CEMSE Weekly Updates - February 24, 2026 Tue, Feb 24 2026 Newsletter Upcoming Events Stay informed about the upcoming events and the latest news from CEMSE. From Edge to Intelligence: Light-Driven Synaptic Devices for Adaptive Healthcare and Vision Systems Dayanand Kumar, Postdoctoral Research Fellow, Electrical and Computer Engineering Mar 1, 12:00 - 13:00 B9 L2 R2325 optoelectronic devices light-driven synaptic devices neuromorphic electronics edge computing This talk presents a flexible, back-end-of-line compatible optoelectronic synapse developed for neuromorphic edge computing. From Prompts to Production: The Systems Agenda for Agentic AI Marco Canini, Professor, Computer Science Mar 2, 12:00 - 13:00 B9 L2 R2325 AI observability reproducibility Computer Information Systems In this talk, I will discuss our recent work on benchmarking, evaluation, and deployment of multi-agent LLM systems, and use it to outline a broader research agenda for agentic AI as a systems discipline - where progress depends not only on better models, but on principled infrastructure for observability, reproducibility, safe experimentation, and scalable execution. Bayesian Inference for Partially Observed Continuous-Time Processes Amin Wu, Ph.D. Student, Statistics Mar 3, 10:00 - 12:00 B5 L5 R5220 McKean-Vlasov SDEs bayesian inference markov chains Monte Carlo This thesis develops Bayesian inference methods for partially observed stochastic differential equations (SDEs) with unknown parameters, focusing on the stochastic Volterra equation (SVE), non-synchronous diffusions, and McKean-Vlasov SDEs. Employing Euler-Maruyama discretization. Structure Preserving Methods for Schrodinger Type of Equations Theodoros Katsaounis, Professor, Department of Mathematics and Applied Mathematics, University of Crete (UoC) Mar 3, 14:30 - 15:30 B1 L3 R3119 Schrödinger equation cosmology waves This talk presents a class of structure preserving methods for Schrodinger type of equations with applications in the generation of rogue waves and cosmology. Assessing Network Middlebox Impact on End-to-End Protocol Behavior via a Distributed and Reprogrammable Framework Ilies Benhabbour, Ph.D. Student, Computer Science Mar 4, 13:00 - 16:00 B5 L5 R5220 cybersecurity Cryptography distributed computing This dissertation focuses on the detection and verification of network middleboxes thanks to the creation of a new distributed framework called NoPASARAN. Approximation and Optimization for Neural Networks Gerrit Welper, Assistant Professor, Mathematics, University of Central Florida (UCF) Mar 4, 16:00 - 17:00 Zoom Meeting 95807131415 Neural Networks optimization deep neural networks Finite element methods In this talk, we consider new connections between the approximation and optimization of neural networks. Instead of relying on excessive over-parametrization to achieve zero training loss, we identify good minima by comparison with established approximation bounds. Remote Sensing and Agroinformatics Insights in Saudi Arabia Using Machine Learning Ting Li, Postdoctoral Research Fellow, Environmental Science and Engineering Mar 5, 12:00 - 13:00 B9 L2 R2325 remote sensing machine learning sustainable agricultural agricultural productivity This talk explores how machine learning and high-resolution satellite remote sensing are being used to transform vast amounts of raw data into actionable agroinformatics at a national scale, providing the precision needed to manage these vital resources sustainably. Simulation of Metasurfaces Described by Generalized Sheet Transition Conditions Using Integral Equations Sebastian Celis Sierra, Postdoctoral Research Fellow, Electrical and Computer Engineering Mar 8, 00:00 - 01:00 B9 L2 R2325 Metasurfaces computational electromagnetics Computer simulations numerical integration This seminar outlines the development of computationally efficient integral equation solvers that simulate complex multiscale metasurfaces by modeling their physical geometries as infinitesimally thin sheets governed by generalized sheet transition conditions, thereby avoiding the need for full volumetric discretization.
