Lingyun Wang is a researcher on Shopify's Agentic Foundation Modeling team, where he works on agentic AI systems that connect foundation model research, scalable infrastructure, and real-world production impact.

Before joining Shopify, he worked in Amazon Stores Foundational AI, Amazon Ads, Alexa AI, Hulu, and Microsoft, contributing to foundational AI research and large-scale machine-learning-powered products across shopping, advertising, entertainment, recommendation, and conversational AI.

Interests

News

Jul 2026 · Shopify Engineering · New blog

New engineering blog: Teaching Sidekick to say no: automated data curation with LLM judge consensus. We share how consensus across LLM judges turns noisy production interactions into reliable training data, helping a domain-specific Sidekick model recognize impossible requests and refuse them well instead of producing an ungrounded answer.

Jun 2026 · arXiv preprint

New preprint: EARS: Explanatory Abstention for Reliable Sub-Agent Modeling in Large-scale Multi-Agent Systems. We treat sub-agent abstention as an inter-agent communication protocol — instead of over-answering ambiguous or unsupported requests, a sub-agent exposes an actionable failure state to the coordinator for clarification, rerouting, or fallback. On a large-scale e-commerce assistant, EARS raises the response pass rate from 68.5% to 78.9%.

Jun 2026 · NeurIPS 2026 · Workshop proposal

I'm on the organizing committee — together with collaborators from top universities and frontier industry labs — proposing the NeurIPS 2026 Workshop on User and Environment Simulation. We're actively recruiting Program Committee members from diverse backgrounds. If you're interested, please reach out.

Research

Selected publications after 2021, grouped by research area.

Agentic modeling

User and environment simulation

LLM modeling

Multimodal modeling

Invited Talks

NVIDIA GTC 2024

Training Optimization for LLM with NVIDIA NeMo and AWS

A technical session on large language model training optimization with NVIDIA NeMo and AWS.

Watch the session

Blog

Engineering tech blogs.

2,000 robots walk into a shop...

An engineering deep dive into how SimGym was built, scaled, and applied to simulate e-commerce agent behavior, with a focus on inference optimization.

Products

Shipped products with media coverage.

Shopify

Agentic Foundation Modeling

Sidekick — Shopify's AI-powered commerce assistant, helping merchants run and grow their businesses through natural-language guidance and agentic actions.

SimGym — a framework for user behavior simulation in e-commerce with traffic-grounded VLM agents, enabling realistic experimentation before launch.

Coverage: Sidekick 2025 · Sidekick 2026 · SimGym

Amazon · Stores Foundational AI

Foundation Modeling and Inference Optimization

Rufus — Amazon's generative AI–powered conversational shopping assistant, helping customers research products, compare options, and decide what to buy in natural language.

Coverage: Rufus Science · Rufus Product · Rufus Multi Modal

Amazon · Alexa

Recommendation

Alexa Brain — recommendation and personalization behind Amazon Alexa, powering skill discovery and proactive suggestions across hundreds of millions of devices.

Coverage: Amazon Alexa Developer Blog

Patents

Beyond these granted patents, 5+ additional patents covering large language model modeling, evaluation, agentic modeling, and user simulation are currently being filed with the U.S. Patent and Trademark Office.

Education