# Zhirui Luo > AI Researcher & Engineer | Agentic AI, Multimodal Foundation Models, Clinical Decision AI | Postdoc @ NCI Location: Baltimore, Maryland, United States Profile: https://flows.cv/zhiruiluo I am an AI researcher and engineer focused on building intelligent systems that combine reasoning, perception, and real-world decision-making. My work sits at the intersection of large-scale deep learning, multimodal foundation models, and agentic AI systems, with a strong emphasis on translating research innovations into deployable, high-impact applications. My primary research explores how AI can extract meaningful knowledge from complex biomedical data. I design multimodal models that integrate histopathology imaging, molecular profiling, and clinical signals to improve cancer classification, understand tumor heterogeneity, and support precision diagnostics. My recent work also extends into safety-critical AI, where I develop multi-agent reasoning systems and retrieval-augmented large language model pipelines for clinical decision support. Beyond healthcare, I am deeply interested in building scalable AI infrastructure and production-ready machine learning systems. I have experience developing distributed training pipelines, large-scale evaluation frameworks, and model deployment architectures across HPC and cloud environments. I enjoy working on problems that require combining model innovation with systems engineering and practical deployment. More broadly, I am motivated by advancing AI systems that move beyond pattern recognition toward robust reasoning, multimodal understanding, and real-world impact. I am particularly interested in applications of agentic AI, foundation model alignment, and decision-support systems across healthcare and other high-stakes domains. 📩 Contact: zhirluo@gmail.com ## Work Experience ### Postdoc Fellow @ National Cancer Institute (NCI) Jan 2024 – Present | Bethesda, Maryland, United States I develop multimodal AI and large-scale deep learning systems to advance cancer diagnostics, clinical decision support, and safety-critical medical AI. My work focuses on combining foundation models, multimodal data integration, and reasoning-based AI systems to improve real-world clinical workflows. Key Contributions • Designed multimodal deep learning models integrating histopathology imaging, DNA methylation, gene expression, and clinical data to improve CNS tumor classification and characterize spatial tumor heterogeneity • Developed transformer-based vision models and multiple-instance learning frameworks achieving state-of-the-art performance in multi-institutional tumor classification benchmarks • Built agentic clinical reasoning systems using large language models and retrieval-augmented generation (RAG) to support Emergency Severity Index (ESI) triage, reducing safety-critical under-triage events while improving diagnostic accuracy • Architected scalable ML infrastructure including distributed training pipelines, large-scale evaluation frameworks, and automated benchmarking workflows across HPC and cloud environments • Designed production-oriented deployment pipelines with containerization, CI/CD automation, and real-time inference optimization for clinical decision-support applications ### Graduate Teaching Assistant @ New Mexico Institute of Mining and Technology Jan 2018 – Jan 2024 | Socorro, New Mexico Area Computer Networks Principle of Programming Languages Compiler Writing Operating Systems Sensor Networks Python ### Graduate Research Assistant @ New Mexico Institute of Mining and Technology Jan 2018 – Jan 2024 | Socorro, New Mexico Area Concentration: Deep Learning, Data analytics, High performance computing Committee member: Jun Zheng, Subhasish Mazumdar, Ramyaa, Sihua Shao Membership: NSF EPSCoR Member, HCCS lab, NMIMT Ph.D. Dissertation: Deep Learning Methods for Smart Meter Data Analytics and Applications ### Instructor @ Upward Bound Math and Science at New Mexico Tech Jan 2022 – Jan 2022 | Socorro, NM Developed and taught a 6-weeks Python course for high-school students ### Software Engineer @ Zhejiang Guozi Robotics Jan 2018 – Jan 2018 | Hangzhou, Zhejiang, China Involved in a multi-robot logistic system for warehouse management. Solved traffic deadlock problems caused by maps design and traffic control. Drove software development across multiple teams. ### Undergraduate Research Assistant @ New Mexico Institute of Mining and Technology Jan 2016 – Jan 2017 | Socorro, New Mexico Project 1: Developed a full-stack bone drilling surgery training system for medical students. Project 2: Performed data analysis on surgery training data for evaluting skill-level of students. ## Education ### Doctor of Philosophy - PhD in Computer Science New Mexico Institute of Mining and Technology ### Master's degree in Computer Science New Mexico Institute of Mining and Technology ### Bachelor of Science - BS in Computer Science New Mexico Institute of Mining and Technology ### Bachelor of Science (B.S.) in Software Engineering Yangtze University ## Contact & Social - LinkedIn: https://linkedin.com/in/luobill2017 - Portfolio: https://zhiruiluo.github.io - GitHub: https://github.com/zhiruiluo - Portfolio: https://scholar.google.com/citations?user=2Up7L00AAAAJ&hl=en --- Source: https://flows.cv/zhiruiluo JSON Resume: https://flows.cv/zhiruiluo/resume.json Last updated: 2026-04-17