Juan's Picture
Juan D. Correa
Assistant Professor
CS Department - Universidad Autónoma de Manizales
jcorrea [at] autonoma [dot] edu [dot] co
juandavidcorreagranada

I obtained my Ph.D. from the Computer Science Department at Columbia University, where I was adviced by Professor Elias Bareinboim.
My research is on the fundamental conditions and methods to make causal claims from data collected in heterogenous domains, obtained by experimentation or under sampling selection bias.

News

Publications

New General Transportability of Soft Interventions: Completeness Results
Juan D. Correa, Elias Bareinboim
Columbia Causal AI Lab, Technical Report (R-68), Jun 2020.
NeurIPS-20. In Proceedings of the 34th Annual Conference on Neural Information Processing Systems, , forthcoming.
On Pearl's Hierarchy and the Foundations of Causal Inference
Elias Bareinboim, Juan D. Correa, Duligur Ibeling, Thomas Icard
Columbia Causal AI Lab, Technical Report (R-60), Jul 2020.
ACM-20. In Probabilistic and Causal Inference: The Works of Judea Pearl (ACM Special Turing Series), forthcoming.
A Calculus for Stochastic Interventions: Causal Effect Identification and Surrogate Experiments
Juan D. Correa, Elias Bareinboim
Columbia Causal AI Lab, Technical Report (R-55), Nov 2019.
AAAI-20. In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.
Generalized Transportability: Synthesis of Experiments from Heterogeneous Domains
Sanghack Lee, Juan D. Correa, Elias Bareinboim
Columbia Causal AI Lab, Technical Report (R-53), Nov 2019.
AAAI-20. In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.
Identifiability from a Combination of Observations and Experiments
Sanghack Lee, Juan D. Correa, Elias Bareinboim
Columbia Causal AI Lab, Technical Report (R-52), Nov 2019.
AAAI-20. In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.
General Identifiability with Arbitrary Surrogate Experiments
Sanghack Lee, Juan D. Correa, Elias Bareinboim
Purdue AI Lab, Technical Report (R-46), May 2019.
UAI-19. In In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, 2019.
Best Paper Award (1 out of 450 papers).
From Statistical Transportability to Estimating the Effects of Stochastic Interventions
Juan D. Correa, Elias Bareinboim
Purdue AI Lab, Technical Report (R-45), May 2019.
IJCAI-19. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, 2019.
Adjustment Criteria for Generalizing Experimental Findings
Juan D. Correa, Jin Tian, Elias Bareinboim
Purdue AI Lab, Technical Report (R-43), Apr 2019.
ICML-19. In Proceedings of the 36th International Conference on Machine Learning, 2019.
Identification of Causal Effects in the Presence of Selection Bias
Juan D. Correa, Jin Tian, Elias Bareinboim
Purdue AI Lab, Technical Report (R-38), Nov 2018.
AAAI-19. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 2019.
Generalized Adjustment Under Confounding and Selection Biases
Juan D. Correa, Jin Tian, Elias Bareinboim
Purdue AI Lab, Technical Report (R-29), Nov 2017.
AAAI-18. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence, 2018.
Outstanding Paper Award Honorable Mention (2 out of 3800 papers).
Causal Effect Identification by Adjustment under Confounding and Selection Biases
Juan D. Correa, Elias Bareinboim
Purdue AI Lab, Technical Report (R-24), Nov 2016.
AAAI-17. In Proceedings of the 31st AAAI Conference on Artificial Intelligence, 2017.
Pre-PhD
Grid Computing and CBR Deployment: Monitoring Principles for a Suitable Engagement
Luis F. Castillo, Gustavo Isaza, Manuel G. Bedia, Miguel Aguilera, Juan D. Correa
Distributed Computing and Artificial Intelligence, 2012.

Teaching

  • Graduate Teaching Assistant - Columbia University
    • COMS4995W Causal Inference (Fall 2020)
    • COMS4995W Causal Inference (Spring 2020)
  • Graduate Teaching Assistant - Purdue University
    • CS590-AML Advanced Machine Learning (Spring 2019)
    • CS471 Intro to Artificial Intelligence (Spring 2018)
    • CS590-AI Artificial Intelligence (Fall 2017)
    • CS471 Intro to Artificial Intelligence (Spring 2017)
    • CS590-AI Artificial Intelligence (Fall 2016)
  • Lecturer - Universidad Autonoma de Manizales
    • Introduction to Programming (2014-2015)
    • Object Oriented Programming (2013-2014)
  • Lecturer - Universidad de Caldas
    • Introduction to Programming (2013)
    • Introduction to Artificial Intelligence (2013)