SOCR Events JMM BigData Jan2014
From Socr
(→Organizer) |
|||
Line 22: | Line 22: | ||
|+ | |+ | ||
|- | |- | ||
- | | 1:00-1:20 || Ivo D. Dinov || [http://www.ams.org/amsmtgs/2160_abstracts/1096-68-27.pdf Big Data Challenges in Neuroimaging, Informatics and Genomics Computing (1096-68-27)] | + | | '''Time ''' | '''Presenter ''' | '''Title ''' | |
+ | |- | ||
+ | | 1:00-1:20 || Ivo D. Dinov [http://wiki.stat.ucla.edu/socr/uploads/c/c1/Dinov_BigDataChallenges_AMS_JMM_2014.pdf PDF Slides] || [http://www.ams.org/amsmtgs/2160_abstracts/1096-68-27.pdf Big Data Challenges in Neuroimaging, Informatics and Genomics Computing (1096-68-27)] | ||
|- | |- | ||
| 1:30-1:50 || Elias Bareinboim || [http://www.ams.org/amsmtgs/2160_abstracts/1096-62-2468.pdf Inference with Emphasis on Transportability and External Validity (1096-62-2468)] | | 1:30-1:50 || Elias Bareinboim || [http://www.ams.org/amsmtgs/2160_abstracts/1096-62-2468.pdf Inference with Emphasis on Transportability and External Validity (1096-62-2468)] |
Revision as of 15:38, 15 January 2014
Contents |
SOCR News & Events: 2014 JMM/AMS Special Session on Big-Data: Mathematical and Statistical Modeling, Tools, Services, and Training
Overview
The volume and diversity of biomedical data is exponentially increasing with Peta bytes of imaging and genetics data acquired annually. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Scientists demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data management, data interrogation, evidence-based biomedical inference, and reproducibility of findings. Novel mathematical algorithms, statistical analyses and computational tools are necessary to cope with this avalanche of data and hardware devices.
Organizer
- Ivo Dinov, UMich/UMSN/SOCR, and UCLA/Statistics.
Session Logistics
- Date/Time: Thursday January 16, 2014, 1:00-3:50 PM
- Venue: Baltimore Convention Center, 1 W Pratt St Baltimore, MD 21201, (410) 649-7000
- Room: Room 317, Baltimore Convention Center
- Conference: 2014 JMM Meeting
- Equipment: Computer projector and screen. No computer/laptop, blackboard or whiteboard in session room
- Paper Abstract Submission - choose session SS 18A (due date: Sept 01, 2013)
Speakers
Presenter | Title | | ||
1:00-1:20 | Ivo D. Dinov PDF Slides | Big Data Challenges in Neuroimaging, Informatics and Genomics Computing (1096-68-27) |
1:30-1:50 | Elias Bareinboim | Inference with Emphasis on Transportability and External Validity (1096-62-2468) |
2:00-2:20 | Nguyet T Nguyen | Hidden Markov Model for High Frequency Data (1096-62-2312) |
2:30-2:50 | Jeff Randell Knisley | Consensus Spectral Techniques and Machine Learning (1096-62-1122) |
3:00-3:20 | Catherine A Bliss | Covariance Matrix Adaptation Evolution Strategy for Link Prediction in Dynamic Social Networks (1096-65-1009) |
3:30-3:50 | John Ensley | My Life as a Tweet Word (1096-68-2249) |
Resources
Translate this page: