Rui Yin

Rui Yin

Assistant Professor at Department of Health Outcomes and Biomedical Informatics, University of Florida

About me

I am a tenure-track assistant professor (AI Initiative) at the Department of Health Outcome and Biomedical Informatics, University of Florida. I completed my postdoctoral training at the Department of Biomedical Informatics, Harvard Medical School, working with Dr. Paul Avillach. Before that, I received my Ph.D. degree from the School of Computer Science and Engineering, Nanyang Technological University of Singapore in 2020, under the supervision of Dr. Kwoh Chee Keong. My thesis is meta-analysis on the lethality of influenza A viruses using machine learning approaches, examined by the dissertation advisory committee members Professor Bo An, Professor Erik Cambria and Professor Sinno Jialin Pan. I obtained my bachelor’s degree and master’s degree from Shandong University and Central South University in 2013 and 2015, respectively.

Research Interest

  • LLM, NLP and PLM (protein language model) for downstream biomedical tasks (protein design, protein-protein interaction, miRNA-disease association, clinical notes extraction and entity recognition).
  • Computational modeling in RNA viruses, immunology and infectious disease (influenza, coronaviruses, etc.).
  • Machine learning modeling to facilitate the diagnosis and treatment of AD/ADRD, cancer, diabetes and liver disease, and rare/undiagnosed diseases.
  • Genotype-phenotype association study for biomarker identification and novel discovery.
  • Combination of clinical informatics and genomics to support clinical decision systems.
  • Interpretable and causal AI to advance health equity and improve patient outcomes.
Recent News
  • [Sep.2025] Meichuan Yin joined our lab as a research assistant. Welcome!
  • [Aug.2025] Praneeth Buchepalli joined our lab as a research assistant. Welcome!
  • [Aug.2025] I am collaborating in an NIGMS R35 project as Site PI to support the discovery of drug effects in cancer and dementia.
  • [Aug.2025] Our proposal “Leveraging AI to Decipher microRNA mis-regulation in Colorectal Cancer” was funded by the Florida Department of Health.
  • [Jul.2025] Our proposal of AI modeling to identify m7G modification sites in cancer was funded by UF Health AI Pilot and Exploratory Study
  • [Jun.2025] Our paper “FCFNets: A Factual and Counterfactual Learning Framework for Enhanced Hepatic Fibrosis Prediction in Young Adults with T2D” was online at MedRxiv and accepted for oral presentation at the 2025 AMIA Annual Symposium.
  • [Jun.2025] Ziying Zhang, PhD candidate at King’s College London, joined our lab as a visiting PhD student.
  • [Jun.2025] Mohammad Shafieinouri, PhD-MD student at the University of Florida, joined our lab for rotation. Welcome!
  • [May.2025] Yuanhan Chen joined our lab as a research assistant. Welcome!
  • [May.2025] Our paper “MTLNFM: A Multi-task Framework Using Neural Factorization Machines to Predict Patient Clinical Outcomes” was online at MedRxiv.
  • [May.2025] I served as a Panel Reviewer for the University of Florida R01 BootCamp Program.
  • [Apr.2025] Our paper “AutoRADP: An Interpretable Deep Learning Framework to Predict Rapid Progression for Alzheimer’s Disease and Related Dementias Using Electronic Health Records” was online at MedRxiv and accepted for a flash talk at the 2025 ICIBM conference.
  • [Apr.2025] Our paper “RNALoc-LM: RNA subcellular localization prediction using pre-trained RNA language model” was published in the Journal of Bioinformatics.
  • [Mar.2025] I served as a Panel Reviewer for the PHHP PhD Fellowship Program at the University of Florida.
  • [Mar.2025] I am serving as Guest Editor on MDPI Applied Sciences on the Topic “Advanced Image and Video Processing Technology for Healthcare”.
  • [Mar.2025] Our paper “SEHI-PPI: An End-to-End Sampling-Enhanced Human-Influenza Protein-Protein Interaction Prediction Framework with Double-View Learning” was online at BioRxiv.
  • [Feb.2025] I served as a Panel Reviewer at NIH study section GVE.
  • [Feb.2025] Jiaxin Li joined our lab as a voluntary research assistant. Welcome!
  • [Jan.2025] I served as a Panel Reviewer for the SC EPSCoR GAIN program.
  • [Jan.2025] Our paper “Social Determinants of Healthy Aging: An Investigation using the All of Us Cohort” was online at MedRxiv.
  • [Nov.2024] I served as a Panel Reviewer for the UF-Scripps Pilot Program.
  • [Oct.2024] Our paper “Blood-tumor barrier organoids recapitulate glioblastoma microenvironment and enable high-throughput modeling of therapeutic delivery” was online at BioRxiv.
  • [Sep.2024] Our proposal “The Nucleotide-to-Graph Language Models for Identifying miRNA-Target Interactions in Colorectal Cancer Patients” was funded by the Elsa U. Pardee Foundation.
  • [Aug.2024] Our paper “Phenome-wide profiling identifies genotype-phenotype associations in Phelan-McDermid syndrome using family-sourced data from an international registry” was published in the Journal of Molecular Autism.
  • [Aug.2024] Our paper “SGCL-LncLoc: An Interpretable Deep Learning Model for Improving IncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning” was published in the Journal of Big Data Mining and Analytics.
  • [Jul.2024] Our paper “Autoencoder to Identify Sex-Specific Sub-phenotypes in Alzheimer’s Disease Progression Using Longitudinal Electronic Health Records” was online at MedRxiv.
  • [Jul.2024] Our paper “BertSNR: an interpretable deep learning framework for single-nucleotide resolution identification of transcription factor binding sites based on DNA language model” was published in the Journal of Bioinformatics.
  • [Jun.2024] Mengting Xiong joined our lab as a Research Coordinator, welcome!
  • [Jun.2024] Lin Li joined our lab as a PhD student, welcome!
  • [Jun.2024] I gave a presentation at the IEEE International Conference on Healthcare Informatics (ICHI) 2024, with the topic “Interpretable AI (XAI) on Graphs and Its Applications in Biomedicine”.
  • [Apr.2024] Our paper “Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer” was online at BioRxiv.
  • [Apr.2024] Our paper “VarPPUD: Variant post prioritization developed for undiagnosed genetic disorders” was online at MedRxiv.
  • [Apr.2024] Hongru Zhao accepted the PhD offer from Michigan State University, congratulations!
  • [Mar.2024] Our paper “An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer’s Disease Using UK Biobank” was online at MedRxiv.
  • [Feb.2024] Our proposal “Semantic Embedded Graph Neural Networks to Unravel miRNA Targets in Colorectal Cancer” was funded by UF College of Medicine’s Office of Research and the Intelligent Clinical Care Center.
  • [Feb.2024] Our paper “EF-Net: Mental State Recognition by Analyzing Multimodal EEG-fNIRS via CNN” was accepted by MDPI Sensors.
  • [Feb.2024] I am serving as a panel reviewer in NSF.
  • [Jan.2024] Our paper “Changes in Cyclic Guanosine Monophosphate Channel of 661w Cells In vitro with Excessive Light Time” was accepted by the Journal of Ophthalmic & Vision Research.
  • [Jan.2024] I am serving as an Associate Editor in the Journal of Heliyon, Bioinformatics and Computational Biology Section.
  • [Jan.2024] Our paper “SGCL-LncLoc: an interpretable deep learning model for improving lncRNA subcellular localization prediction with supervised graph contrastive learning” was accepted by Big Data Mining and Analytics.
  • [Jan.2024] Daphne Calin joined our lab as an undergraduate research assistant. Welcome!
  • [Dec.2023] Our paper “Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach” was accepted by JMIR AI.
  • [Dec.2023] Our paper “LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism” was accepted by Bioinformatics.
  • [Nov.2023] Our paper “CLCAP: Contrastive Learning Improves Antigenicity Prediction for Influenza A Virus Using Convolutional Neural Networks” was accepted by Methods.
  • [Nov.2023] Qiang Yang joined our lab as a postdoc researcher, welcome!
  • [Oct.2023] Our paper “HSELDA: Heterogeneous Sub-Graph Learning for lncRNA-Disease Associations Prediction” was accepted by the 2023 IEEE International Conference on Bioinformatics and Biomedicine.
  • [Oct.2023] Our paper “PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction” was accepted by the 2023 IEEE International Conference on Bioinformatics and Biomedicine.
  • [Sep.2023] Our paper “Editorial: Computational Methods to Analyze RNA Data for Human Diseases” was accepted by Frontiers in Genetics.
  • [Sep.2023] I am serving as an Editorial Board Member in the Journal of BMC Bioinformatics
  • [Sep.2023] Our proposal “Targeted protein design via constrained denoising diffusion probabilistic models” was funded by the Ministry of Education, Singapore
  • [Aug.2023] Our paper “Identification of Outcome-Oriented Progression Subtypes from Mild Cognitive Impairment to Alzheimer’s Disease Using Electronic Health Records” was accepted by the 2023 AMIA Annual Symposium
  • [Aug.2023] Our paper “MTLNFM: Multi-task Learning to Predict Patient Clinical Outcomes with Neural Factorization Machine” was accepted by the 2023 AMIA Annual Symposium
  • [Aug.2023] Pratyush Shukla joined our lab as a graduate research assistant. Welcome!
  • [Jul.2023] I was invited to give a talk at the 2023 International Conference on Intelligent Biology and Medicine Workshop, with the topic “Leveraging the power of genomics to facilitate the diagnosis of undiagnosed diseases with machine learning models”
  • [Jul.2023] I am serving as the co-chair for the 2024 IEEE International Conference on Healthcare Informatics Tutorial.
  • [Jun.2023] Rohit Inampudi joined our lab as an undergraduate research assistant. Welcome!
  • [Jun.2023] Weimin Meng joined our lab as a PhD student, welcome!
  • [Jun.2023] I was appointed as guest editor for the Special Issue “Computational Modeling in RNA Viruses” in the Journal of MDPI Viruses.
  • [May.2023] Our paper “COMET: Convolutional Dimension Interaction for Collaborative Filtering” was accepted by ACM Transactions on Intelligent Systems and Technology.
  • [May.2023] Our paper “ViPal: A framework for virulence prediction of influenza viruses with prior viral knowledge using genomic sequences” was accepted by the Journal of Biomedical Informatics.
  • [Apr.2023] Hongru Zhao joined our lab as a graduate research assistant, welcome!
  • [Apr.2023] I am serving as a co-chair for the International Conference on Intelligent Biology and Medicine Workshop (ICIBM 2023).
  • [Mar.2023] Our proposal “Contrastive Convolutional Neural Networks to Predict High-confidence mRNA-miRNA Pairs in Colorectal Cancer Patients” was funded by UF Health Cancer Center as Artificial Intelligence Supplement Pilot & Exploratory Program.
  • [Mar.2023] I am serving as Program Committee member for IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2023).
  • [Feb.2023] I was appointed as the Guest Editor in the Journal of Computational Genomics of Frontiers in Genetics.
  • [Feb.2023] I joined UFHealth Cancer Center as a community member.
  • [Jan.2023] Our paper “CLCAP: Contrastive Learning Improves Antigenicity Prediction for Influenza A Virus Using Convolutional Neural Networks” was accepted by the 21st Asia Pacific Bioinformatics Conference.
  • [Jan.2023] Our paper “A review of the enzyme design in catalytic stability by artificial intelligence” was accepted by Briefings in Bioinformatics.
  • [Dec.2022] I officially started my position as an assistant professor at HOBI, University of Florida
  • [Nov.2022] Our paper “GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation” was accepted by Briefings in Bioinformatics.
  • [Nov.2022] I am serving as Program Committee member for the 21st Asia Pacific Bioinformatics Conference (APBC).
  • [Nov.2022] Xiangyu Chen joined our lab as a research intern, welcome!
  • [Oct.2022] Jiaxin Li joined our lab as a research undergraduate student. Welcome!
  • [Oct.2022] Our collaborative proposal “Computational Drug Repurposing for AD/ADRD with Integrative Analysis of Real-World Data and Biomedical Knowledge was funded by NIA!
  • [Sep.2022] I am serving as Program Committee member for IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2022).
  • [Aug.2022] Xiaohan Li joined our lab as a research graduate student, welcome!
  • [Jun.2022] Our paper “A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods” was accepted by Briefings in Bioinformatics.
  • [May.2022] I was appointed as guest editor for Research Topic: Computational Methods to Analyze RNA Data for Human Diseases in the Journal of Frontiers In Genetics.
  • [May.2022] I accepted the offer from the University of Florida and will join the university as a tenure-track assistant professor this December.
  • [Apr.2022] I was invited to give a talk at Auburn University, Auburn, Alabama.
  • [Apr.2022] I was invited to give a talk at the University of Florida, Gainesville, Florida.
  • [Apr.2022] I was invited to give a talk at Emory University, Atlanta, Georgia.
  • [Mar.2022] New preprint “ViPal: A Framework for Virulence Prediction of Influenza Viruses with Prior Viral Knowledge Using Genomic Sequences” is released.
  • [Mar.2022] I was invited to give a talk at the University of California Irvine. (Virtual)
  • [Mar.2022] I was invited to give a talk at the University of Massachusetts, Boston, Massachusetts.
  • [Mar.2022] Our paper “Mendelian Randomization Analysis Suggests No Associations of Herpes Simplex Virus Infections With Multiple Sclerosis” was published at Frontiers in Neuroscience.
  • [Feb.2022] I was invited to give a talk at Boston University, Boston, Massachusetts.