Topic Modeling
647 faculty research Topic Modeling on GradNova.
Applications of Machine Learning in Natural Language Processing (conversational Agents, Grammar Error Correction, Automated Text Editing) and Material Design (bayesian Optimization of Catalysts, Oxygen Carriers and Other Materials to Facilitate Desirable Chemical Reactions for Co2 Conversion and Co2 Capture)
Machine Learning, Including Reinforcement Learning, Federated Learning, Continual Learning, Self-Supervised Learning, Meta Learning, Few Shot Learning, Causal Learning, Uncertainty Quantification and Calibration
Reinforcement Learning in Robotics
Topic Modeling
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Assistant Professor, Electrical and Computer Engineering
High-Recall Information Retrieval, in Which the Goal Is to Find Substantially All Information Relevant to an Information Need With the Least Possible Effort, Where the Stakes of Missing Relevant Information Are High
Key Application Areas Include Electronic Discovery in Law, Curation of Government Archives, and Systematic Review in Evidence-Based Medicine
Responsible AI and Data Science, Which Includes, but Is Not Limited To, Legal, Ethical, and Policy Considerations
Topic Modeling
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Thomas M. Linville Professor, Computer Science, Biomedical Engineering, and Data Science