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