Miao Li

Miao Li, Ph.D.

Scientist working at the interface of AI-enabled drug discovery, computational biology, and immunology: deep learning models, AI agents, and single-cell and immune-repertoire pipelines for TCR discovery and cell therapy, grounded in hands-on CAR-T and TCR-T engineering.

miao.li6908@gmail.com LinkedIn GitHub Google Scholar

Experience

2023 – Present

Senior Scientist, AstraZeneca

Gaithersburg, Maryland

  • Architect and lead developer of an AI agent that turns natural-language requests into SLURM-orchestrated NGS pipelines, giving wet-lab scientists self-serve analysis.
  • Built and maintain immune-repertoire and bulk/single-cell RNA-seq pipelines supporting Oncology and Respiratory & Immunology research.
  • Trained a protein-language-model TCR classifier; model-prioritized clones validated at a 35% hit rate against MART-1, recovering clones as rare as 0.0002%.
  • Lead single-cell RNA/TCR-seq analysis for Graves’ disease; narrowed ~3,000 clones to 70 candidates and 18 validated hits for TCR-blockade target selection.
  • Developed a chemically defined, stem cell-derived CAR-T differentiation protocol with >10⁸-fold functional T-cell expansion.

2022 – 2023

Postdoctoral Fellow, University of California, Los Angeles

Los Angeles, California

  • Led single-cell RNA/TCR-seq profiling of conventional CAR-T and stem cell-derived allogeneic CAR-NKT cells against solid tumors — persistence, tumor trafficking, and intratumoral programs — pointing to new CAR/checkpoint-blockade combinations.

2018 – 2022

Postdoctoral Fellow, Indiana University Bloomington

Bloomington, Indiana

  • Applied machine-learning-guided analysis to super-resolution microscopy of macrophage receptors, linking nanoscale receptor organization to innate immune activation.

Selected projects

May 2026 – Oct 2026

FDE Research

Nine agent skills behind one entry point that turn a vague enterprise AI request into a project plan you can defend: evidence first, human sign-off last.

Mar – Aug 2026

NGS Intelligent Workflow Assistant

An AI agent that lets bench scientists run TCR and antibody sequencing pipelines on a shared HPC cluster by describing what they need in plain language.

Sep 2025 – Mar 2026

TCR Pathology Classifier

A deep learning model that ranks T-cell receptors by the disease they are likely associated with, so the lab screens a short list instead of a whole repertoire.

2026

Full-Chain Development Skills

Twenty-one open-source agent skills that walk a project from idea to release — research, PRD, spec, design, test-driven build, and retrospective — with real stop points.

2022 – 2026

CAR-T vs. CAR-NKT in solid tumors

Following two cell therapies through tissues and time to learn why one of them does better in solid tumors — and which checkpoint each one needs.

Education

2013 – 2017

Ph.D., Physics (Dr. rer. nat.)

University of Munich (LMU), Munich, Germany

2011 – 2012

M.Res., Pharmacy

The University of Nottingham, Nottingham, United Kingdom

2006 – 2011

B.Eng., Pharmaceutical Science

Wuhan University of Technology, Wuhan, China

Publications

  1. Y.-R. Li*, M. Li*, Y. Chen, H. Leng, Y. Zhu, … L. Yang. Spatiotemporal profiling reveals distinct dynamics and checkpoint regulations of CAR-T and CAR-NKT cells against solid tumors. Signal Transduction and Targeted Therapy 2026. doi:10.1038/s41392-026-02602-x
  2. F. Yang, A. Yanes, M. Li, P. Heizer, … Z. Guo. Differential regulation of Treg stability in human naïve and effector Treg subsets by TGFβ-signaling via ARKADIA-SKI axis. Frontiers in Immunology 2025, 16. doi:10.3389/fimmu.2025.1636434
  3. Y.-R. Li, Z. Li, Y. Zhu, M. Li, Y. Chen, et al.. Overcoming ovarian cancer resistance and evasion to CAR-T cell therapy by harnessing allogeneic CAR-NKT cells. Med 2025, 6(10). doi:10.1016/j.medj.2025.100804
  4. B. Li, J. Elsten-Brown, M. Li, E. Zhu, et al.. Serotonin transporter inhibits antitumor immunity through regulating the intratumoral serotonin axis. Cell 2025, 188(14):3823–3842. doi:10.1016/j.cell.2025.04.032
  5. Y.-R. Li, Y. Zhou, J. Yu, Y. J. Kim, M. Li, et al.. Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method. Nature Biotechnology 2025, 43(3):329–344. doi:10.1038/s41587-024-02226-y
  6. Y.-R. Li, Z. S. Dunn, Y. Yu, M. Li, P. Wang, L. Yang. Advancing cell-based cancer immunotherapy through stem cell engineering. Cell Stem Cell 2023, 30. doi:10.1016/j.stem.2023.02.009
  7. Y. Zhou*, M. Li*, K. Zhou, J. Brown, T. Tsao, X. Cen, T. Husman, A. Bajpai, Z. S. Dunn, L. Yang. Engineering induced pluripotent stem cells for cancer immunotherapy. Cancers 2022, 14(9):2266. doi:10.3390/cancers14092266
  8. M. Li, C. Vultorius, M. Bethi, Y. Yu. Spatial organization of Dectin-1 and TLR2 during synergistic crosstalk revealed by super-resolution imaging. The Journal of Physical Chemistry B 2022, 126(31):5781–5792. doi:10.1021/acs.jpcb.2c03557
  9. M. Li, S. Lee, M. Zahedian, C. Ding, J. Yan, Y. Yu. Immobile ligands enhance FcγR-TLR2/1 crosstalk by promoting interface overlap of receptor clusters. Biophysical Journal 2022. doi:10.1016/j.bpj.2022.02.010
  10. M. Li, Y. Yu. Innate immune receptor clustering and its role in immune regulation. Journal of Cell Science 2021, 134(4). doi:10.1242/jcs.249318
  11. M. Li, H. Wang, W. Li, X. G. Xu, Y. Yu. Macrophage activation on “phagocytic synapse” arrays: Spacing of nanoclustered ligands directs TLR1/2 signaling with an intrinsic limit. Science Advances 2020, 6:eabc8482. doi:10.1126/sciadv.abc8482
  12. Y. Yu, M. Li, Y. Yu. Tracking single molecules in biomembranes: Is seeing always believing?. ACS Nano 2019, 13:10860–10868. doi:10.1021/acsnano.9b07445
  13. M. Li, T. Lohmüller, J. Feldmann. Optical injection of gold nanoparticles into living cells. Nano Letters 2015, 15(1):770–775. doi:10.1021/nl504497m

* Co-first authors.

Skills

Computational

GenAI, agentic workflows & AI coding tools

Methods
Multi-agent orchestration and end-to-end agentic workflow design for analytics tasks; LLM-based reasoning over study metadata and analysis requests
Tools
Claude Agent SDK, Claude Code, MCP, agent skills, LangChain/LangGraph, RAG
Practice
GenAI coding assistants for project planning, code development, code review, and scientific documentation under spec-driven development
Governance
Human-in-the-loop approval, identity isolation, and audit logging for governed research environments

Programming & reproducible analytics engineering

Languages
Python (primary), R, Shell scripting, UNIX/Linux, Git/GitHub, SLURM/HPC clusters
Practice
Reusable code libraries, version control, QC and reproducibility standards, and FAIR-aligned analytics pipelines built under spec- and test-driven development
Applications
Production-grade web applications (Flask; full-stack TypeScript/React/Node)
Visualization
Data visualization and reporting (Matplotlib, Seaborn, ggplot2, Tidyverse)

Statistical & machine learning methods

Classical ML
scikit-learn (logistic and linear regression, Random Forest, XGBoost, PCA, K-means, DBSCAN)
Deep learning
PyTorch (Transformer, cross-attention, CNN, encoder-decoder); foundation-model fine-tuning (protein language models, ESM2)
Applications
Cohort stratification and endotype discovery; prospective benchmarking and independent validation of model predictions against held-out functional readouts

Large-scale health data analysis

Data
Patient-derived oncology and immune-mediated-disease datasets at scale: bulk and single-cell RNA-seq, scTCR-seq, NGS immune-repertoire profiling
Tools
Cell Ranger, Scanpy, Seurat, MiXCR
Analyses
QC, harmonization, cross-study integration, cohort annotation, differential and pathway analysis, pseudotime and RNA velocity, cell–cell communication, and mechanism interpretation
Data management
Cross-dataset mining, data suitability assessment, and large-scale multi-omics data management

Wet lab

Cellular immunology & CAR-T engineering

Cell culture
Primary cell culture and expansion (HSCs, iPSCs, PBMCs, CAR-T, NK, iNKT, macrophage cells); 2D/3D iPSC differentiation into effector T cells (e.g., CD8⁺ CAR-T)
Engineering
CAR-T and TCR-T engineering; antigen-specific TCR screening
Assays
Multicolor flow cytometry (phenotypic analysis of T-cell markers); ELISA (cytokine release profiling); cytotoxicity and viability assays (e.g., xCELLigence, plate reader-based killing assays)

Molecular biology & gene editing

Gene editing
CRISPR/Cas9-mediated gene knock-in and editing
Cloning
Lentivirus production, packaging, and transduction (CAR-T engineering); molecular cloning (Gibson assembly)
Assays
PCR, genomic DNA extraction, Western blot

Advanced analytics & imaging

Microscopy
Super-resolution (STORM), confocal, TIRF, and epifluorescence microscopy; electron microscopy (SEM, TEM)
Tracking
Bioluminescence imaging (BLI) for in vivo CAR-T tracking; single-molecule tracking
Analysis
Image analysis and quantification (ImageJ)
Biophysics
Nanopatterned surfaces and optical manipulation