Dr. Yang Li received his Ph.D. in Operations Research and Control Theory from the School of Mathematics at Shandong University in 2019, under the supervision of Prof. Guojun Li. During his doctoral studies, he conducted joint research at the Department of Bioinformatics and Genomics, College of Computing and Informatics at The University of North Carolina at Charlotte. He subsequently pursued postdoctoral training in the Department of Biomedical Informatics, College of Medicine at The Ohio State University and later worked in R&D at AstraZeneca plc. Since March 2024, he has been an assistant professor at the School of Mathematics, Statistics and Mechanics, Beijing University of Technology. He is a recipient of the Beijing High-Level Youth Talent Award and has served as a guest editor for Frontiers in Genetics.

Dr. Li’s research interests lie in gene regulatory network inference, transcription factor binding site prediction, and single-cell sequencing data analysis. He has authored over 20 peer-reviewed publications in leading journals, including Nature Communications, Nucleic Acids Research, Briefings in Bioinformatics, Bioinformatics, and iScience. His work has been cited over 700 times (Google Scholar), with a single article cited up to 190 times.

Research Experience

Assistant Professor

Institute of Operations Research and Information Engineering
School of Mathematics, Statistics and Mechanics
Beijing University of Technology
April 2024 – Present

Research Focus:

• Developing algorithms using graph theory, combinatorial optimization, and machine learning to reconstruct regulatory networks driving cellular evolution from single-cell multi-omics data
• Building combinatorial optimization and machine learning models to identify key features, interactions, and regulatory networks underlying phenotypes in single-cell multi-modal data
• Designing deep learning methods for spatial transcriptomics to predict tissue modules and their regulatory networks

Postdoctoral Researcher

Chronic Obstructive Pulmonary Disease & Idiopathic Pulmonary Fibrosis R&D Unit
AstraZeneca, Gaithersburg, MD, USA
Supervisors: Mahboobeh Ghaedi (Principal Scientist), Rania Dagher (Associate Principal Scientist)
March 2022 – March 2024

Research Focus:

• Modeled pulmonary emphysema using iPSC-derived foam spheroid/COPD fibroblast co-culture systems with scRNA-seq analysis
• Investigated susceptibility of alveolar type II progenitor cells in COPD using in vitro iPSC systems
• Mapped cell lineage trajectories and key regulators in COPD and IPF via pseudotemporal analysis of scRNA-seq data

Postdoctoral Researcher

Departments of Biomedical Informatics & Neuroscience
The Ohio State University Wexner Medical Center, Columbus, OH, USA
Advisors: Qin Ma (Professor), Phillip G. Popovich (Professor and Chair of Neuroscience)
January 2020 – March 2022

Research Focus:

• Developed novel algorithms to construct gene regulatory networks, enhancer-driven regulons, and enhancer-driven GRNs from scRNA-seq and scATAC-seq data
• Explored microglial roles in coordinating intercellular interactions for spinal cord injury repair via scRNA-seq
• Studied vulnerability of the middle temporal gyrus in Alzheimer’s disease through spatial transcriptomics analysis
• Created deep learning models for simultaneous imputation and clustering of scRNA-seq data
• Designed combinatorial biclustering algorithms for large-scale scRNA-seq and spatial transcriptomics data
• Revealed differential regulation of chemokines in tumor-associated macrophages within tumor microenvironments
• Built algorithms and DL models for transcription factor motif discovery from ChIP-seq, ChIP-exo, and ATAC-seq data

Teaching Experience

Beijing University of Technology

2024 – Present

• Instructed undergraduate and graduate courses in approximation algorithms, mathematical engineering, and integer programming
• Developed specialized modules on mathematical applications in bioinformatics and intelligent radiotherapy
• Led problem-solving sessions for engineering mathematics courses

The Ohio State University

2020 – 2021

• Taught computational genomics and machine learning courses for medical graduate students
• Designed curriculum on single-cell epigenetics (scATAC-seq) and graph neural networks
• Created modules on statistical pitfalls in bioinformatics for interdisciplinary data science courses

Earlier Appointments

• Teaching assistant for international combinatorics course
• Teaching assistant for mathematical analysis in National Science Experiment Base (i.e., Mathematics base class, Hua Luogeng Class, or Pan Chengdong Class)

Conferences

1. Workshop on Bioinformatics and Precision Medicine, January 2025, Weihai, Shandong, China
2. Annual Conference on Operations Research and Information Engineering, December 2024, Beijing, China
3. Workshop on Combinatorial & Continuous Optimization and Mathematics-Medicine Interdisciplinary Research, October 2024, Beijing, China
4. 15th International Conference on Computational Systems Biology (ISB 2024), August 2024, Kaifeng, Henan, China
5. Workshop on Bioinformatics and Precision Medicine, August 2024, Weihai, Shandong, China
6. Workshop on Original Exploration Program of NSFC, June 2024, Nanjing, Jiangsu, China
7. Parallel Forum on Modern Urban Construction (Beijing International Youth Innovation Forum) & 7th “Rixin Forum” for International Young Scholars, November 2023, Beijing, China
8. Young Scholars Forum on Mathematics-Computer Science-Life Sciences, July 2023, Beijing, China
9. Interdisciplinary Conference on Mathematics and Bioinformatics, November 2019, Qingdao, Shandong, China
10. Conference on Intelligent Computing and Biomedical Big Data, November 2018, Shanghai, China
11. Workshop on Graph Theory and Its Applications, September 2016, Jinan, Shandong, China
12. Young Scholars Forum on Mathematics-Computer Science-Life Sciences, May 2014, Beijing, China
13. International Workshop on Bioinformatics, July 2013, Shanghai, China

Grants

1. Beijing Municipal Human Resources and Social Security Bureau, China: Research Funding for “Dynamic Analysis of Gene Regulatory Mechanisms and Algorithm Development Using Single-Cell Multi-omics Data”, 09/2025-06/2026, ¥50,000, PI
2. Beijing University of Technology, China: Discipline Development Fund (Startup Grant #057000514125508), 01/2025-12/2025, ¥50,000, PI
3. Ministry of Science and Technology, China: National Key Research and Development Program “Research and Translation of Key Issues in Intelligent Radiotherapy for Tumors” (#2024YFA1014100), 12/2024-12/2027, ¥20,000,000, Participant
4. National Natural Science Foundation of China: General Program “Algorithm Development for Cell-Specific Analysis and Regulatory Mechanisms Using Single-Cell Multi-omics Data” (#62272270), 01/2023-12/2026, ¥550,000, Participant
5. National Science Foundation, United States: Early-concept Grants for Exploratory Research “IIBR Informatics: Reinforced Imputation Framework for Gene Expression Recovery from Single-Cell RNA-seq Data” (#1945971), 03/2021-02/2024, $300,000, Participant (Completed)
6. National Institutes of Health/National Cancer Institute, United States: U24 Resource Grant “Participant Engagement and Cancer Genome Sequencing Coordinating Center” (#U24CA252977), 08/2020-07/2025, $1,965,600, Participant (Ongoing)
7. National Natural Science Foundation of China: Key Program “Graph and Combinatorial Optimization-based Algorithms for Biological and Network Data Mining” (#11931008), 01/2020-12/2024, ¥2,700,000, Participant (Ongoing)
8. National Natural Science Foundation of China: General Program “Structural Modeling and Molecular Transport Mechanisms of Multi-family Ion Cotransporters” (#31870094), 01/2019-12/2022, ¥590,000, Participant (Completed)
9. National Natural Science Foundation of China: General Program “Prediction and Analysis of Cis-regulatory Motifs Using Next-Generation Sequencing Data” (#61772313), 01/2018-12/2021, ¥630,000, Participant (Completed)
10. National Science Foundation, United States: Advances in Bioinformatics Innovation Grant “Annotation of Cis-regulatory Sequences Using a Large Number of Chromatin Immunoprecipitation Sequencing Datasets” (#1661332), 08/2017-07/2022, $810,000, Participant (Completed)
11. National Natural Science Foundation of China: General Program “Metagenomic Assembly Algorithm Development via de Bruijn Graph Simplification” (#61771009), 01/2017-12/2020, ¥500,000, Participant (Completed)
12. National Natural Science Foundation of China: General Program “Theoretical Studies and Algorithms for Key Driver Mutation Pathways in Cancer Genomes” (#31571354), 01/2016-12/2019, ¥250,000, Participant (Completed)
13. National Natural Science Foundation of China: General Program “Regulatory Motif Prediction Using Chromatin Immunoprecipitation Sequencing Data and Phylogenetic Information” (#61303084), 01/2014-12/2016, ¥230,000, Participant (Completed)
14. National Natural Science Foundation of China: General Program “Computational Methods for Assembling Alternatively Spliced Transcriptomes from RNA-Seq Data” (#61272016), 01/2013-12/2016, ¥600,000, Participant (Completed)

Awards

1. Beijing High-Level Young Talent, Beijing Municipality, May 2024
2. Best Presentation Award: Parallel Forum on Modern Urban Construction (Beijing International Youth Innovation Forum) & 7th “Rixin Forum” for International Young Scholars, Beijing University of Technology, November 2023
3. Top 10 Annual Selected Papers, Ohio State University: “Elucidation of Biological Networks Across Complex Diseases Using Single-Cell Omics”, First Author, January 2021

Patents

1. Liu Bingqiang, Ma Qin, Li Yang, Wang Yizhong. Method and System for Identifying Transcription Factor Binding Sites Based on de Bruijn Graph: Chinese Patent Application 2023116137751 [P]. 2023-11-29.

Software

1. TESA: Weighted two-stage sequence alignment framework for identifying DNA motifs from Chromatin Immunoprecipitation-exonuclease data (C++)
2. CEMIG: Prediction of cis-regulatory motifs using de Bruijn graph from Assay for Transposase-Accessible Chromatin with sequencing data (C++)
3. STREAM: Enhancer-driven gene regulatory network inference from single-cell RNA sequencing and Assay for Transposase-Accessible Chromatin with sequencing data (R)
4. ProSampler: Ultra-fast and accurate motif discovery in large Chromatin Immunoprecipitation sequencing datasets for combinatorial motif identification (C++)
5. MiMod: Novel algorithm for mining biological network modules (C++)
6. PBlock: Block-based characterization of protease specificity from substrate sequence profiles (C++)

Editorial Work

1. Guest Editor: Frontiers in Genetics
2. Journal Reviewer: Nature, Nature Communications, Genome Biology, Nucleic Acids Research, Briefings in Bioinformatics, Bioinformatics, PLoS Computational Biology, BMC Genomics, BMC Bioinformatics, Computational Biology and Chemistry, Molecular Therapy - Nucleic Acids, Frontiers, Current Bioinformatics
3. Conference Reviewer: IEEE MedAI 2024