Kevin Wu picking class 21

README.md

@@ -41,7 +41,7 @@ This student-led course explores modern techniques for controlling — and learn
 | 5  | 09/19/2025   | Lecture - Guancheng "Ivan" Qiu | **Nonlinear** trajectory **optimization**; collocation; implicit integration | |
 | 6  | 09/26/2025   | **External seminar 2** - Henrique Ferrolho | Trajectory **optimization** on robots in Julia Robotics | |
 | 7  | 10/03/2025   | Lecture - Jouke van Westrenen | Stochastic optimal control, Linear Quadratic Gaussian (LQG), Kalman filtering, robust control under uncertainty, unscented optimal control; | |
-| 8  | 10/10/2025   | **External seminar 3** TBD (speaker to be confirmed) | Topology **optimization** | |
+| 8  | 10/10/2025   | Lecture - Kevin Wu | Distributed optimal control & multi-agent coordination; Consensus, distributed MPC, and optimization over graphs (ADMM) ||
 | 9  | 10/17/2025   | **External seminar 4** — François Pacaud | GPU-accelerated optimal control | |
 |10  | 10/24/2025   | Lecture - Michael Klamkin | Physics-Informed Neural Networks (PINNs): formulation & pitfalls | |
 |11  | 10/31/2025   | **External seminar 5** - Chris Rackauckas | Neural Differential Equations: PINNs + classical solvers | |
@@ -62,7 +62,7 @@ Students must provide materials equivalent to those used in an in-person session
 | 18 | Lecture - Joe Ye | Robust control & min-max DDP (incl. PDE cases); chance constraints; Data-driven control & Model-Based RL-in-the-loop | |
 | 19 | Lecture - TBD | Contact Explict and Contact Implicit; Trajectory Optimization for Hybrid and Composed Systems;  | |
 | 20 | Lecture - TBD | Probabilistic Programming; Bayesian numerical methods; Variational Inference; probabilistic solvers for ODEs/PDEs; Bayesian optimization in control;  | |
-| 21 | Lecture - TBD | Distributed optimal control & multi-agent coordination; Consensus, distributed MPC, and optimization over graphs (ADMM). | |
+| 21 | Lecture - Kevin Wu | Distributed optimal control & multi-agent coordination; Consensus, distributed MPC, and optimization over graphs (ADMM). | |
 | 22 | Lecture - TBD | Dynamic Optimal Control of Power Systems; Generators swing equations, Transmission lines electromagnetic transients, dynamic load models, and inverters. | |
 
 ## Reference Material

class08/background_materials/README.md

@@ -1 +1,21 @@
 # Class 8 Background Material - 10/10/2025
+
+Lecture structure is still under development. Tentative plan:
+
+## Introduction
+Brief introduction of my research and background.
+
+## Topic 1: Consensus
+"Algorithms that provide rapid agreement and teamwork between all participants"
+Great foundational paper:
+https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4118472
+
+## Topic 2: ADMM (Alternating Direction Method of Multipliers)
+Great foundational textbook:
+https://web.stanford.edu/~boyd/papers/pdf/admm_distr_stats.pdf
+
+Perhaps introduce with the connection of progressive-hedging (in CEP research) to ADMM?
+
+## Topic 3: Model Predictive Control
+Foundational paper (tentative?):
+https://www.sciencedirect.com/science/article/pii/S0005109899002149?

class08/class08.md

@@ -1,8 +1,8 @@
 # Class 8 — 10/10/2025
 
-**Presenter:** TBD
+**Presenter:** Kevin Wu
 
-**Topic:** Topic TBD
+**Topic:** Distributed optimal control & multi-agent coordination; Consensus, distributed MPC, and optimization over graphs (ADMM)
 
 ---