CEMSE Weekly Updates - April 21, 2026 Tue, Apr 21 2026 Newsletter Upcoming Events Stay informed about the upcoming events and the latest news from CEMSE. Publication Ethics and Authorship - Including the Responsible and Ethical Use of AI in Research Sidney Engelbrecht, Senior Research Compliance Specialist, Research Operations Apr 26, 12:00 - 13:00 B9 R2325 research ethics scientific research AI This talk outlines essential publication ethics and best practices at KAUST, focusing on authorship criteria, researcher responsibilities, dispute resolution, and the ethical use of AI in scholarly writing. Dynamical Systems in Data Science: From Kinetic Closure to Learning Dynamics Dr. Florian Kogelbauer, Senior Research Fellow, Swiss Federal Institute of Technology Zurich (ETH Zurich) Apr 27, 12:00 - 13:00 B2/3 A0215 This talk explores two ways in which ideas from dynamical systems can shape the mathematics of data science. Mathematical Modeling and Analysis of Liquid Crystals: Ericksen-Leslie Model Majed Sofiani, Postdoctoral Research Fellow, Applied Mathematics and Computational Science Apr 27, 14:00 - 15:00 B1 R3426 Ericksen-Leslie Model non-linear partial differential equations Liquid Crystals Navier-Stokes equation This talk I will provide an overview of the celebrated Ericksen-Leslie model for nematic liquid crystals. Disease Nowcasting Using Integrated and Adaptive Statistical Models Yang Xiao, Ph.D. Student, Statistics Apr 28, 10:00 - 12:30 B5 R5220; Zoom Meeting 93296195795 Adaptive modeling Public Health bayesian inference This thesis provides a comprehensive Bayesian nowcasting framework that addresses reporting delays, integrates complementary data sources, and improves real-time estimation of disease activity. Probabilistic Shaping Based Modulation Schemes for Spectral-Efficient VLC systems Amanat Kafizov, Ph.D. Student, Electrical and Computer Engineering Apr 28, 15:00 - 16:30 B1 L3123 Visible light communications visible light communication systems spectral efficiency probabilistic shaping optical wireless communication systems This thesis proposes novel adaptive coded PS-based modulation schemes to improve the spectral efficiency (SE) of visible light communication (VLC) systems. Causal Reasoning in Medical Digital Twins: Methods and Architectures Sakhaa Alsaedi, Ph.D. Student, Computer Science Apr 29, 03:00 - 05:00 B3 R5209 explainable AI reasoning causal representation learning medical digital twins personalized medicine AI AI for healthcare This dissertation develops a principled computational framework for causal reasoning in Medical digital twins (MDT) systems, moving beyond correlation-driven approaches toward explainable and biologically grounded decision support. On Cross Validation, Log Gaussian Cox Process and Variational Bayes Hans Montcho, Ph.D. Student, Statistics Apr 29, 10:00 - 12:00 B2 R5220; Zoom Meeting 99219689653 Bayesian computational technique Bayesian computational statistics latent Gaussian models Point patterns spital point patterns This dissertation advances Bayesian computation by developing a cross validation approach to assess LGCPs defined on Euclidean, manifolds or network domains and improving skewed posterior approximations for LGMs. A Unified and Computationally Efficient Non-Gaussian Statistical Modeling Framework Xiaotian Jin, Ph.D. Student, Statistics Apr 29, 15:00 - 16:30 B4 R5209 latent Gaussian models spatio-temporal statistics stochastic algorithms multivariate statistics This thesis develops a linear latent non-Gaussian modeling framework that extends latent Gaussian models to accommodate skewness, heavy tails, and extremes while preserving computational tractability, along with its implementation in the R package ngme2. Reinforcement Learning and Optimization in Large Action Spaces under Limited Feedback Fares Fourati, Ph.D. Student, Electrical and Computer Engineering Apr 29, 15:00 - 16:45 B2 R5209 Reinforcement Learning machine learning combinatorial multi-armed bandits large action spaces limited feedback efficient exploration submodular optimization black-box optimization global optimization This dissertation develops theoretical foundations and scalable algorithms for reinforcement learning and optimization in large decision spaces under limited feedback. Event Status: Cancelled | Robust and Fuzzy Methods for High-Dimensional Time Series Clustering and Forecasting Ziling Ma, Ph.D. Student, Statistics Apr 30, 12:00 - 13:00 B9 R2325 These talks introduce several robust methods for clustering and forecasting multivariate time series data. Towards an Early Warning System for Climate-Sensitive Infectious Diseases: Spatio-Temporal Modeling and Deep Learning for Dengue Forecasting in Brazil Xiang Chen, Ph.D. Student, Statistics Apr 30, 13:00 - 16:00 B5 R5209 spatio-temporal modeling geospatial statistics infectious disease explainable AI Public Health climate data deep learning computational predictions This dissertation develops integrated spatio-temporal forecasting approaches that combine deep learning, climate data, spatial dependencies, and human mobility to improve dengue prediction and support early-warning systems in Brazil. Cavity-Engineered VCSELs with Integrated Photodetectors for Optical Entropy and Security Hang Lu, Ph.D. Candidate, Electrical and Computer Engineering Apr 30, 15:30 - 17:00 B2 R5220; Zoom Meeting 94108463874 semiconductor lasers VCSEL optical entropy randomness source Secure communication This thesis establishes cavity-engineered VCSELs with integrated photodetectors as a unified and scalable photonic platform for optical entropy generation and security.
