Postdoctoral Scholar
Cognitive Systems Laboratory Computer Science Department University of California, Los Angeles Email: eb at cs dot ucla dot edu Phone: +1 310 267 5645 Address: Boelter Hall, Room 3564, UCLA, Los Angeles, CA, 90024. |

[ summary – news – service – tutorials – talks – publications ]

I obtained my PhD in Computer Science from UCLA, where I had the pleasure of working with Judea Pearl. Previously,
I obtained my B.Sc. and M.Sc. degrees in Computer Science at Federal University of Rio de Janeiro, Brazil.

My research focuses on theoretical causality and its applications to bioinformatics, economics, and public health. More specifically, my thesis work develops formal methods for solving the fundamental problem of generalizing causal and statistical knowledge. The most immediate instances of this problem appear in almost any data analysis under the rubrics of external validity, meta-analysis, and selection bias.

I am broadly interested in Artificial Intelligence, Machine Learning, Statistics, Cogntive Science, and Philosophy of Science.

My CV: pdf (November/15, 2014)

- Nov/2014: Our new paper on selection bias (with J. Tian) was accepted to AAAI-2015.
- Sept/2014: Our new paper on transportability (with J. Pearl) was accepted to NIPS-2014.
- Sep/2014: I was selected as the 2014 Edward K. Rice Outstanding Doctoral Student. This award is given to a single Ph.D. student in all engineering and applied sciences majors at UCLA.
- Jul/2014: Our paper "Recovering from Selection Bias in Causal and Statistical Inference" (link) just received the best paper award at the Annual Conference of the American Association for Artificial Intelligence (AAAI-14).
- Jun/2014: I am honored that I was selected as the "Outstanding Graduating PhD Student" (commencement award), Computer Science, UCLA.
- Jun/2014: I received the "Google Outstanding Graduate Research Award", Computer Science, UCLA.
- Apr/2014: Our new paper on selection bias (with J. Tian and J Pearl) was accepted to AAAI-2014, link.
- Apr/2014: I am honored to be selected as one of the 2014 Dan David Scholars for "outstanding achievement and future promise" in the field of Artificial Intelligence (citation here).
- Apr/2014: I am co-organizing an ICML-14 workshop on Causal Modeling & Machine Learning (with B. Schölkopf, K. Zhang, J. Zhang), consider submitting your work, link.
- Mar/2014: I am a guest editor (with J. Pearl, B. Schölkopf, K. Zhang, J. Li) of ACM Transactions on Intelligent Systems and Technology on "Causal Discovery and Inference". See the call for papers.
- Feb/2014: With Judea Pearl, I gave a tutorial on "Causes and Counterfactuals: Concepts, Principles and Tools" at NIPS 2013. The video (with slides) is available online, link (requires HTML5).
- Sep/2013: Our new paper on transportability was accepted to NIPS-2013, link.
- Jul/2013: The video of my talk on meta-transportability in AISTATS-2013 is now available here.

- Conferences (program committee): AAAI-15, AISTATS-15, KDD-DI-14, UAI-14, AISTATS-14, ICML-14, Causal-NIPS-13, IEEE-BigData-13, IJCAI-13, AAAI-13, UAI-13, ICML-13, UAI-12, ICML-12, IJCAI-11, NIPS-11(Rev), UAI-11, MMIS-ICDM-11, KR-10(Rev).

- Journals (reviewer): Annals of Applied Statistics, Scandinavian Journal of Statistics, The British Journal for the Philosophy of Science, Statistics in Medicine, Statistics, J. of Machine Learning Research (JMLR), J. of Causal Inference, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Bioinformatics, J. of Proteome Research, J. of Proteomics, Physica A.

- (with J. Pearl) "Causes and Counterfactuals: Concepts, principles, and tools", NIPS, Lake Tahoe, NV, Dec/2013.
- "Causality and Big Data”, EMC2 Summer School on Big Data, Rio de Janeiro, Brazil, Feb/2013.
- "An Introduction to Causal Inference", 2nd IEEE Conf. on Healthcare Informatics, Imaging, and Systems Biology, La Jolla, CA, Sep/2012.

- Kyoto International Conference on Modern Statistics, Kyoto, Japan, Nov/2014.
- International Workshop on Causal Inference and its Related Topics, Tokyo, Japan, Nov/2014.
- SIGKDD-14 Workshop on Discovery Informatics, New York, Aug/2014.
- UAI-14 Workshop on Causality: Learning and Prediction, Quebec City, Canada, July/2014.
- Institute of Mathematical Statistics (IMS) Annual Meeting, Sydney, Australia, Jul/2014.
- NICTA, Sydney, Australia, Jul/2014.
- 2014 Atlantic Causal Inference Conference, Providence, RI, May/2014.
- (with J. Pearl) Joint Mathematics Meetings (Big Data: Math and Stats Modeling), American Mathematical Society (AMS), Baltimore, MD, Jan/2014.
- (with J. Pearl) NIPS-13 Workshop on Causality (Large-scale Experimental Design and Inference of Causal Mechanisms), Lake Tahoe, NV, Dec/2013.
- (with J. Pearl) MURI/ONR, UCLA, Los Angeles, California, Sep/2013.
- (with J. Pearl) MURI/ONR, UCLA, Los Angeles, California, Oct/2012.
- Graduate School of Engineering, COPPE/Federal University of Rio de Janeiro (UFRJ), Brazil, May/2012.
- Computer Science Colloquium, CS-Math/Federal University of Rio de Janeiro (UFRJ), Brazil, May/2012.
- 58th World Congress of Statistics, International Statistics Institute (ISI), Dublin, Ireland, Aug/2011.
- DERI/National University of Ireland (NUI), Galway, Ireland, Aug/2011.

**Recovering Causal Effects From Selection Bias**

E. Bareinboim, J. Tian.

In *Proceedings of the 29th Conference on Artificial Intelligence (AAAI)*, 2015, forthcoming.

**
External Validity: From do-calculus to Transportability across Populations
**

J. Pearl, E. Bareinboim.

*Statistical Science*, 2014, forthcoming.
[pdf]

**Transportability from Multiple Environments with Limited Experiments: Completeness Results**

E. Bareinboim, J. Pearl.

In *Proceedings of the 27th Annual Conference on Neural Information Processing Systems (NIPS)*, 2014, forthcoming.

**Spotlight presentation (62 out of 1678 accepted papers).**

**Recovering from Selection Bias in Causal and Statistical Inference**

E. Bareinboim, J. Tian, J. Pearl.

In *Proceedings of the 28th Conference on Artificial Intelligence (AAAI)*, 2014.
[pdf]

**Best Paper Award (1 out of 398 accepted papers).**

**Generalizability in Causal Inference: Theory and Algorithms**

E. Bareinboim.

Ph.D. Thesis, Computer Science Department, UCLA, fothcoming.

**Causal Transportability from Multiple Environments with Limited Experiments**

E. Bareinboim, S. Lee, V. Honavar, J. Pearl.

In *Proceedings of the 26th Annual Conference on Neural Information Processing Systems (NIPS)*, 2013.
[pdf]

**Causal Transportability with Limited Experiments**

E. Bareinboim, J. Pearl.

In *Proceedings of the 27th Conference on Artificial Intelligence (AAAI)*, 2013.
[pdf]

**Meta-Transportability of Causal Effects: A formal approach**

E. Bareinboim, J. Pearl.

In *Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2013.
[pdf]

** A General Algorithm for Deciding Transportability of Experimental Results**

E. Bareinboim, J. Pearl.

*Journal of Causal Inference*, Vol. 1, pp. 107--134, 2013.
[pdf]

** Causal Inference by Surrogate Experiments**

E. Bareinboim, J. Pearl.

In *Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI)*, 2012.
[pdf]

**Transportability of Causal Effects: Completeness Results**

E. Bareinboim, J. Pearl.

In *Proceedings of the 26th Conference on Artificial Intelligence (AAAI)*, 2012.
[pdf]

**Controlling Selection Bias in Causal Inference**

E. Bareinboim, J. Pearl.

In *Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2012.
[pdf]

**Local Characterizations of Causal Bayesian Networks**

E. Bareinboim, C. Brito, J. Pearl.

In * Lecture Notes in Artificial Intelligence (LNAI), Springer*, 2012.
[pdf]

**Transportability of Causal and Statistical relations: A formal approach**

J. Pearl, E. Bareinboim.

In *Proceedings of the 25th Conference on Artificial Intelligence (AAAI)*, 2011.
[pdf]

**External Validity and Transportability: A Formal Approach**

J. Pearl, E. Bareinboim.

In *Proceedings of the Joint Statistical Meetings-American Statistical Association (JSM-ASA)*, 2011.
[pdf]

**Controlling Selection Bias in Causal Inference**

E. Bareinboim, J. Pearl.

In *Proceedings of the 25th Conference on Artificial Intelligence (AAAI)*, 2011.
[pdf]

**Local Characterizations of Causal Bayesian Networks**

E. Bareinboim, C. Brito, J. Pearl.

In *Proceedings of the GKR-22nd International Joint Conference on Artificial Intelligence (IJCAI)*, 2011.
[pdf]

**Analyzing marginal cases in differential shotgun proteomics**

P. Carvalho, J. Fischer, J. Perales, J. Yates III, V. Barbosa, E. Bareinboim.

*Bioinformatics*, Vol 27, pp. 275-276, 2011.
[pdf]

**Descents and nodal load in scale-free networks,**

E. Bareinboim, V.C. Barbosa.

*Physical Review E*, Vol. 77, 046111, 2008.
[pdf]

**Grammatical inference applied to linguistic modeling of biological regulation networks**

E. Bareinboim, A. Vasconselos, J. Silva

*Eletronic Journal of Communication Information & Innovation in Health*, Vol 1, S. pp. 329–333, 2007.

**Characterizing Regulatory Regions in E.coli using Augmented Regular Expressions**

G. Menezes, E. Bareinboim, J. Silva, A. Vasconselos

In *Proceedings of the 3rd Annual Brazilian Association for Bioinformatics and Computational Biology (AB3C) Conference*, 2007.

November 30, 2014.