Sheng Li

Assistant Professor

University of Virginia

United States

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About

Dr. Sheng Li is an Assistant Professor at the University of Virginia. His research interests encompass artificial intelligence, neural networks, and biological applications, as reflected in his recent publications on topics such as visual semantics, protein sequencing, and medication adherence monitoring. Dr. Li has contributed significantly to the fields of unsupervised learning and causal inference through innovative algorithm development and editorial work.

Articles (14)

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2024

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2023

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2023

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2021

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2020

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UNITED STATES

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Sheng Li

Research Interests

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Articles (14)

Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations

Engineering Biological Nanopore Approaches toward Protein Sequencing

Cross-Domain Graph Convolutions for Adversarial Unsupervised Domain Adaptation

Application of Artificial Intelligence to the Monitoring of Medication Adherence for Tuberculosis Treatment in Africa: Algorithm Development and Validation

Co-Embedding of Nodes and Edges With Graph Neural Networks

Knowledge-Guided Article Embedding Refinement for Session-Based News Recommendation

Flexible Auto-Weighted Local-Coordinate Concept Factorization: A Robust Framework for Unsupervised Clustering

A Survey on Causal Inference

Editorial: Deep dictionary learning: Algorithm, theory and application

Editorial: IMAVIS special issue on deep cross-media neural model for generating image descriptions

Mapping the glycosyltransferase fold landscape using interpretable deep learning

Deep evolutionary analysis reveals the design principles of fold a glycosyltransferases

Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space

Marginalized Multiview Ensemble Clustering

Collaborators (5)

Juliet Nabbuye Sekandi

Pengsheng Ji

Chang Liu

Joseph Reiner

Aleksei Aksimentiev

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