SOCR News CMStatistics2022 - Revision history

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Dinov: Created page with "== SOCR News & Events: ''Quantum Mechanics Uncertainty, Data Science Inference, and AI in Complex Time (Kime)'' == Image:Spacekime_TCIU_Trivial_PolarCylind..."

2022-04-19T16:57:40Z

Created page with "== SOCR News & Events: ''Quantum Mechanics Uncertainty, Data Science Inference, and AI in Complex Time (Kime)'' == Image:Spacekime_TCIU_Trivial_PolarCylind..."

New page

== [[SOCR_News | SOCR News & Events]]: ''Quantum Mechanics Uncertainty, Data Science Inference, and AI in Complex Time (Kime)'' ==

[[Image:Spacekime_TCIU_Trivial_PolarCylinder_WaveEqu_Phase.png|150px|thumbnail|right| [https://www.socr.umich.edu/TCIU/ Spacekime/TCIU Project] ]]

== Presenters==
: [https://umich.edu/~dinov Ivo Dinov] ([https://www.umich.edu University of Michigan], [https://www.socr.umich.edu SOCR], [https://midas.umich.edu MIDAS]), [http://www.socr.umich.edu/people/SOCR_Personnel_Yueyang.html Yueyang Shen] (University of Michigan), and [http://www.socr.umich.edu/people/Milen_Velev.html Milen V. Velev] (BTU).

:: Dr. Dinov is a professor of Health Behavior and Biological Sciences and Computational Medicine and Bioinformatics at the University of Michigan. He is a member of the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM) and a core member of the University of Michigan Comprehensive Cancer Center. Dr. Dinov serves as Director of the Statistics Online Computational Resource, Co-Director of the multi-institutional Probability Distributome Project, and Associate Director of the Michigan Institute for Data Science (MIDAS). He is a member of the American Statistical Association (ASA), International Association for Statistical Education (IASE), American Mathematical Society (AMS), American Association for the Advancement of Science (AAAS), American Physical Society (APS), and an Elected Member of the International Statistical Institute (ISI).

==Session Logistics==
* '''Date/Time''': Thursday, March 17, 2022, 3:00 PM – 5:36 PM, [https://www.timeanddate.com/time/zones/gmt GMT]
* '''Talk Title''': ''Quantum Mechanics Uncertainty, Data Science Inference, and AI in Complex Time (Kime)''
* '''Registration''': [http://www.cmstatistics.org/CMStatistics2022/index.php Registration Link]
* '''Conference''': [http://www.cmstatistics.org/CMStatistics2022/index.php CMStatistics 2022 meeting website]
* '''Session''': Statistical Neuroimaging
* '''Zoom''': TBD
* '''Talk Format''': Hybrid/In-Person/Online presentation; specific time:TBD

== Abstract==
: This talk will translate quantum mechanical uncertainty principles to address data science challenges by using complex time (kime) to lift the classical 4D spacetime into the 5D spacekime manifold. We extend the laws of velocity, momentum, Lorentz transformations, and 4D solutions of Einstein’s equations to their corresponding counterparts in 5D spacekime. Direct AI applications include translation of classical random sampling in spacetime to spacekime phase-uncertainty and a Bayesian formulation of spacekime analytics. We will show examples translating longitudinal data to kimesurfaces using neuroimaging and macroeconomics data.

'''Slidedeck''': TBD.

==Background==
* [[SOCR_News | SOCR News & Events]]
* [https://www.socr.umich.edu/html/SOCR_UserGoogleMap.html SOCR Global Users]
* [https://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]

==References==
* Dinov, ID and Velev, MV (2021) [https://doi.org/10.1515/9783110697827 Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics], De Gruyter (STEM Series), Berlin/Boston, ISBN 9783110697803 / 3110697807, DOI 10.1515/9783110697827.
* Wang, Y, Shen Y, Deng, D, Dinov, ID. (2022) [https://doi.org/10.1016/j.padiff.2022.100280 Determinism, Well-posedness, and Applications of the Ultrahyperbolic Wave Equation in Spacekime], Journal of Partial Differential Equations in Applied Mathematics, DOI: 10.1016/j.padiff.2022.100280, in press.
* Zhang, R, Zhang, Y, Liu, Y, Guo, Y, Shen, Y, Deng, D, Qiu, Y, Dinov, ID. (2022) [https://doi.org/10.1007/s00521-021-06789-8 Kimesurface Representation and Tensor Linear Modeling of Longitudinal Data], Neural Computing and Applications Journal, DOI: 10.1007/s00521-021-06789-8.
* [https://www.socr.umich.edu/spacekime/ Spacekime website]
* [https://tciu.predictive.space/ Time-Complexity and Inferential Uncertainty (TCIU)]

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← Older revision		Revision as of 18:36, 8 December 2022
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−	'''Slidedeck'''~~: TBD.~~	+	[https://wiki.socr.umich.edu/images/d/dd/Dinov_Spacekime_CMStatistics_Dec2022.pdf '''Slidedeck''']

	==Background==		==Background==

@@ Line 20: / Line 20: @@
 * '''Session''': [http://www.cmstatistics.org/CMStatistics2022/organized.php EO420: Advances in statistical neuroimaging and spatio-temporal modeling]
 * '''Zoom''': [https://us04web.zoom.us/j/74773947823 ZM link]
-* '''Talk Format''':  Hybrid (In-Person & Online) Presentation; Specific Time:TBD
+* '''Talk Format''':  Hybrid (In-Person & Online) Presentation.
 == Abstract==

@@ Line 13: / Line 13: @@
 ==Session Logistics==
 * '''Date/Time''': King's College London, 17-19 December 2022, [https://www.timeanddate.com/time/zones/gmt GMT time-zone]
 * '''Talk Title''': ''Quantum Mechanics Uncertainty, Data Science Inference, and AI in Complex Time (Kime)''
@@ Line 18: / Line 19: @@
 * '''Conference''': [http://www.cmstatistics.org/CMStatistics2022/index.php CMStatistics 2022 meeting website]
 * '''Session''': [http://www.cmstatistics.org/CMStatistics2022/organized.php EO420: Advances in statistical neuroimaging and spatio-temporal modeling]
-* '''Zoom''': TBD
+* '''Zoom''': [https://us04web.zoom.us/j/74773947823 ZM link]
 * '''Talk Format''':  Hybrid (In-Person & Online) Presentation; Specific Time:TBD

← Older revision		Revision as of 20:06, 6 September 2022
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	:: Dr. Dinov is a professor of Health Behavior and Biological Sciences and Computational Medicine and Bioinformatics at the University of Michigan. He is a member of the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM) and a core member of the University of Michigan Comprehensive Cancer Center. Dr. Dinov serves as Director of the Statistics Online Computational Resource, Co-Director of the multi-institutional Probability Distributome Project, and Associate Director of the Michigan Institute for Data Science (MIDAS). He is a member of the American Statistical Association (ASA), International Association for Statistical Education (IASE), American Mathematical Society (AMS), American Association for the Advancement of Science (AAAS), American Physical Society (APS), and an Elected Member of the International Statistical Institute (ISI).		:: Dr. Dinov is a professor of Health Behavior and Biological Sciences and Computational Medicine and Bioinformatics at the University of Michigan. He is a member of the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM) and a core member of the University of Michigan Comprehensive Cancer Center. Dr. Dinov serves as Director of the Statistics Online Computational Resource, Co-Director of the multi-institutional Probability Distributome Project, and Associate Director of the Michigan Institute for Data Science (MIDAS). He is a member of the American Statistical Association (ASA), International Association for Statistical Education (IASE), American Mathematical Society (AMS), American Association for the Advancement of Science (AAAS), American Physical Society (APS), and an Elected Member of the International Statistical Institute (ISI).
		+
		+	: [https://socr.umich.edu/people/SOCR_Personnel_Yueyang.html Yueyang Shen (Michigan)]
		+
		+	: [https://socr.umich.edu/people/Milen_Velev.html Milen V. Velev (BTU)]

	==Session Logistics==		==Session Logistics==

← Older revision		Revision as of 20:04, 6 September 2022
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	== Abstract==		== Abstract==
−	: ~~This talk will translate quantum mechanical uncertainty principles to address data science challenges by~~ using complex time (kime) to lift the classical 4D ~~spacetime~~ into the 5D ~~spacekime~~ manifold. We extend the laws of velocity, momentum, Lorentz transformations, and 4D solutions of Einstein’s equations to their corresponding counterparts in 5D spacekime. Direct AI applications include ~~translation of~~ classical random sampling in spacetime to spacekime phase-uncertainty and a Bayesian formulation of spacekime analytics. We will show examples ~~translating~~ longitudinal data to ~~kimesurfaces using neuroimaging~~ and ~~macroeconomics data~~.	+	: By using complex time (kime) to lift the classical 4D space-time into the 5D space-kime manifold, this talk will demonstrate translating quantum mechanics principles to address data science and predictive analytics challenges. We extend the physical laws of velocity, momentum, Lorentz transformations, and 4D solutions of Einstein’s equations to their corresponding counterparts in 5D spacekime. Direct AI applications include transforming classical random sampling in spacetime to spacekime phase-uncertainty and a Bayesian formulation of spacekime analytics. Using neuroimaging and macroeconomics data, we will show examples mapping longitudinal data (e.g., time-series) to 2D manifolds (e.g., kime-surfaces) and discuss the subsequent modeling, inference, and AI based on space-kime representations.
		+

@@ Line 4: / Line 4: @@
 == Presenters==
-: [https://umich.edu/~dinov Ivo Dinov] ([https://www.umich.edu University of Michigan], [https://www.socr.umich.edu SOCR], [https://midas.umich.edu MIDAS]), [http://www.socr.umich.edu/people/SOCR_Personnel_Yueyang.html Yueyang Shen] (University of Michigan), and [http://www.socr.umich.edu/people/Milen_Velev.html Milen V. Velev] (BTU).
+: [https://umich.edu/~dinov Ivo Dinov] ([https://www.umich.edu University of Michigan], [https://www.socr.umich.edu SOCR], [https://midas.umich.edu MIDAS]).
 :: Dr. Dinov is a professor of Health Behavior and Biological Sciences and Computational Medicine and Bioinformatics at the University of Michigan. He is a member of the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM) and a core member of the University of Michigan Comprehensive Cancer Center. Dr. Dinov serves as Director of the Statistics Online Computational Resource, Co-Director of the multi-institutional Probability Distributome Project, and Associate Director of the Michigan Institute for Data Science (MIDAS). He is a member of the American Statistical Association (ASA), International Association for Statistical Education (IASE), American Mathematical Society (AMS), American Association for the Advancement of Science (AAAS), American Physical Society (APS), and an Elected Member of the International Statistical Institute (ISI).