QB/AI Black Box Lectures
In the summer, interns, students, and faculty gather for Black Box Lectures. Each lecture covers an area of interest of the presenter, spanning machine learning, statistics, computer science, and artificial intelligence as well as computational ideas in neuroscience, genetics, molecular biology, and plant biology, among others. The idea is to look under the hood of "black box" models, methods, brains, proteins, and molecules to better understand complex systems.
Each lecture will be a chalkboard talk with one presenter. The lectures will be held in the Hawkins room (Wendt building) usually Wednesdays at 12pm with lunch served (thanks QB/AI Simons Center!). This website has the most up-to-date information about lecture topics, times, and presenters.
Ryan Fayyazi, "Sequential Monte Carlo", June 2024
Summer 2026 Schedule
| Day | Time | Room | Presenter | Topic |
|---|---|---|---|---|
| Wed July 1 | 12-1pm | Hawkins | Ben Cowley | ?? |
| Wed July 8 | 12-1pm | Hawkins | Kate Alexander | Gene Neighborhoods |
| Wed July 15 | 12-1pm | Hawkins? | Zachary Lippman | ?? |
| Wed July 22 | 12-1pm | Hawkins? | ?? | ?? |
| Wed July 29 | 12-1pm | Hawkins? | Satwik Pasani | Stochastic Differential Equations |
| Wed Aug 5 | 12-1pm | Hawkins | Justin Kinney | ?? |
| Wed Aug 12 | 12-1pm | Hawkins | Masayuki Nagai | ?? |
| Wed Aug 19 | 12-1pm | Hawkins | Alex Koulakov | Mixture-of-experts in an olfactory system |
| Wed Aug 26 | 12-1pm | Hawkins | Habon Issa | Temporal coding |
(old) Summer 2025 Schedule
| Day | Time | Presenter | Topic | Difficulty |
|---|---|---|---|---|
| Tues June 17 | 4-5pm | Ben Cowley | Color processing in Brains and AI | beginner |
| Tues June 24 | 4-5pm | J. Casco-Rodriguez | Recurrent and spiking neural networks | intermediate |
| Tues July 1 | 4-5pm | Amitava Banerjee | Bad math for good plots: the replica trick | intermediate |
| Tues July 8 | 4-5pm | Kaiser Loell | Motif finding and EM | intermediate |
| Tues July 15 | 4-5pm | Satwik Pasani | KL Divergence | intermediate |
| Tues July 22 | 4-5pm | Masayuki Nagai | Continual Learning | intermediate |
| Tues July 29 | 4-5pm | David Klindt | Independent Component Analysis | beginner |
| Tues Aug 5 | 4-5pm | Shubham Choudhary | Deriving DNNs as synapses | beginner |
| Tues Aug 12 | 4-5pm | Arkarup Banerjee | Conducting a concert of neurons | beginner |
| Wed Aug 20 | 4-5pm | Kyle Daruwalla | How to train your dragon (LLM) | intermediate |
| Tues Aug 26 | 4-5pm | Yaman Thapa | TD Learning: Expectation meets reality | beginner |
| Tues Sep 2 | 4-5pm | Sunny Liu | Info. Geometry and Natural Grads. | beginner |
| Tues Sep 9 | 4-5pm | Stan Kerstjens | Complexity: it’s complicated… or is it? | beginner |
(old) Summer 2024 Schedule
| Day | Time | Presenter | Topic | Difficulty |
|---|---|---|---|---|
| Thurs June 6 | 4:30-5:30pm | Ben Cowley | Bayesian Active Learning | intermediate |
| Thurs June 13 | 4:30-5:30pm | Wolf de Wulf | Gaussian Processes | intermediate |
| Thurs June 20 | 4:30-5:30pm | Ryan Fayyazi | Sequential Monte Carlo | Intermediate |
| Thurs June 27 | 4:30-5:30pm | Tig Moore | Pruning in biological and artificial neural networks | Beginner |
| Thurs July 4 | -- | No meeting | -- | -- |
| Thurs July 11 | 4:30-5:30pm | Ludovic Corcos | Physics-Informed Neural Networks | Advanced |
| Thurs July 18 | 4:30-5:30pm | Satwik Pasani | Maximum Entropy Models | Intermediate |
| Thurs July 25 | 4:30-5:30pm | Todd Morrill | Variational Autoencoders | Intermediate |
| Thurs Aug 1 | 4:30-5:30pm | CiCi Zheng | Predictive coding 101 | beginner |
| Thurs Aug 8 | 4:30-5:30pm | Christos Kaneen | Bio-inspired credit assignment | Intermediate |
| Thurs Aug 15 | 4-5pm | Arka Banerjee | Computing time in the Brain | Beginner |
| Thurs Aug 22 | 4:30-5:30pm | Jamie Lohoff | Automatic Differentiation 101 | Beginner |
| Thurs Aug 29 | 4:30-5:30pm | Kyle Daruwalla | Derivatives, Descent, and auto-Differentiation | Intermediate |
| Thurs Sep 5 | 4:30-5:30pm | Ari Benjamin | Stochastic Gradient Estimation | Beginner |
| Thurs Sep 12 | 4:30-5:30pm | Masayuki Nagai | Kolmogorov-Arnold Networks (KANs) | Beginner |
| Thurs Sep 19 | 4:30-5:30pm | Christian Pehle | Spikes, States and Spaces | Advanced |
| Thurs Oct 3 | 4:30-5:30pm | Tingkai Liu | Transformers and Mamba | advanced |
(old) Summer 2023 Schedule
| Day | Time | Presenter | Topic | Difficulty |
|---|---|---|---|---|
| Thurs June 8 | 5-6pm | Ben Cowley | Linear regression with active learning | intermediate |
| Tues June 13 | 5-6pm | Pantelis Vafeidis | Introduction to Transformers | intermediate |
| Fri June 30 | 4-5pm | Kyle Daruwalla | Double Descent in Deep Learning | intermediate |
| Wed July 5 | 5-6pm | Ryan Fayyazi | Diffusion models: Different perspectives | intermediate |
| Tues July 11 | 5-6pm | Xiaoxuan Lei | Introduction to Topological Data Analysis | intermediate |
| Tues July 25 | 5-6pm | Christian Pehle | Optimal Control Theory | advanced |
| Tues Aug 1 | 5-6pm | Arkarup Banerjee | Coincidence detectors | neuroscience |
| Tues Aug 8 | 5-6pm | Burak Gurbuz | Introduction to Continual Learning | Beginner |
| Thurs Aug 17 | 4:30-5:30pm | Ben Cowley | The History of Optimization | intermediate |
| Tues Aug 22 | 4:30-5:30pm | Ari Benjamin | The dynamics of gradient descent | intermediate |
| Tues Aug 29 | 4:30-5:30pm | CiCi Zheng | Hopfield networks and energy functions | beginner |