SimGym: A Framework for A/B Test Simulation in E-Commerce with Traffic-Grounded VLM Agents has been accepted to the COLM 2026 Workshop on Agent Behavior. SimGym grounds browser agents in real traffic to forecast how storefront changes affect buyer behavior, shortening experimentation from weeks to under an hour without exposing real shoppers to untested variants.
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
SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agents has been accepted to the COLM 2026 Workshop on Learning from Situated and Embodied Interaction. SimPersona learns compact buyer types directly from clickstreams, giving web agents grounded and diverse behavior while preserving each merchant's real buyer distribution.
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.
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%.
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.
Our paper, ShopGym: An Integrated Framework for Realistic Simulation and Scalable Benchmarking of E-Commerce Web Agents, has been accepted to the ICML 2026 RLxF Workshop, with open-source code released.
Research
Selected publications after 2021, grouped by research area.
Agentic modeling
EARS: Explanatory Abstention for Reliable Sub-Agent Modeling in Large-scale Multi-Agent Systems
Abstention as an inter-agent communication protocol — sub-agents expose actionable failure states for clarification, rerouting, or fallback.
User and environment simulation
SimGym: A Framework for A/B Test Simulation in E-Commerce with Traffic-Grounded VLM Agents
Traffic-grounded browser agents for simulating e-commerce A/B tests.
ShopGym: An Integrated Framework for Realistic Simulation and Scalable Benchmarking of E-Commerce Web Agents
Realistic, reproducible storefront simulation and benchmark generation for web agents.
Code: GitHub
SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agents
Buyer persona modeling from clickstreams for grounded synthetic shopping agents.
LLM modeling
LongLeader: A Comprehensive Leaderboard for Large Language Models in Long-context Scenarios
Benchmarking long-context comprehension across large language models.
An Exploration of Speech Conditioned Large Language Models (SLMs)
Design-space exploration for speech-conditioned LLMs and spoken instruction following.
Multimodal modeling
M-LLM Based Video Frame Selection for Efficient Video Understanding
Adaptive frame selection for efficient video reasoning with multimodal large language models.
Multimodal Instruction Tuning with Hybrid State Space Models
Hybrid transformer-Mamba modeling for long-context multimodal instruction tuning.
Invited Talks
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 sessionBlog
Engineering tech blogs.
Teaching Sidekick to say no: automated data curation with LLM judge consensus
Using consensus across LLM judges to curate training data at scale and teach domain-specific models when—and how—to refuse impossible requests.
Flow generation through natural language: an agentic modeling approach
Bringing agentic modeling from idea to production, with the lessons learned along the way.
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.
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
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
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
Computer-Implemented Methods for Machine Learning Model Based Spatial-Temporal Adaptive Shift for End-to-End Text-Video Retrieval
Spatial-temporal shifting for text-video retrieval and video search matching.
Enhanced Shopping Based on Recognition of Objects Presented in Video
Object recognition in video for smart shopping and product discovery experiences.
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
Virginia Tech
M.S., Computer Engineering, earned in the Ph.D. program
Advisor: Prof. Robert P. Broadwater