CEMSE Weekly Updates - October 7, 2025

Stay informed about the upcoming events and the latest news from CEMSE.

Registration is open for One-on-One Statistical Consulting for KAUST Researchers, register before October 12, 2025.

Don’t miss the KAUST 2025 Workshop on Statistics — submit your ePoster information by October 26 and register to join the event in person or virtually.

Visit the events pages for more information.

 

Upcoming Events

Phase-Change Memory for In-Memory Computing

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B9, L2, R2325

This talk, structured as a tutorial, will elucidate the core principles of In-memory computing (IMC), showing how the physical properties and inherent organization of memory devices can help overcome the limitations of conventional data processing architectures.
KAUST-CS-Seminar-Fumin-Zhang-Bio-Inspired-consensus-Enabled-by-Distributed-Active-Perception

Bio-Inspired Consensus Enabledby Distributed Active Perception

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Auditorium (between Buildings 4 and 5), Level 0, Room 0215

Consensus is a fundamental requirement for coordination and cooperation among a swarm of intelligent agents. In environments with difficulty for localization and communication, achieving swarm level consensus is a challenging task. We propose a layered approach to achieve signal propagation over large swarms through active perception. Biological evidence from fish swarms has shown that distributed active perception is used by animals to allow fast response to stimulations when only a few members are excited.

KAUST Robotics Bay Inauguration

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B5 L2 R2800

Join us for the Robotics Bay inauguration at KAUST.

Learning-Based Observer Design for Nonlinear Systems with Convergence Guarantees

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B3 L5 R5220

This thesis advances nonlinear estimation by proposing learning-based nonlinear observers with convergence guarantees. The proposed approaches overcome the limitations of the existing methods by being applicable to a wide range of nonlinear systems while providing global convergence guarantees. Furthermore, the developed observers are robust to disturbances, sensor delay, and measurement noise.

Bias-Reduced Estimation of Structural Equations Models

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B9 L2 R2325

This talk demonstrates that the reduced-bias M-estimation (RBM) framework is a computationally efficient and robust method for mitigating finite-sample bias in structural equation models, outperforming standard estimators, especially in small-sample contexts.

Register for Upcoming Events

One-on-One Statistical Consulting for KAUST Researchers 2025

B1 L4 R4102

In recognition of World Statistics Day, a United Nations–designated observance that highlights the importance of trustworthy data and sound statistical methods, the KAUST Student Chapter of the American Statistical Association (ASA) is hosting one-on-one consulting sessions for KAUST students and researchers. Graduate students and postdoctoral researchers from the Statistics Program will be available to provide personalized guidance on research-related statistical challenges. These consultations aim to strengthen the use of statistical methods across disciplines, support high-quality research

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