Connectionists: CfP for the invited lecture of Dr. I. Pitas on 'Decentralized Machine Learning for Natural Disaster Management Applications' at U Connecticut, on June 11th, 2026 @ 12:00pm EDT

[Ioanna Koroni]

Dear AI scientists and students,

University of Connecticut hosts the attached upcoming exciting lecture 
by Dr. Ioannis Pitas /Chair of the International AI Doctoral Academy 
(//AIDA/ <https://www.i-aida.org/>/) Principal Researcher at Aristotle 
University of Thessaloniki (AUTH) and CERTH/ITI Greece./ You are 
welcomed to attend.

When & Where: June 11th, 2026 @ 12:00pm EDT, IPB Room 203, University of 
Connecticut, Storrs, CT, USA

Virtual Zoom link: https://authgr.zoom.us/j/92451144378

*Decentralized Machine Learning for Natural Disaster Management 
Applications*

*Abstract:*

This lecture overviews decentralized and distributed DNN architectures 
and their implementation in cloud/edge environments. Big data analysis 
can be greatly facilitated if decentralized/distributed DNN 
architectures are employed that interact with each other for DNN 
training and/or inference using the human Teacher-Student education 
paradigm. A novel Learning-by-Education Node Community (LENC) framework 
is presented that facilitates communication and knowledge exchange among 
diverse Deep Neural Networks (DNN) agents, undertaking the role of a 
student or teacher DNN by offering or absorbing knowledge respectively. 
The framework enables efficient and effective knowledge transfer among 
participating DNN agents while enhancing their learning capabilities and 
fostering their collaboration among diverse networks. The proposed 
framework addresses the challenges of handling diverse training data 
distributions and the limitations of individual DNN agent learning 
abilities. The LENC framework ensures the exploitation of the best 
available teacher knowledge upon learning a new task and protects the 
DNN agents from catastrophic forgetting. The experiments demonstrate the 
LENC framework functionalities on multiple teacher-student learning 
techniques and their integration with lifelong learning. Our experiments 
manifest the LEMA framework’s ability to maximize the accuracy of all 
participating DNN agents in classification tasks by leveraging the 
collaborative knowledge of the framework. A LENC framework 
implementation in cloud/edge environments is also overviewed.

Applications are presented in big visual data analysis tasks for Natural 
Disaster Management (NDM), focusing on flood and wildfire monitoring, 
combatting and management. As many players enter into NDM, from first 
responders to civil authorities, NDM needs big data analysis that is 
typically decentralized and DDN-based and resides in the entire 
edge-to-cloud computing continuum.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20260609/3cfdf21b/attachment.html>