IML

Poster Presentation Session

Interpretable Machine Learning (CS 6390) - Spring 2024

Date: Wednesday, May 8th, 2024
Time: 5:30 PM to 7:30 PM
Address: 170 West Dr, St. Louis, MO 63121
Building: Social Sciences Building
Room: 335
Parking: You can park anywhere. Come early if you prefer to park on the street next to the building.

Student Projects

1. Insights into Visual Fraud: Exploring Interpretability with XceptionNet and LIME
2. Emotion Recognition: Training AI to Decipher Facial Expressions
3. Exploring Interpretability in ConvNeXt Models’ Advancements over ConvNet Towards Transformer-level Accuracy
4. GARCH Effects and Interpreting ECG (electrocardiogram) with LIME
5. Textual Insights: A Deep Dive into Cyberbullying Detection Through Interpretable AI
6. Decoding Insights with LIME: Unraveling the Interpretability of Gender Classifier
7. Interpreting Recidivism Prediction Models
8. Understanding NLP Encodings
9. Cloud Detection in Satellite Imagery using Deep Learning and its Interpretability

Visitors/judges (to be updated)

Joining in person during the poster session:

• Dr. Jie Hou, Associate Professor, SLU
• Wilbert S. Hawley III, Adjunct Instructor, SLU
• Harcharan S Kabbay, Senior ML Engineer, World Wide Technology
• Dr. Ken Smith, UMSL
• Shaney Flores, Instructor, WashU
• Abderrahmen Mtibaa, Assistant Professor, UMSL
• Bal Krishna Neupane, Instructor, UMSL

Comments by the judges