Black Box Lectures

In the summer, interns, students, and faculty gather for Black Box Lectures. Each lecture covers an area of interest in machine learning, statistics, computer science, artificial intelligence, and neuroscience. The idea is to look under the hood of "black box" models, methods, and brains.

Each lecture will be a chalkboard talk with one presenter. The lectures will be held outside Marks Annex if nice weather (rain location: Freeman atrium). The time/day may change based on the weather but will usually be Tuesdays, 4-5pm. If you'd like to be added to the e-mail list, please let Ben know.


Ryan Fayyazi, "Sequential Monte Carlo", June 2024





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 ?? ??
Tues July 15 4-5pm Satwik Pasani ?? ??
Tues July 22 4-5pm Masayuki Nagai ?? ??
Tues July 29 4-5pm David Klindt Independent Component Analysis beginner
Tues Aug 5 4-5pm Shubham Choudhary ?? ??
Tues Aug 12 4-5pm Arkarup Banerjee ?? ??
Tues Aug 19 4-5pm Kyle Daruwalla ?? ??
Tues Aug 26 4-5pm Yaman Thapa ?? ??
Tues Sep 2 4-5pm Sung Liu ?? ??
Tues Sep 9 4-5pm Priyanka Gupta ?? ??
Tues Sep 16 4-5pm Stan Kerstjens ?? ??
Tues Sep 23 4-5pm ?? ?? ??
Tues Sep 30 4-5pm ?? ?? ??





beginner: No formal background in computational approaches but motivated to learn.
intermediate: Some knowledge in linear algebra, statistics, and/or computer science.
advanced: Could be a reviewer for an ML conference paper.







(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