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2020-11-10T15:32:34Z

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2020-10-10T22:28:28Z

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== [[SOCR_News | SOCR News & Events]]: Computational Neuroscience, Time Complexity, and Spacekime Analytics ==

[[Image:SOCR_UMich_2020a.png|150px|thumbnail|right| [https://socr.umich.edu SOCR Resource] ]]
The [https://midas.umich.edu/2020-symposium/ 2020 UM Data Science Annual Symposium] will take place virtually.

==Logistics==
* [https://midas.umich.edu/2020-symposium/ Program]
* '''Dates/Times''': Tuesday and Wednesday November 10-11, 2020
* '''Place''': Zoom Event TBD ...
* '''Title''': ''Computational Neuroscience, Time Complexity, and Spacekime Analytics''
* '''Presenter''': [http://umich.edu/~dinov Ivo Dinov], joint work with [http://socr.umich.edu/people/Milen_Velev.html Milen V. Velev] (Burgas University)
[[Image:Spacekime_TCIU_Trivial_PolarCylinder_WaveEqu_Phase.png|150px|thumbnail|right| [https://www.socr.umich.edu/TCIU/ Spacekime/TCIU Project] ]]
* '''Abstract''': The proliferation of digital information in all human experiences presents difficult challenges and offers unique opportunities of managing, modeling, analyzing, interpreting, and visualizing heterogeneous data. There is a substantial need to develop, validate, productize, and support novel mathematical techniques, advanced statistical computing algorithms, transdisciplinary tools, and effective artificial intelligence apps.
: Spacekime analytics is a new technique for modeling high-dimensional longitudinal data, such as functional magnetic resonance imaging (fMRI). This approach relies on extending the notions of time, events, particles, and wavefunctions to complex-time (kime), complex-events (kevents), data and inference-functions, respectively. This talk will illustrate how the kime-magnitude (longitudinal time order) and kime-direction (phase) affect the subsequent predictive analytics and the induced scientific inference. The mathematical foundation of spacekime calculus reveals various statistical implications including inferential uncertainty and a Bayesian formulation of spacekime analytics. Complexifying time allows the lifting of all commonly observed processes from the classical 4D Minkowski spacetime to a 5D spacetime manifold, where a number of interesting mathematical problems arise.
: Spacekime analytics transforms time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). This process uncovers some of the intricate structure in high-dimensional data that may be intractable in the classical space-time representation of the data. In addition, the spacekime representation facilitates the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. Direct neuroscience science applications of spacekime analytics will be demonstrated using simulated data and clinical observations (e.g., UK Biobank).
: Joint work with Milen V. Velev (Burgas University, Bulgaria).

* '''Slidedeck''': [https://socr.umich.edu/docs/uploads/2020/Dinov_Spacekime_MIDAS_Nov_2020.pdf Presentation Slides]

==Background==
* [[SOCR_News | SOCR News & Events]]
* [http://www.socr.umich.edu/html/SOCR_UserGoogleMap.html SOCR Global Users]
* [http://socr.umich.edu/html/Navigators.html SOCR Navigators]
* [[SOCR_Data | SOCR Datasets and Challenging Case-studies]]
* [[SOCR_Books|Electronic Textbooks]]:
** [[EBook| Probability and Statistics EBook]]
** [[SMHS | Scientific Methods for Health Sciences]]
** [https://dspa.predictive.space Data Science and Predictive Analytics]

* [https://www.socr.umich.edu/spacekime/ Spacekime website]
* [https://tciu.predictive.space/ Time-Complexity and Inferential Uncertainty (TCIU)]

<hr>

==References==
* This work is sponsored in part by NIH Grants [http://projectreporter.nih.gov/project_info_details.cfm?aid=8975330&icde=25689118 P30 DK089503], [http://projectreporter.nih.gov/project_info_description.cfm?aid=8821268&icde=22205726 P20 NR015331], [https://projectreporter.nih.gov/project_info_description.cfm?aid=9816658 R01CA233487], and [https://projectreporter.nih.gov/project_info_details.cfm?aid=9842024 R01MH121079], as well as, NSF Grants [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1916425 1916425], [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1734853 1734853] and [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1636840 1636840].
* Dinov, ID and Velev, MV (2021) [https://www.degruyter.com/view/title/576646 Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics], De Gruyter (STEM Series), Berlin/Boston, ISBN 9783110697803 / 3110697807.
* SOCR Home page: https://www.socr.umich.edu

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@@ Line 7: / Line 7: @@
 * [https://midas.umich.edu/2020-symposium/ Program]
 * '''Dates/Times''': Tuesday and Wednesday November 10-11, 2020
-* '''Place''':  Zoom Event TBD ...
+* '''Place''':  [https://umich.zoom.us/j/91423370825 Zoom Event]
 * '''Title''':  ''Computational Neuroscience, Time Complexity, and Spacekime Analytics''
 * '''Presenter''':  [http://umich.edu/~dinov Ivo Dinov], joint work with [http://socr.umich.edu/people/Milen_Velev.html Milen V. Velev] (Burgas University)

SOCR News MIDAS Symposium 2020 - Revision history

Dinov: /* Logistics */

Dinov: Created page with "== SOCR News & Events: Computational Neuroscience, Time Complexity, and Spacekime Analytics == Image:SOCR_UMich_2020a.png|150px|thumbnail|right| [https://so..."