University of Washington NeuroAI Seminar

Welcome to NeuroAI-UW seminar, a regular weekly seminar for UW community organized by NeuroAI Shlizerman Lab.

Meetings are currently held hybridly (Summer & Fall 2020, Winter & Spring & Fall 2021-2023, Winter 2024). Contact us if you would like to join! UW students can enroll into designated courses: AMATH 500L or EE 598F to participate in the seminarial activities.

New: We will be positing some of the invited visitors talks in NeuroAI YouTube playlist.

2024 Spring Schedule

This quarter, we review impactful alternative architectures recently proposed in the NeuroAI literature. The seminar is held every Friday from 11:00 am - noon PDT in a hybrid manner.

Date	Paper/Activity	Student Presenter
03/29/2024	Brainstorming Meeting & Final Presentations on NeuroAI and LLMs (Team 1, 2)	Mingfei Chen, Jingyuan Li, Frenda Lin, Trung Le, Kun Su, Yang Zheng, Jinlin Xiang, Jimin Kim, Xiulong Liu, Eunki Chung, Rahul Biswas
04/05/2024	Organizational & Intro Meeting & Final Presentations on NeuroAI and LLMs (Team 3)	Saba Heravi, James Hazelden, Ari Asarch, Yoonseo Orite, Kavya Balasubramanian
04/12/2024	Energy Transformer	James Hazelden, Saba Heravi, Yang Zheng
04/19/2024	State Space Models: Mamba: Linear-Time Sequence Modeling with Selective State Spaces & Efficiently Modeling Long Sequences with Structured State Spaces	Victoria Pierce, Mingfei Chen, and Xiulong Liu
04/26/2024	RNN Alternatives: RWKV: Reinventing RNNs for the Transformer Era & Hierarchically Gated Recurrent Neural Network for Sequence Modeling	Jinlin Xiang, Jesse Owens, and Jimin Kim
05/03/2024	MLP Mixer: An All MLP Architecture for Vision & The Forward-Forward Algorithm	Adithya Gowda Baragur, Seb Schwab, and Trung Le
05/10/2024	Building transformers from neurons and astrocytes & NISQ QNN: Classification with Quantum Neural Networks on Near Term Processors	Ian Quah, Sean Robert Gamer, and Jingyuan Li

2024 Winter Schedule

Thanks Jinlin, Mingfei and Saba for being Student Organizers.

In this quarter, we will prepare seminars on 3 critical topics related to NeuroAI and LLMs (Large Language Models). The seminar will be held every Friday 11:00am - 12:00pm (PST) hybridly.

Topic	Student Presenter
LLM-Enhanced Neural Decoding	Mingfei Chen, Jingyuan Li, Frenda Lin, Trung Le, Kun Su, Yang Zheng
Domain Adaptation of Pre-trained LLM for Research	Jinlin Xiang, Jimin Kim, Xiulong Liu, Eunki Chung, Rahul Biswas
Interpretation of Neural Networks in LLMs	Saba Heravi, James Hazelden, Ari Asarch, Yoonseo Orite, Kavya Balasubramanian

Date	Paper/Activity	Student Presenter
1/12/2024	Organizational & Intro Meeting on NeuroAI and LLMs
1/19/2024	Decoding Speech Perception from Non-Invasive Brain Recordings	Mingfei Chen, Jingyuan Li, Frenda Lin, Trung Le, Kun Su, Yang Zheng
1/26/2024	Large Language Models Struggle to Learn Long-Tail Knowledge	Jinlin Xiang, Jimin Kim, Xiulong Liu, Eunki Chung, Rahul Biswas
2/02/2024	Hopfield Networks is All You Needs	Saba Heravi, James Hazelden, Ari Asarch, Yoonseo Orite, Kavya Balasubramanian
2/09/2024	Guest Speaker Jean-Rémi King (École Normale Supérieure / Meta AI)
2/16/2024	Guest Speaker Nikhil Kandpal (University of Toronto)
2/23/2024	Guest Speaker: TBA

2023 Fall Schedule

In this quarter, we will continue to present tutorials and organize discussions on 6 critical topics related to NeuroAI.

Topic	Student Presenter
Deep Learning Programming Tools for NeuroAI	Yang Zheng, Jazlin Taylor
Design, Programing and Publishing OpenSource Code for NeuroAI	Jinlin Xiang, Trung Le, Jimin Kim
Data and Benchmarking Practices in NeuroAI	Amisha Himanshu Somaiya, Trung Le
Neuro, AI and NeuroAI Ethics	Rahul Biswas, Jingyuan Li
Hardware Acceleration for DL and NeuroAI	Saba Heravi, James Hazelden
LLMs and Their Relation to NeuroAI	Mingfei Chen, Xiulong Liu, Pavan Kumar Anand

2023 Spring Schedule

In this quarter, we will prepare and present tutorials on 6 critical topics related to NeuroAI.

Topic	Student Presenter
Deep Learning Programming Tools for NeuroAI	Astitwas S. Lathe, Yang Zheng, Wenxuan Hu
Design, Programing and Publishing OpenSource Code for NeuroAI	Jimin Kim, Jinlin Xiang, Trung Le
Data and Benchmarking Practices in NeuroAI	Ayush Singh, Chunqing Cao
Neuro, AI and NeuroAI Ethics	Rahul Biswas, Atharva Mattam, James Hazelden
Hardware Acceleration for DL and NeuroAI	Saba Heravi, Ruihong Yin, Carter Rowell
LLMs and Their Relation to NeuroAI	Xiulong Liu, Mingfei Chen, Jingyuan Li

2023 Winter Schedule

In this quarter, we will prepare and present tutorials on 5 critical topics related to NeuroAI.

Topic	Student Presenter
Deep Learning Programming Tools for NeuroAI	Sadjyot Gangolli, Mingfei Chen, Xiulong Liu, Hanna Lee
Design, Programing and Publishing OpenSource Code for NeuroAI	Jimin Kim, Kun Su, Pranav Kamath, Jingyuan Li
Data and Benchmarking Practices in NeuroAI	Jinlin Xiang, Trung Le, Ayush Singh
Neuro, AI and NeuroAI Ethics	Rahul Biswas, Ryan Vogt, Xinwen Liu
Hardware Acceleration for DL and NeuroAI	Yang Zheng, James Hazelden, Saba Heravi

2022 Fall Schedule

Thanks Mingfei and Jingyuan for being Student Organizer.

Date	Paper/Activity	Student Presenter
10/07/2022	Organizational & Intro Meeting on Energy Based Models
10/14/2022	A Path Towards Autonomous Machine Intelligence	James Hazelden, Saba Heravi, Andrew Line, Yang Zheng.
10/21/2022	The surprising effectiveness of representation learning for visual imitation	Hanna Lee, Jimin Kim
10/28/2022	Self-supervised learning of pretext-invariant representations	Jinlin Xiang, Trung Le
	Barlow twins: Self-supervised learning via redundancy reduction	Raphael Bechtold, Ryan V
11/04/2022	Understanding the world through action	Ze Xia (Lucas) Wang, Saba Heravi
	Deep hierarchical planning from pixels	Ruihong Yin, Pinyi Wang, Xiulong Liu
11/11/2022	Break Veterans Day
11/18/2022	Guest Speaker Yubei Chen (New York University)
11/25/2022	Break Thanksgiving
12/02/2022	Break NeurIPS
12/09/2022	NeurIPS Updates
12/16/2022	Guest Speaker Kuan Fang (UC Berkeley)

2022 Spring Schedule

Thanks Ryan Vogt and Jingyuan Li for being the Student Organizers.

Date	Paper/Activity	Student Presenter
04/01/2022	Organizational & Intro Meeting
04/08/2022	VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning	Kun Su, Mingfei Chen, Harsha Vardhan
	The Causal-Neural Connection: Expressiveness, Learnability, and Inference	Rahul Biswas, Shirui Chen, Xiulong Liu
04/15/2022	ILQR-VAE : Control-base Learning of Input Driven Dynamics with Application To Neural Data	Pamel Kang, Trung Le, Jingyuan Li
	Neural Active Learning with Performance Guarantees	Zhuochun Liu, Zhongshu Meng, Jinlin Xiang
04/22/2022	Inferring Latent Dynamics Underlying Neural Population aCTIVITY VIA neural Differential Equations	Michael Nolan, Saba H, Destiny Alvarado
	Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph	Yang Zheng, Anoop Mysore Nataraja, Malek Itani
04/29/2022	Guest Speaker Kevin Xia (Columbia University)
05/06/2022	Towards Biologically Plausible Convolutional Networks	Xiangyu Gao, Yujia Liu, Xinyue Sun
	Deep Reinforcement Learning with Spiking Q-Learning	Jingwei Xu, Miranda Anderson, Jimin Kim
05/13/2022	A3D3 Speakers
05/20/2022	TBA
05/27/2022	Guest Speaker Claudio Gentile (Google)
06/03/2022	A3D3 Speakers
06/10/2022	Guest Speaker Marine Schimel (Cambridge)

2022 Winter Schedule

Date	Paper/Activity	Student Presenter
01/14/2022	Organizational Meeting
01/21/2022	Where is all the nonlinearity: flexible nonlinear modeling of behaviorally relevant neural dynamics using recurrent neural networks	Michael Nolan, Saba Heravi, Ryan Vogt, Zekun Chen
	Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity	Kun Su, Xiangyu Gang, Pamel Kang, Jingyuan Li
01/28/2022	Neural Active Learning with Performance Guarantees	Xiulong Liu, James Hazelden, Jinlin Xiang, Liem Vu
	Dynamic Causal Modelling Revisited	Rahul Biswas, Astitwa Sarthak Lathe, Trung Le
02/04/2022	A3D3 NeuroAI
	OpenLabCluster Demo	Jingyuan Li (UW ECE), Moishe Kesselman (UW CSE)
	Detection of Sleep Spindles with FPGA	Xiaohan Liu (UW ECE), Aidan Yokuda (UW ECE)
	Somatotopic representation of texture sensation in the primary somatosensory and motor cortices of mice	Megan Lipton (Purdue Neurobiology)
02/11/2022	Guest Speaker Eva L. Dyer (Gatech)
02/18/2022	Stabilizing Dynamical Systems via Policy Gradient Methods	Jimin Kim, Mingfei Chen, Aidan Yokuda
	AugMax: Adversarial Composition of Random Augmentations for Robust Training	Yang Zheng, Xiaohan Liu, Yujia Liu, Xinyue Sun
02/25/2022	Guest Speaker Max Simchowitz (MIT)
03/04/2022	A3D3 NeuroAI
	Optimizing brain stimulation using deep learning	Seungbin Park (Purdue)
	Quantifying the effect of stimulation protocols on rapid network connectivity inference	Tomohiro Ouchi (UW)
	Modeling Neural Population Activity with Spatiotemporal Transformer	Trung Le (UW)
03/11/2022	Guest Speaker: Omid G. Sani (USC)

2021 Fall Schedule

Date	Paper/Activity	Student Presenter
10/08/2021	Organizational Meeting
10/15/2021	Representation learning for neural population activity with Neural Data Transformers	Rahul Biswas, Jimin kim
	Deep Reinforcement Learning for Neural Control	Ryan Vogt, Jinlin Xiang
10/22/2021	A unified framework of online learning algorithms for training recurrent neural networks	Harsha Vardhan, James Hazelden
	Lyapunov-Guided Embedding for Hyper-parameter Selection in Recurrent Neural Networks	Kun Su, Michael Nolan
10/29/2021	AL-SAR: Active Learning for Skeleton-based Action Recognition	Xiulong Liu, Syed M. Aun Haider
	How does it sound?	Jingyuan Li, Trung Le
11/05/2021	Guest Speaker Xiulong liu (UW)
	Guest Speaker Jingyuan Li (UW)
11/12/2021	Guest Speaker: Chethan Pandarinath (Georgia Tech)
	Guest Speaker: Joel Ye (CMU)
11/19/2021	Local Plasticity rules can learn deep representations using self-supervised contrastive predictions	Yang Zheng, Saba Heravi
	AI Choreographer: Music Conditioned 3D Dance Generation with AIST++	Xiangyu Gao, Yonghun Lee
11/26/2021	Thanksgiving Break
12/03/2021	Guest Speaker: Cristina Savin (NYU)
	Guest Speaker: Owen Marschall (NYU)

2021 Spring Schedule

Date	Paper/Activity	Student Presenter
04/02/2021	Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking	Chuanmudi Qin, Xiulong Liu, Kun Su
	Backpropagation and the brain	Ben Francis, Felix Tse, Trung Le
04/09/2021	Understanding self-supervised Learning Dynamics without Contrastive Pairs	Jingyuan Li, Ayesha Ghaffar, Zidan Luo
	Closed-Form Factorization of Latent Semantics in GANs	Jingxi Yu, Xiangyu Gao, Yang Zheng
04/16/2021	Guest Speaker: Anqi Wu (Columbia University)
04/23/2021	Non-reversible Gaussian processes for identifying latent dynamical structure in neural data	Rahul Biswas, Ryan Vogt, Michael Nolan
	Modeling behaviorally relevant neural dynamics with a novel preferential subspace identification	Saba Heravi, Astitwa Lathe, Yiren Wang, Jimin Kim
04/30/2021	Guest Speaker: Bolei Zhou (The Chinese University of Hong Kong)
05/07/2021	New Papers Discussion
05/14/2021	ICLR Paper Presentation
05/21/2021	No Meeting
05/28/2021	Guest Speaker: Omid G. Sani (USC)
06/04/2021	Guest Speaker: Yuandong Tian (Facebook)

2021 Winter Schedule

Date	Paper/Activity	Student Presenter
01/08/2021	Organizational Meeting
01/15/2021	Graph Convolutional Reinforcement Learning	Jinlin Xiang, Trung Le
	When Counterpoint Meets Chinese Folk Melody	Haobo Zhang, Xiulong Liu, Kun Su
01/22/2021	Gradient Starvation: A Learning Proclivity in Neural Networks	Ryan Vogt, Yang Zheng
	Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function	Michael Nolan, Ben Francis, Rahul Biswas
01/29/2021	Guest Speaker: Zhiyao Duan
02/05/2021	Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks	Jingyuan Li, Saba Heravi, Yetao Chen
	Improved protein structure prediction using potentials from deep learning	Chris Yin, Jamie Park, Jimin Kim
02/12/2021	Unsupervised Sound Separation Using Mixture Invariant Training	Kun Su, Jinlin Xiang, Zhichao Lei
	Deep Reinforcement Learning and its neuroscientific implications	Ben Francis, Trung Le, Saba Heravi
02/19/2021
02/26/2021	Guest Speaker: Kathryn Hess Bellwald
03/05/2021	Guest Speaker: Wenrui Zhang
03/12/2021	Guest Speaker: Mohammad Pezeshki

2020 Autumn Schedule

Date	Paper/Activity	Student Presenter
10/02/2020	Organizational Meeting
10/09/2020	Learning a Prior over Intent via Meta-Inverse Reinforcement Learning	Yang Zheng, Rahul Biswas
	Universality and Individuality in recurrent networks	Michael Nolan, Ben Francis
10/16/2020	Unsupervised deep learning identifies semantic disentanglement in single inferotemporal neurons	Jinlin Xiang, Ryan Vogt
	Low-dimensional dynamics for working memory and time encoding	Jimin Kim, Trung Le, David Babin
10/23/2020	Guest Speaker: Niru Maheswaranathan
10/30/2020	Rotational Dynamics Reduce Interference Between Sensory and Memory Represenatations	Jingyuan Li, Saba Heravi
	Foley Music: Learning to Generate Music from Videos	Kun Su, Xiulong Liu
11/06/2020	Guest Speaker: Christopher Cueva
11/13/2020	No meeting
11/20/2020	Guest Speaker: Alexandra Libby
11/27/2020	Thanksgiving Break - No meeting
12/4/2020	Guest Speaker: Irina Higgins
12/4/2020	Guest Speaker: Chuang Gan
12/11/2020	Research Video Updates

2020 Summer Schedule

We are reading papers published in recent Top AI Conferences (CVPR 2020, ICML 2020)!

Date	Paper	Keywords	Presenter	Presentation Link
7/30/2020	Improving the Gating Mechanism of Recurrent Neural Networks	RNN	Ryan Vogt	Google Slides
	Encoding Musical Style with Transformer Autoencoders	Music Generation	Kun Su	Google Slides
8/6/2020	Controllable Orthogonalization in Training DNNs	Network Optimization	Yang Zheng	Google Slides
	Π´nets: Deep Polynomial Neural Networks	Network Design	Jinlin Xiang	Google Slides
8/13/2020	Forecasting Sequential Data Using Consistent Koopman Autoencoders	Time Series Prediction	Saba Heravi	Google Slides
	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules	RNN	Jingyuan Li	Google SLides
8/20/2020	Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition	Graph, Skeleton	Rahul Biswas	Google Slides
	Do RNN and LSTM have Long Memory	RNN	Jimin Kim	Google Slides
8/27/2020	XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning	Incremental Learning	Kun Su	Google Slides
	Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network	RNN	Saba Heravi	Google Slides
9/3/2020	Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention	RNN	Ryan Vogt	Google Slides
	Deep Isometric Learning for Visual Recognition	Network Design	Jimin	Google Slides
9/10/2020	Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation	Weakly Supervised	Jinlin Xiang	Google Slides
	Towards Global Explanations of Convolutional Neural Networks with Concept Attribution	Interpretability	Jingyuan Li	Google Slides
9/17/2020	Low-rank Compression of Neural Nets: Learning the Rank of Each Layer	Compression	Rahul Biswas	Google Slides
	Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation		Yang Zheng	Google Slides