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BACKGROUND
Causation is our framework for understanding how the world works, it is our basis for interventions to achieve desired outcomes. This topic continues to engage the imagination of scholars in an unusually wide range of disciplines, including computer science, neuroscience, psychology, epidemiology, cognitive science, sociology, philosophy, mathematics, and economics. There are exciting opportunities at the interface between these fields that this symposium will explore and foment. This ICLM meeting was funded by multiple UCLA departments, the BRI and the UCLA Office of Interdisciplinary & Cross Campus Affairs.
SYMPOSIUM
It will take place in the UCLA Medical School Campus (NRB auditorium) on September 25th, 2017 and it will cover a wide range of topics on the general theme of Causal Inference, from computer science, to neuroscience, psychology, epidemiology, cognitive science, sociology, philosophy, mathematics, and economics. The speakers are world-renowned leaders in this far reaching topic with implications that touch every facet of the human experience. The meeting will consist of TED-like talks accessible to everyone in this multidisciplinary topic
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Registration is free but required

If you are having problems with registering, send an email with your name and department information to silvaa#mednet.ucla.edu
For questions contact Alcino Silva (silvaa#mednet.ucla.edu)
Schedule:
Neuroscience Research Building Auditorium, 635 Charles Young Drive South Los Angeles, Westwood.
For a map of NRB and parking click here

08:55 AM – 09:00 Alcino Silva (UCLA): Introduction
09:00 AM – 09:18
Chris Hitchcock (Caltech): Causation in science and everyday life
09:18 AM – 09:23 Q & A
09:23 AM – 09:41
Frederick Eberhardt (Caltech): Large and small causes
09:41 AM – 09:46 Q & A
09:46 AM – 10:04
Ralph Adolphs (Caltech): What causes our thoughts and feelings?
10:04 AM – 10:09 Q & A
10:09 AM – 10:27
Pietro Perona (Caltech): Causality in vision
10:27 AM – 10:32 Q & A

10:32 AM –10:52 BREAK
10:52 AM – 11:10
Alcino Silva (UCLA): Research maps: an approach to integrate and gauge causal information
11:10 AM – 11:15 Q & A
11:15 AM – 11:33
William Hsu (UCLA): Causal inference in experiment planning
11:33 AM – 11:38 Q & A
11:38 AM – 11:53
Onyebuchi Arah (UCLA): Regression diagrams in causal analysis
11:53 AM – 11:58 Q & A
11:58 AM – 12:16
Chad Hazlett (UCLA): Making sense of sensitivity: Extending omitted variable bias
12:16 PM – 12:21 Q & A

12:21 PM – 1:21
LUNCH
1:21 PM – 1:39
Sander Greenland (UCLA): Cognitive distortions of causal-inference statistics: Why observational studies of statistical stupidity should inform analysis methodology
1:39 PM – 1:44 Q & A
1:44 PM – 2:02
Maya Petersen (Berkeley): Integrating machine learning in causal effect estimation
2:02 PM – 2:20 Q & A
2:20 PM – 2:38
Patricia Cheng (UCLA): Is natural human learning rational?
2:38 PM – 2:43 Q & A
2:43 PM – 3:01
Aaron Blaisdell (UCLA): Causal reasoning in rodents
3:01 PM – 3:06 Q & A

3:06 PM – 3:26
BREAK

3:26 PM – 3:44
Mayank Mehta (UCLA): Neuronal dynamics of predictive coding
3:44 PM – 3:49 Q & A
3:49 PM – 4:07
Huiying Li (UCLA): The human skin microbiome in health and disease
4:07 PM – 4:12 Q & A
4:12 PM – 4:30
Jonathan Braun (UCLA): Illness as metaphor – what the microbiome teaches us about the nature of health
4:30 PM – 4:35 Q & A
4:35 PM – 4:53
Judea Pearl (UCLA): The Causal Revolution, the ladder of causation, machine learning, and strong AI. 
4:53 PM – 4:58 Q & A
4:58 PM
DISCUSSION
5:15 PM RECEPTION: First Floor Conference Room, Gonda Building

For Hotels near UCLA go to: PDF
For a map of NRB and parking click
here
If you are having problems with registering, send an email with your name and department information to silvaa#mednet.ucla.edu
For questions contact Alcino Silva (silvaa#mednet.ucla.edu)