Kime-Phase Tomography Presentations at APS/GPS 2026
In March 2026, at the American Physical Society (APS) 2026 Global Physics Summit, SOCR is organizing: The updated Spacekime website also includes a brief, 7-minute, spacekime podcast (audio) and a short, 5-minute, video describing complex-time representation, kime-phase tomography (KPT), and spacekime gravitational field equations.
Spacekime/TCIU AI Tutor & Virtual Assistant
In May 2025, SOCR released a first-generation Spacekime/TCIU AI Tutor & Virtual Assistant, which provides an easy introductory question-and-response interface for learning about complex-time (kime) representation, interpretation of observability, time complexity, inferential uncertainty, and spacekime analytics. The Spacekime/TCIU AI Tutor & Virtual Assistant uses pretrained generative AI models and large language models tailored on TCIU…
Simple Spacekime Representation Webapp
In April 2025, SOCR released a very simple Webapp showing Time-series to Kime-Surfaces Mapping. The app is an oversimplification of the intricate process of transforming (observed or simulated) repeated measurement longitudinal processes into mathematically-rich computable objects (kimesurfaces). At the same time, the app’s functionality supports active learning and provides intuition about alternative analytic, numerical, discrete,…
APS GDS Complex-Time (Kime) Webinar
In April 2025, the APS GDS Virtual Tutorial Series included a webinar on Complex-time (kime) Representation, Statistical Inference, and AI prediction. The materials, including end-to-end electronic R markdown notebook, datasets, and video, are available on the SOCR Spacekime website and the APS GDS GitHub repository.
January 2025 Spacekime-Explained Podcast
Check this 14-min audio podcast explaining the mathematical foundations of complex-time representation, computational spacekime analytics, and mind-boggling applications.
Foundational Generative Artificial Intelligence Models (GAIMs)
Expanding on DSPA Chapter 14 (Deep Learning) and the GAIM GitHub website, this newly released DSPA2 appendix 11 demonstrates the application of pre-trained large language models, such as foundational generative artificial intelligence models (GAIMs). Using LM Studio, an integrated development environment for GAIM applications, this DSPA appendix shows parallels between RStudio, as an IDE for…
Lecture on AI and Spacekime Analytics in Health Research and Biomedical Inference
At the 2024 International conference on High-Dimensional Data Analysis Conference (HDDA-13) in Singapore (August 28-30, 2024), Ivo Dinov is organizing a special session on Data Science, Artificial Intelligence, and High-Dimensional Spatiotemporal Dynamics, and presenting a lecture on AI and Spacekime Analytics in Health Research and Biomedical Inference.
2024 OLLI Lecture on Artificial Intelligence in Health
On April 25, 2024, Ivo Dinov is giving a lecture at the 2024 OLLI Lecture Series on Artificial Intelligence (AI) on the topic of AI in Health – Research Promises, Education Perils and Clinical Practice Impact, Towsley Auditorium, Washtenaw Community College.
Spacekime Analytics Tutorial/Talk at AmStat SMI 2024 Conference
A short course “Complex-Time Representation of Spatiotemporal Processes and Spacekime Analytics” and a lecture on “Statistical Foundations of Invariance in Deep Network Learning” will be presented at the 2024 annual Statistical Methods in Imaging (SMI) Meeting of the American Statistical Association (AmStat). The conference takes place May 29-31, 2024 at the JW Marriott Indianapolis, Indianapolis,…
Spacekime Explained by generative AI
Can AI explain complex time? Here is a generative artificial intelligence model (GAIM) description of spacekime, which is driven by the following human-provided prompt “explain the notion of complex time and spacekime analytics.” The GAIM description was generated automatically on July 01, 2023 via the OpenAI application programming interface (API). <start_of_GAIM_output/> The notion of complex…
Something went wrong. Please refresh the page and/or try again.
A new Spacekime Article Explores the Mathematical Foundations of Complex Time Representation
In April 2023, the SOCR team released a new arXiv manuscript detailing the relations between various integral transformations, Meijer-G functions, and kime-representations of discrete signals and continuous functions. This study expands other SOCR reports that utilize mathematical-physics techniques, statistical computing, artificial intelligence, and data science methods to model, interpret, analyze, and visualize high-dimensional time-varying observations.…
Yueyang Shen Presents A Spacekime Laplace Transform Framework at APS April 2023 Meeting
Yueyang Shen (University of Michigan, SOCR, BIDS-TP) is presenting at the April 2023 meeting of the American Physical Society (APS). His talk will cover a new numerical framework for approximating the forward and inverse Laplace transforms (LT-ILT), appropriate parameter estimations, and signal approximations. This work illustrates an idealized analysis relaxing the data matrix construction assumptions…
Spacekime Talk at 2022 CMStatistics Conference
A talk on Quantum Mechanics Uncertainty, Data Science Inference, and AI in Complex Time (Kime) will be presented on Saturday, December 17, 2022, 18:05 – 19:20 GMT (13:05-14:20 US ET) at the 2022 CMStatistics Conference, King’s College London.
ASA SII Section Talk – Spacekime Analytics (10/25/22, 1 PM US ET)
This talk will introduce complex-time (kime) representation of longitudinal data and the induced space-kime analytics. This approach translates quantum mechanics concepts into data science and lifts the classical 4D spacetime problems into a 5D spacekime manifold. Direct AI and statistical inference applications include translation of classical random sampling in spacetime to spacekime phase-uncertainty and a…
2023 JMM/AMS Special Session on Complex Data
This 2023 JMM/AMS Invited Special Session will include talks on new mathematical, computational, and statistical approaches for tensor-based representation, modeling and inference with direct applications to high-dimensional and longitudinal data. Presentations will cover coupled tensor-tensor completion strategies, complex time (kime) representation and tensor linear modeling of kimesurfaces, and current advances in tensor computing. Various data…
Tensor-Modeling and Spacekime-Analytics Training Course in March 2022
On March 13, 2022, there will be a day-long short course Longitudinal Data Tensor-Linear Modeling and Space-kime Analytics. This training course, part of the March 2022 APS Meeting, will present the current state-of-the-art approaches for tensor-based linear modeling and spacekime analytics. Instructors will present a generalized framework for modeling and prediction of scalar, matrix, or…
Spacekime Textbook Availability
The electronic and print versions of the newly published Data Science Time Complexity, Inferential Uncertainty, and Spacekime Analytics textbook are available globally for viewing, downloading, checking-out, and purchasing at a number of national, university, and community libraries, bookshops, and vendors.
Spacekime Textbook Published
In December 2021, De Gruyter STEM published the Data Science Time Complexity, Inferential Uncertainty, and Spacekime Analytics textbook (Ebook/EPUB and Hardcover print editions).
Development of the Spacekime Model
Michigan Medicine DCMB News-brief on the Development of the Spacekime Model.
APS Presentation on Data Science, Time Complexity, and Spacekime Analytics (April 10, 2021)
Ivo Dinov is presenting Data Science, Time Complexity, and Spacekime Analytics, at the 2021 Meeting of the American Physical Society (APS) Ohio-Region Section. Due to the SARS-CoV-2 pandemic, this is a remote (distance) event. More details, registration, logistics and ZOOM links are available on the SOCR News site.
Something went wrong. Please refresh the page and/or try again.
Follow the Spacekime Blog
You can choose to subscribe to automatically receive new spacekime blog posts emailed to your inbox.
Longitudinal data and time-series signals are transformed to spacekime surfaces with richer geometric and topological structure.
Spacekime Community Site 