Feng Jiang

Orcid: 0009-0002-4206-6377

Affiliations:
  • University of Texas at Arlington, Department of Computer Science and Engineering, TX, USA


According to our database1, Feng Jiang authored at least 17 papers between 2022 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Learning from Guidelines: Structured Prompt Optimization for Expert Annotation Tasks.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
Segment Any Cell: A SAM-Based Auto-Prompting Fine-Tuning Framework for Nuclei Segmentation.
IEEE Trans. Neural Networks Learn. Syst., December, 2025

GRAM-TDI: adaptive multimodal representation learning for drug target interaction prediction.
CoRR, September, 2025

Leveraging Gait Patterns as Biomarkers: An attention-guided Deep Multiple Instance Learning Network for Scoliosis Classification.
CoRR, April, 2025

TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Text-Guided Multi-instance Learning for Scoliosis Screening via Gait Video Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

HAGE: Hierarchical Alignment Gene-Enhanced Pathology Representation Learning with Spatial Transcriptomics.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

Zero-Shot Composed Image Retrieval via Dual-Stream Instruction-Aware Distillation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity.
Briefings Bioinform., July, 2024

Toward Robust Self-Training Paradigm for Molecular Prediction Tasks.
J. Comput. Biol., 2024

UniEntrezDB: Large-scale Gene Ontology Annotation Dataset and Evaluation Benchmarks with Unified Entrez Gene Identifiers.
CoRR, 2024

Compositional Image Retrieval via Instruction-Aware Contrastive Learning.
CoRR, 2024

Segment Any Cell: A SAM-based Auto-prompting Fine-tuning Framework for Nuclei Segmentation.
CoRR, 2024

Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks.
Proceedings of the Computer Vision - ECCV 2024, 2024

AlphaEpi: Enhancing B Cell Epitope Prediction with AlphaFold 3.
Proceedings of the 15th ACM International Conference on Bioinformatics, 2024

2022
Robust self-training strategy for various molecular biology prediction tasks.
Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022


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