Daniel Daza
Q d.dazacruz@vu.nl

Education

Amsterdam, The Netherlands dfdazac.github.io
 dfdazac

7 danieldazac

Vrije Universiteit Amsterdam
September 2019 - Present
PhD Candidate
Amsterdam, The Netherlands
Supervisors: Paul Groth (University of Amsterdam), Michael Cochez (Vrije Universiteit Amsterdam)
University of Amsterdam
September 2017 - August 2019
MSc in Artificial Intelligence
Amsterdam, The Netherlands
Cum Laude
Average: 8.3/10
Thesis: A modular framework for unsupervised graph representation learning
Supervisor: Thomas Kipf
UD Francisco Jose de Caldas
August 2010 - August 2016
BSc in Electronics Engineering
Bogotá, Colombia
Average: 8.4/10. Graduated 1st place in class
Received three Honors Scholarship awards.
Thesis: Designing electrical machines with AI methods, Merit AwardInterests

Publications

Information extraction, representation learning on knowledge graphs, weakly andunsupervised learning.
 D. Daza, M. Cochez, and P. Groth, SlotGAN: Detecting Mentions in Text
via Adversarial Distant Learning
ACL Workshop on Structured Prediction for NLP (2022). (pdf. code) E. Arakelyan*, D. Daza*, P. Minervini*, and M. Cochez, Complex Query
Answering with Neural Link Predictors
ICLR (2021) - Outstanding Paper Award (top 1%). (pdf, code) D. Daza, M. Cochez, and P. Groth, Inductive Entity Representations from
Text via Link Prediction
The Web Conference (2021). (pdf, code) D. Daza and M. Cochez, Message passing query embedding
ICML Workshop on Graph Representation Learning (2020). (pdf, code)* Equal contribution
Technical skills

Python, PyTorch, TensorFlow, Java, Android Programming, Matlab, Git.

Work Experience University of Amsterdam
November 2018 – January 2019
Teaching Assistant
Amsterdam, The Netherlands
I guided students of the master’s program in Artificial Intelligence following the Natural Language Processing course.
Irdeto B.V.
Data Science Intern

June 2018 - August 2018
Hoofddorp, The Netherlands

Worked on the design and deployment of scalable machine learning products withTensorFlow on Kubernetes clusters and cloud storage.
Chegg.com
January 2015 - August 2017
Private Tutor
Tutoring in mathematics, programming, databases, computer science, machine learning and scientific computing. Aided students around the world reviewing topics andassisting them on diverse projects.
UD Francisco José de Caldas
August 2015 - December 2015
Research Assistant
Bogotá, Colombia
Worked on preparing seminars and events led by the Automation and Computational
Intelligence Laboratory (LAMIC). Assisted on research, publication and teachingtasks carried out by the group.
UD Francisco José de Caldas
February 2013 – June 2015
Teaching Assistant
Bogotá, Colombia
Guided students with assignments and laboratory projects, assisted professors onpreparing their lectures and required materials, prepared demonstrations for the students to complement lectures.
Invited Talks

Deloitte, Amsterdam, The Netherlands
June 2022
Learning Entity Representations from Knowledge Graphs and Textual Descriptions
Zeta Alpha, Amsterdam, The Netherlands
Inductive Entity Representations from Text via Link Prediction
King’s College London, London, UK
Complex Query Answering with Neural Link Predictors

September 2021

March 2021

Delft University of Technology, Delft, The Netherlands
September 2020
Graph Neural Networks for Query Answering Over Knowledge Graphs
Elsevier, Amsterdam, The Netherlands
Message Passing Query Embedding
Miscelaneous

Oxford ML Summer School
Attendee (5% acceptance rate)

February 2020

August 2021

University of Bergen Summer School on Knowledge Graphs and Machine
Learning
June 2022
Attendee, and speaker at oral presentation
Supervision
Stefan Schouten, “Incorporating Semantics in Knowledge Graph Embeddings” (MScthesis, University of Amsterdam, 2021).
Qingzhi Hu, “Data Integration and Predictive Modeling for Impact Investing” (MScthesis, University of Amsterdam, 2022).
Fredrik Skjelvik, “Complex Query Answering in the Biomedical Domain” (BSc thesis,Vrije Universiteit Amsterdam, 2022).