Professors and courses
Sean Benson
[intermediate] Deep Learning for a Better Understanding of Cancer
Thomas Breuel
[intermediate/advanced] Large Scale Deep Learning and Self-Supervision in Vision and NLP
Hao Chen
[introductory/intermediate] Label-Efficient Deep Learning for Medical Image Analysis [virtual]
Jianlin Cheng
[introductory/intermediate] Deep Learning for Bioinformatics
Nadya Chernyavskaya
[intermediate] Graph Networks for Scientific Applications with Examples from Particle Physics
Efstratios Gavves
[advanced] Advanced Deep Learning [virtual]
Quanquan Gu
[intermediate/advanced] Benign Overfitting in Machine Learning: From Linear Models to Neural Networks
Jiawei Han
[advanced] Text Mining and Deep Learning: Exploring the Power of Pretrained Language Models
Awni Hannun
[intermediate] An Introduction to Speech Recognition and Weighted Finite-State Automata [virtual]
Tin Kam Ho
[introductory/intermediate] Deep Learning Applications in Natural Language Understanding
Timothy Hospedales
[intermediate/advanced] Deep Meta-Learning
Shih-Chieh Hsu
[intermediate/advanced] Real-Time Artificial Intelligence for Science and Engineering
Tatiana Likhomanenko
[intermediate/advanced] Self-, Weakly-, Semi-Supervised Learning in Speech Recognition [virtual]
Othmane Rifki
[introductory/advanced] Speech and Language Processing in Modern Applications
Mayank Vatsa
[introductory/intermediate] Small Sample Size Deep Learning [virtual]
Yao Wang
[introductory/intermediate] Deep Learning for Computer Vision
Zichen Wang
[introductory/intermediate] Graph Machine Learning for Healthcare and Life Sciences
Alper Yilmaz
[introductory/intermediate] Deep Learning and Deep Reinforcement Learning for Geospatial Localization