Methods for Improving the Interpretability and Evaluation of Machine Learning Models and Decision Making Systems

ClusT: Interactive Visualization Tool for Deep Constrained Clustering on Tweets

Defensive Machine Learning Techniques for Countering Adversarial Attacks

Cell type identification in single-cell genomics and its applications

Enhancing Document Understanding through the Incorporation of Structural Inference

Contextual Embedding Representations for Retrieval-Based and Generation-Based Dialogue Systems

Computational Structures as Neural Symbolic Representation

Predictive value of cellphone geolocated mobility, vaccination, and social factors on COVID-19 mortality to provide foundational framework for predicting outcomes of future pandemics

Evaluating Speaker Diarization in Transcripts: A Text-based Approach with the TDER Metric and the TranscribeView System

Explanation Iterative Supervision via Saliency-guided Data Augmentation

Human.exe: Generating Critical Theories of Humanity in Human-Computer Interaction

Development of Immersive Cognitive Tasks for Use in Human Memory Research

Leveraging Distributed Tracing for Root Cause Localization in Microservice-Architectured Distributed Systems

Transcriptome Analysis of Primary Prostate Tumor Foci and Corresponding Lymph Node Metastases Identifies Pathways Associated with Metastatic Disease

Multi-task Multi-sensor Framework for Assessing Health Effects of Heat Exposure with Medical Sensors

Sentiment in Online Car Auctions

Vulnerability Detection: A Machine Learning Approach to Identifying Security Vulnerabilities In Code

The Emora College Companion: A Socialbot for College Students

Large scale neuronal type classification using graph neural networks