germany. During my PhD. I was also a Research Assistant at GESIS - The Leibniz Institute for the Social Sciences where I joined the Data Science group at the Computational Social Science Department. I worked together with my supervisors Claudia Wagner and Markus Strohmaier. I also had the privilege of working with Fariba Karimi, Florian Lemmerich and Philipp Singer.
[abstract] [proposal] [manuscript] [slides] [cite]
Master in Computer Science
In 2014, I got my Master's of Science (Computer Science) degree at the University of Saarland in Saarbrücken, Germany, where I expanded my knowledge in Information Retrieval, Data mining and Databases. I joined the Max Planck Institute for Software Systems in 2013 to work on my Master's thesis where I leveraged user attributes and behaviors in order to discover topical context in conversations from Twitter. I worked together with my supervisor Krishna Gummadi and colleagues Juhi Kulshrestha, Bilal Zafar and Saptarshi Gosh.
Engineer in Computer Science
In 2010, I got my Engineer's degree in Computer Science at Escuela Superior Politécnica del Litoral in Guayaquil, Ecuador where my major studies were focused on Software Engineering, Programming and Human-Computer Interaction. I joined Centro de Tecnologias de Informacion (CTI) as a developer and research assistant to work in several projects including my bachelor's thesis, an Online Social Network based on Liferay, under the supervision of Xavier Ochoa. During this time I also launched my own software development company neoBOX S.A., where I was the President and CTO until 2020.