Charlie Yang

About

I’m a software engineer at AWS Kiro, where I work on agentic AI developer experiences.

Alongside product engineering, I contribute to medical imaging and AI agent research at the University of Colorado Anschutz School of Medicine. I enjoy turning ambiguous research problems into dependable products—balancing technical depth with usability, performance, and clean execution.

Highlights

• At AWS Kiro, designing an AI automation framework for agent-driven workflows—standardizing multi-step tool calling and orchestration (MCP), execution state management, and failure recovery for reliable long-running agent sessions.
• Evolving LLM context and memory systems (compaction, retrieval, context scheduling under token budgets), reducing inference cost and latency while preserving response quality.
• As an intern, designed and shipped Kiro IDE's core distributed context compaction system—hierarchical compression with RAG on Amazon S3 Vectors and OpenSearch Serverless, achieving 80–90% compression—and drove its production launch serving 100K+ users.
• Contributor to KiroCrew, an open-source multi-agent workspace built on kiro-cli and the Agent Client Protocol (ACP): session-resilience, redaction, and sandboxing improvements.
• Research on reliable AI for medical imaging: reliability stress tests and decision-time routing for chest X-ray vision–language models (CHASE 2026) and confidence-gated cloud–edge cascade triage (Smart Health, 2026), plus a U.S. provisional patent on an intelligent radiology reporting platform.
• Earlier, built a real-time ICU patient monitoring system at the Chinese Academy of Sciences, Institute of Automation, securing a software patent and a national grant.

Experience

• Software Development Engineer, Amazon Web Services · Kiro

  Jul 2026 – Present · Seattle, WA

  Building agentic AI developer experiences and evolving the context systems that make long-running workflows more capable, reliable, and intuitive.

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• Research Assistant, University of Colorado Anschutz School of Medicine

  Jul 2026 – Present · Remote

  Researching medical imaging and AI agents in a remote, part-time role.

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• Software Engineer Intern, Amazon Web Services · Kiro

  Jun 2025 – Aug 2025 · Seattle, WA

  Led the design and productization of a modular context management system combining hierarchical compaction, memory, and retrieval.

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• Research Intern, Brown University Health

  Mar 2025 – Aug 2025 · Providence, RI

  Developed an AI-powered medical imaging platform for report generation, image analysis, and clinical comparison workflows.

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Earlier experience

• 2024 – 2025 · Personal Trainer, Brown University Athletics · View details
• 2024 – 2025 · Lead Web Developer & Designer, Rhode Island Coalition for Israel · View details
• 2024 · Algorithm Engineering Intern, Shukun Technology · View details
• 2023 – 2024 · Software & ML Engineer Intern, Chinese Academy of Sciences · View details
• 2023 · Research Intern, University of Science and Technology Beijing · View details
• 2022 · Research Intern, Nanyang Technological University · View details

Academic

Research interests: Multimodal LLMs · Medical Image Analysis · AI in Healthcare · Agentic AI

Citations: 47 · h-index: 2 · i10-index: 1 · View Google Scholar
Updated September 2026

Publications

Metrics and publication citations are synchronized from Google Scholar.

• Reliability Stress Tests and Decision-Time Routing for Chest X-ray Vision-Language Models X Yang, Z Zhong, S Collins, G Baird, X Wang, Z Jiao 2026 IEEE/ACM Conference on Connected Health: Applications, Systems and Technologies, 2026.
• Confidence-gated cloud-edge cascade triage via variational risk minimization for medical imaging X Yang, Z Zhong, S Collins, M Bernstein, G Baird, T Healey, M Atalay, et al. Smart Health · 100689, 2026.
• A Unified Platform for Radiology Report Generation and Clinician-Centered AI Evaluation Z Ma, X Yang, Z Atalay, A Yang, S Collins, H Bai, M Bernstein, G Baird, et al. medRxiv · 2025.07.07.25331018, 2025. cited by 1
• The AI Challenge: A Turing Test Pilot Study of Attendings and Residents in Identifying AI-Generated Content Z Ma, X Yang, Z Atalay, Z Zhong, S Collins, H Bai, M Bernstein, A Pandey, et al. Meta-Radiology · 100199, 2025.
• Understanding the brain with attention: A survey of transformers in brain sciences C Chen, H Wang, Y Chen, Z Yin, X Yang, H Ning, Q Zhang, W Li, R Xiao, et al. Brain-X · 1(3), e29, 2023. cited by 44
• Optimization of CNN for Diagnosis on Lung Disease by Lung Segmentation and Rib Suppression X Yang, Y Liu, Z Lin, L Zhong, TT Toe 15th International Symposium on Computational Intelligence and Design, 2022. cited by 2

Education

• Master of Science in Computer Science, Brown University

  2024 – 2026

  Focus on AI, machine learning, and software systems.

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• Bachelor of Engineering in Artificial Intelligence, University of Science and Technology Beijing

  2020 – 2024

  Graduated with honors · GPA 3.83/4.0.

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Skills

• Languages: TypeScript · JavaScript · Python · Java · C/C++ · SQL · Go
• AI & Data: LLM Systems · RAG · MCP · PyTorch · TensorFlow · Computer Vision
• Frameworks: React · Node.js · Flask · Spring Boot · MySQL
• Tools: AWS · Docker · Git · Google Cloud · Vite · Figma

Contact

I’m always glad to connect with people working on thoughtful AI products, developer tools, and healthcare technology.

charlieyangxinye@gmail.com · LinkedIn · Google Scholar · GitHub