The Graduate Student Led Journal Club for Artificial Intelligence Research at Northwestern University

A Casual Place To Present, Ponder, and Discuss AI at Northwestern

Artificial Intelligence is historically and inherently an interdisciplinary field of research. Many of the biggest advancements in the field have come from incorporating insights from neuroscience, psychology, statistics, economics, human factors, linguistics, physics, topology, biology, and many other academic disciplines. AI Journal Club is meant to be a place where we can present, critique, and discuss research (both seminal and also cutting-edge) in a welcoming environment with a diversity of viewpoints. Presentations range from casual paper discussions, to in-depth tutorials of cutting-edge techniques in AI to spirited debates over the ethical implications of AI. We welcome graduate students from any department to attend and participate in discussion and encourage regular attendees to present research related to their own work, research that they would like to solicit help in understanding, research that can foster conversations about the future of our field, or just research that is interesting and sparks novel and exciting ideas.

Spring 2018 Meetings

View Larger Map

Graduate Students with a Northwestern University Email address can sign up for our Slack Channel here

Current Board Members

Previous Board Members

Previous Presentations

Spring 2018

6/6/18 Deep Learning with Differential Privacy

5/30/18 Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

5/23/18 The Building Blocks of Interpretability

5/16/18 Accountability of AI Under the Law: The Role of Explanation

5/8/18 Crowdsourced Pairwise-Comparison For Source Separation Evaluation

4/25/18 “Why Should I Trust You?” Explaining the Predictions of Any Classifier

4/18/18 The Mathematics of Statistical Machine Translation: Parameter Estimation

4/11/18 Efficient Video Object Segmentation via Network Modulation

4/4/18 Interpretable Decision Sets: A Joint Framework for Description and Prediction

Winter 2018

3/15/18 Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms

3/8/18 Recurrent Recommender Networks

3/1/18 Poincaré Embeddings for Learning Hierarchical Representations

2/8/18 Computer Assisted Authoring for Natural Language Story Scripts

2/1/18 VizWiz: Nearly real-time answers to visual questions

1/18/18 Game Design for Classical AI

1/11/18 A Few Useful Things To Know About Machine Learning

List of Past Presentations

Coming soon