AI News, The 27th Annual Conference on the “Artificial Intelligence and ... artificial intelligence

René van Bevern

Dr. rer.

nat.

René van Bevern <rvb@rvb.su> Head

of Algorithmics Laboratory, Senior

lecturer at Chair of Theoretical Cybernetics, Novosibirsk

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Elias Bareinboim

I am an associate professor in the Department of Computer Science and the director of the Causal Artificial Intelligence Lab at Columbia University.

Prior to joining Columbia, I was an assistant professor at Purdue University.

Before that, I obtained my Ph.D.

in Computer Science at the University of California, Los Angeles, advised by Judea Pearl.

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

My research focuses on causal inference and its applications to data-driven fields (i.e., data science) in the health and social sciences as well as artificial intelligence and machine learning.

I am particularly interested in understanding how to make robust and generalizable causal and counterfactual claims in the context of heterogeneous and biased data collections, including due to issues of confounding bias, selection bias, and external validity (transportability).

A survey of recent developments on this topic, when combining massive sets of research data, appeared at the Proceedings of the National Academy of Sciences (PNAS), see the story and the paper.

A brief summary of the automated scientist project was also highlighted at the IEEE Intelligent Systems (link,

story).

For an overview of my thoughts on causal data science, as of April 2019, watch the talk I recently gave at Columbia University, link.

More recently, I have been exploring the intersection of causal inference with decision-making/reinforcement learning (NeurIPS-15, ICML-17, IJCAI-17, NeurIPS-18, AAAI-19, NeurIPS-19) and explainability/fairness analysis (AAAI-18, NeurIPS-18, UAI-19).

Additional information (Nov/11, 2019) --

CV (pdf),

short bio (txt),

hi-res picture (jpg).

In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.

Columbia CausalAI Laboratory, Technical Report (R-55), Nov, 2019, forthcoming.

In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.

Columbia CausalAI Laboratory, Technical Report (R-54), Nov, 2019, forthcoming.

In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.

Columbia CausalAI Laboratory, Technical Report (R-53), Nov, 2019, forthcoming.

In Proceedings of the 34th AAAI Conference on Artificial Intelligence, 2020.

Columbia CausalAI Laboratory, Technical Report (R-52), Nov, 2019, forthcoming.

Columbia CausalAI Laboratory, Technical Report (R-51), Dec, 2019.

[pdf]

In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems, 2019.

Spotlight Presentation (164 out of 6743 papers).

Columbia CausalAI Laboratory, Technical Report (R-50), Sep, 2019, forthcoming.

In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems, 2019.

Columbia CausalAI Laboratory, Technical Report (R-49), Oct, 2019.

[pdf]

In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems, 2019.

Columbia CausalAI Laboratory, Technical Report (R-48), Oct, 2019.

[pdf]

In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems, 2019.

Columbia CausalAI Laboratory, Technical Report (R-47), Oct, 2019.

[pdf]

In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, 2019.

Columbia CausalAI Laboratory, Technical Report (R-46), May, 2019.

[pdf]

Best Paper Award (1 out of 450 papers).

In Proceedings of the 27th International Joint Conference on Artificial Intelligence, 2019.

Columbia CausalAI Laboratory, Technical Report (R-45), May, 2019.

[pdf]

In Proceedings of the 27th International Joint Conference on Artificial Intelligence, 2019.

Columbia CausalAI Laboratory, Technical Report (R-44), May, 2019.

[pdf]

In Proceedings of the 36th International Conference on Machine Learning, 2019.

Columbia CausalAI Laboratory, Technical Report (R-43), Apr, 2019.

[pdf]

In Proceedings of the 36th International Conference on Machine Learning, 2019.

Columbia CausalAI Laboratory, Technical Report (R-42), Apr, 2019.

[pdf]

In Proceedings of the 36th International Conference on Machine Learning, 2019.

Columbia CausalAI Laboratory, Technical Report (R-41), Apr, 2019.

[pdf]

In Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 2019.

Columbia CausalAI Laboratory, Technical Report (R-40), Nov, 2018.

[pdf]

In Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 2019.

Columbia CausalAI Laboratory, Technical Report (R-39), Nov, 2018.

[pdf]

In Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 2019.

Columbia CausalAI Laboratory, Technical Report (R-38), Nov, 2018.

[pdf]

In Proceedings of the 32nd Annual Conference on Neural Information Processing Systems, 2018.

Columbia CausalAI Laboratory, Technical Report (R-37), 2018.

[pdf]

In Proceedings of the 32nd Annual Conference on Neural Information Processing Systems, 2018.

Columbia CausalAI Laboratory, Technical Report (R-36), September, 2018.

[pdf, code]

In Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, 2018.

Columbia CausalAI Laboratory, Technical Report (R-35), August, 2018.

[pdf]

Best Student Paper Award (1 out of 337 papers).

In Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, 2018.

Columbia CausalAI Laboratory, Technical Report (R-34), May, 2018.

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In Proceedings of the 35th International Conference on Machine Learning, 2018.

Columbia CausalAI Laboratory, Technical Report (R-33), May, 2018.

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In Proceedings of the 26th International Joint Conference on Artificial Intelligence, 2018.

Columbia CausalAI Laboratory, Technical Report (R-32), May, 2018.

[pdf]

A note on 'Generalizability of Study Results (Lesko et al., 2017)'

30(2), pp.

186-188, 2019.

Columbia CausalAI Laboratory, Technical Report (R-31), Apr, 2018.

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In Proceedings of the 32nd AAAI Conference on Artificial Intelligence, 2018.

Columbia CausalAI Laboratory, Technical Report (R-30), Nov, 2017.

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In Proceedings of the 32nd AAAI Conference on Artificial Intelligence, 2018.

Outstanding Paper Award Honorable Mention (2 out of 3800 papers).

In Proceedings of the 31st Annual Conference on Neural Information Processing Systems, 2017.

In Proceedings of the 34th International Conference on Machine Learning, 2017.

In Proceedings of the 34th International Conference on Machine Learning, 2017.

In Proceedings of the 26th International Joint Conference on Artificial Intelligence, 2017.

In Proceedings of the 31st AAAI Conference on Artificial Intelligence, 2017.

Causal inference and the data-fusion problem

113 (27), pp.

7345-7352, 2016.

In Proceedings of the 25th International Joint Conference on Artificial Intelligence, 2016.

Comment on 'Causal Inference using invariance prediction: identification and confidence intervals (by Peters, Buhlmann and Meinshausen)'

In Proceedings of the 28th Annual Conference on Neural Information Processing Systems, 2015.

In Proceedings of the 29th AAAI Conference on Artificial Intelligence, 2015.

In Proceedings of the 27th Annual Conference on Neural Information Processing Systems, 2014.

Spotlight Presentation (62 out of 1678 papers).

In Proceedings of the 28th AAAI Conference on Artificial Intelligence, 2014.

Best Paper Award (1 out of 1406 papers).

External Validity: From do-calculus to Transportability across Populations

29(4), pp.

579-595, 2014.

In Proceedings of the 26th Annual Conference on Neural Information Processing Systems, 2013.

In Proceedings of the 27th AAAI Conference on Artificial Intelligence, 2013.

Meta-Transportability of Causal Effects: A formal approach

In Proceedings of the 16th International Conference on Artificial Intelligence and Statistics, 2013.

1(1), pp.

107--134, 2013.

In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, 2012.

In Proceedings of the 26th AAAI Conference on Artificial Intelligence, 2012.

In Proceedings of the 15th International Conference on Artificial Intelligence and Statistics, 2012.

Transportability of Causal and Statistical relations: A formal approach

In Proceedings of the 25th AAAI Conference on Artificial Intelligence, 2011.

In Proceedings of the 25th AAAI Conference on Artificial Intelligence, 2011.

Analyzing marginal cases in differential shotgun proteomics

Bioinformatics, Vol 27, pp.

275-276, 2011.

Descents and nodal load in scale-free networks

77, 046111, 2008.

2018 Isaac Asimov Memorial Debate: Artificial Intelligence

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GMIC Beijing 2018 Opening Video on Artificial Intelligence

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How AI Will Change the Workforce | Jack Fitzpatrick

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Highlights of Global Artificial Intelligence Conference - Seattle April 2018

Global Big Data Conference's vendor agnostic Global Artificial Intelligence(AI) Conference is held on April 27th, April 28th & April 29th 2018 on all industry ...

IJCAI-ECAI 2018 Max Tegmark Intelligible Intelligence & Beneficial Intelligence

Max Tegmark, Massachusetts Institute of Technology, held a keynote, “Intelligible Intelligence & Beneficial Intelligence”, at IJCAI-ECAI 2018, the 27th ...

Artificial Intelligence and Your Business (FCL December 27th)

Dario Gil explains how Artificial Intelligence impacts businesses.

IJCAI-ECAI 2018, Yann LeCun Learning World Models – The Next Step Towards AI

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GRC Summit 2019 - Teaser

See what's in store this June for #GRC professionals like you. Register here: #GRCSummit

Global Artificial Intelligence Conference - Seattle April 2018

Big Data Bootcamp is on April 27th, 28th and 29th 2018. Global Big Data Conference is offering 3 day extensive bootcamp on Big Data. This is a fast paced, ...