CEMSE Weekly Updates - September 29, 2026 Tue, Sep 29 2026 Newsletter Upcoming Events Stay informed about the upcoming events and the latest news from CEMSE. Integrated Silicon Photonics with Quantum Dot On-Chip Lasers: Enabling Scalable and Energy-Efficient Photonic Systems Yating Wan, Assistant Professor, Electrical and Computer Engineering Oct 4, 12:00 - 13:00 B9 R2325 quantum dot lasers Silicon photonics photonic systems energy efficiency This talk presents integrated silicon photonics with quantum dot on-chip lasers that enable development of scalable and energy-efficient photonic systems. Integrated Learning and Optimization and Computationally Efficient Model Predictive Control for Power Systems Applications Imran Pervez, Ph.D. Student, Electrical and Computer Engineering Oct 4, 17:00 - 19:00 B4 R5209; Zoom Meeting 96126193341 MCP power systems integrated machine learning optimization Advanced control systems engineering This dissertation studies novel model predictive control and integrated learning-optimization methodologies that enable computationally efficient, robust, and scalable real-time control and decision-making in modern power systems, improving renewable microgrid operation, electricity market performance, and optimization under uncertainty. Last-Iterate Convergence of Optimistic Multiplicative Weights Update Francesco Orabona, Associate Professor, Computer Science Oct 5, 12:00 - 13:00 B9 R2325 gradient descent operation optimistic gradient descent ascent convex optimization saddle-point problems This talk will show how OMWU converges asymptotically for smooth convex-concave saddle-point problems, with a small enough constant learning rate. Approximate Bayesian inference for structural equation models Haziq Jamil, Research Specialist, Statistics Oct 8, 12:00 - 13:00 B9 R2325 Laplace approximation Bayes estimators copulas R This talk reviews a fast approximate Bayesian SEM method that combines Laplace, variational Bayes, and Gaussian copula techniques to deliver near-MLE speed with MCMC-like inference, and is implemented in the R package INLAvaan.
