Lily Zhang

Lily Zhang

I’m Lily Zhang, a Tech Lead and Research Scientist in the Bay Area, California. My research focus is: post-training and AI training data. I’ve published at CVPR, ICCV, NeurIPS, RAL [1] [2] [3] [4] [5], and gave a keynote at NVIDIA GTC.

At Latitude AI, I build LLMs, multimodal LLMs, and AI agents for physical AI (Modal GTC panel on agentic post-training). Previously, I led applied R&D at Ford Greenfield Labs (2019–2023) on building perception models and AI training data (IROS keynote).

My latest research (colab w AliCloud) reframes feature engineering as agentic code generation, SFT + RL post-trained AI-infra agent deployed at Alibaba Cloud with 91% adoption (poster at NeurIPS 2025 VLM4RWD, oral at DASFAA 2026). Publishing as Xianling Zhang.

Status quo

Is Speculative Decoding All We Need?
Poster AI Engineer World's Fair 2026
Is Speculative Decoding All We Need? — AI Engineer World's Fair
Eureka: SFT + RL Post-trained AI-Infra Agent
Paper Poster NeurIPS 2025 VLM4RWD, DASFAA 2026
Eureka NeurIPS 2025
Learn Meta Skill: Compositional Tool Environments for Long-Horizon Agents
Project Code RL Environments on Tool Use
SuperGeneral
SofaGenius: Orchestrate Agentic Post-Training
Code Video Top 15/13k finalist in Anthropic Global Hackathon
SofaGenius
Frontend Slides: AI-Native Presentation Generation
25K+ GitHub stars. Frontend Slides that's anti-slop
Frontend Slides
Skill Claw: Self-Improving Robot Agents
RL environments that train code policy
Skill Claw
General Chair for IROS 2025 RoboGen Workshop
Call for Papers IEEE IROS 2025 Conference
IROS Workshop
From Lab to Road: Turning Self-Driving Research into Production Features
Article IROS 2023 Novel Sensor Workshop Keynote
IROS 2023 Keynote
Diversify AI Training Data
NVIDIA GTC Conference
NVIDIA GTC Talk on Scene Relighting
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