update readme

Author: andrewrosemberg

README.md

@@ -1,7 +1,7 @@
 [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://learningtooptimize.github.io/LearningToControlClass/dev/)
 
 # Special Topics on Optimal Control and Learning — Fall 2025 (ISYE 8803 VAN)
-*Georgia Institute of Technology – Fridays 2 pm ET*
+*Georgia Institute of Technology – Fridays 2-4:45 pm ET*
 
 **Designers:** Andrew Rosemberg & Michael Klamkin  
 **Instructor:** Prof. Pascal Van Hentenryck
@@ -25,22 +25,36 @@ This student-led course explores modern techniques for controlling — and learn
 
 ## Weekly Schedule (Fall 2025 – Fridays 2 p.m. ET)
 
+#### In-person:
+
 | #  | Date (MM/DD) | Format / Presenter | Topic & Learning Goals | Prep / Key Resources |
 |----|--------------|--------------------|------------------------|----------------------|
-| 1  | 08/22/2025   | Lecture — Andrew Rosemberg | Course map; why PDE-constrained **optimization**; tooling overview; stability & state-space dynamics; Lyapunov; discretization issues | |
-| 2  | 08/29/2025   | Lecture | Numerical **optimization** for control (grad/SQP/QP); ALM vs. interior-point vs. penalty methods | |
-| 3  | 09/05/2025   | Lecture | Pontryagin’s Maximum Principle; shooting & multiple shooting; LQR, Riccati, QP viewpoint (finite / infinite horizon) | |
+| 1  | 08/22/2025   | Lecture — Andrew Rosemberg | Course map; why PDE-constrained **optimization**; tooling overview; stability & state-space dynamics; Lyapunov; discretization issues | [📚](https://learningtooptimize.github.io/LearningToControlClass/dev/class01/class01/) |
+| 2  | 08/29/2025   | Lecture - TBD | Numerical **optimization** for control (grad/SQP/QP); ALM vs. interior-point vs. penalty methods | |
+| 3  | 09/05/2025   | Lecture - TBD | Pontryagin’s Maximum Principle; shooting & multiple shooting; LQR, Riccati, QP viewpoint (finite / infinite horizon) | |
 | 4  | 09/12/2025   | **External seminar 1** - Joaquim Dias Garcia| Dynamic Programming & Model-Predictive Control | |
 | 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 | Essentials of PDEs for control engineers; weak forms; FEM/FDM review | |
+| 7  | 10/03/2025   | Lecture - TBD | Essentials of PDEs for control engineers; weak forms; FEM/FDM review | |
 | 8  | 10/10/2025   | **External seminar 3** TBD (speaker to be confirmed) | Topology **optimization** | |
 | 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 | |
 |12  | 11/07/2025   | Lecture - Pedro Paulo | Neural operators (FNO, Galerkin Transformer); large-scale surrogates | |
 |13  | 11/14/2025   | **External seminar 6** - Charlelie Laurent | Scalable PINNs / neural operators; CFD & weather applications | |
-|14  | 11/21/2025   | Lecture | Robust control & min-max DDP (incl. PDE cases); chance constraints; Data-driven control & RL-in-the-loop | |
+|14  | 11/21/2025   | Lecture - TBD | TBD from the pool | |
+
+#### Pool of additional topics
+
+If there are more students than slots, we will select from the following topics for recorded-lectures. 
+Students must provide materials equivalent to an in-person session. 
+
+| # | Format / Presenter | Topic & Learning Goals | Prep / Key Resources |
+|---|--------------------|------------------------|----------------------|
+| 15 | Lecture - TBD | Quaternions, Lie groups, and Lie algebras; attitude control; LQR with Attitude, Quadrotors | |
+| 16 | Lecture - TBD | Contact Explict and Contact Implicit; Trajectory Optimization for Hybrid and Composed Systems;  | |
+| 16 | Lecture - TBD | Trajectory Optimization with Obstacles; Convexification of Non-Convex Constraints; | |
+| 17 | Lecture - TBD | Robust control & min-max DDP (incl. PDE cases); chance constraints; Data-driven control & Model-Based RL-in-the-loop | |
 
 ## Reference Material