About

Our team has designed and published specific Markov Model-based CWW inference engines for several decision categories: an inference engine for identifying pirate boat activity, an engine for assessing the influence of an organization’s operations on the panic and public mood, and a system for assessing the influence of government activities on the pandemic spread. These earlier machines will be used as the basis for developing a generic CWW engine, along with a user interface that enables the client to augment the generic engine for specific decision types

Implicify LLC has engaged experts on COVID-19 and Aftershock management using Fuzzy Logic.

This team has extensively published on applications of Fuzzy Logic to disasters and public health issues and events. Our recent publications on Fuzzy Logic include the book “Fifty Years of Fuzzy Logic and its Applications,” Best Paper awardee of the PATTERNS conference, and the NATO Science for Peace and Security Program paper “Fuzzy Logic And Data Mining In Disaster Mitigation,” which addresses disasters of the magnitude and surprise level like the present COVID-19 and proposes Fuzzy Logic-based inference tools to deal therewith.

Abraham Kandel is a Distinguished Emeritus Professor in Computer Science and Engineering at the University of South Florida in Tampa, Florida Academy of Sciences Medalist of the Year, and the Founding Executive Director of the National Institute for Systems Test and Productivity Dr. Kandel has published over 900 refereed research papers and 52 books, mainly in the areas of Applied Fuzzy Logic, Uncertainty Management, and Artificial Intelligence (AI). Among his many awards are The IEEE Pioneer Award (2012) and The Fay and Lotfi Zadeh Lifetime Achievement (2016).

Dan Tamir is an Associate Professor of Computer Science at Texas State University and a renowned expert on Fuzzy Logic for Disaster Mitigation. Dr. Tamir has extensively published on Fuzzy Logic, computing with words, information theory, combinatorial optimization, computer vision, and human-computer interaction.

Contact

Implicify, LLC
1300 E. Riverside Dr., Ste. C203,
Austin, TX 78741
dant11002@gmail.com
(512) 739 – 9277