Doctoral Student Research in AI & Machine Learning
Machine learning is the sub-field of AI concerned with learning models from data. Once learned, these models can be use to label future data, make predictions about the future, aid in decision making, or explain the past. At Rice, we cover multiple sub-fields of machine learning, including deep learning.
Faculty
Faculty members leading research in AI & ML are as follows:
- Xia (Ben) Hu
- Chris Jermaine
- Tasos Kyrillidis
- Anshumali Shrivastava
- Arlei Silva
- Devika Subramanian
- Moshe Vardi
The videos below represent current student research projects.
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TwIST: Transformer with Independent Subnetwork TrainingPresenters: Michael Menezes, Xinze Feng, Barbara Su
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Unveiling Hidden Pivotal Players with GoalNet: A GNN-Based Soccer Player Evaluation SystemPresenter: Jacky Jiang |
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FedJets: Efficient Just-In-Time Personalization with Federated Mixture of ExpertsPresenter: Yehya Farhat |
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Provable Model-Parallel Distributed PrincipalPresenter: Barbara Su |
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R-SKI: Robust, Attention-guided Models for Pediatric Chest X-ray Classification using Knowledge-Infused Transfer Learning with Self-SupervisionPresenter: Sheng Cheng |
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CORGI: Coupled Reinforcement Learning for Device Assignment in Non-Blocking Computation GraphsPresenter: Xinyu Yao |
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Attribute-Enhanced Similarity Ranking for Sparse Link PredictionPresenter: João Mattos |