Liam Li | ML Research Scientist
Research Scientist at Pokee AI
I build intelligent agents for deep research and workflow automation.
Previously, I was an early employee at Determined AI, a Series A startup acquired by HPE, where I led our ML efforts. I have a PhD in Machine Learning from Carnegie Mellon University with over 6,000 citations.
Experience
Building intelligent agents for workflow automation. Developing AI systems that can understand, plan, and execute complex multi-step tasks.
Pre-seed startup building task-specific language models.
Led enterprise LLM solutions including inference services, RAG systems, and finetuning pipelines. Designed DeepSpeed training APIs enabling billion-parameter distributed training. PI on ICML oral paper for cross-modal foundation model finetuning.
LLM Infrastructure RAG Distributed Training DeepSpeed
Advised by Ameet Talwalkar. Thesis on efficient methods for automating machine learning. Developed Hyperband and ASHA algorithms. CMU MLD TA Award. GPA: 4.0/4.0.
AutoML Hyperparameter Optimization Neural Architecture Search
Developed open-source active learning library with 1k+ GitHub stars. Created mixture-based batch active learning methods.
Research Highlights
ORCA
ICML 2023
A general cross-modal fine-tuning framework that extends a single large-scale pretrained model to diverse modalities. Enables efficient transfer learning across vision, language, and other domains.
Neural Architecture Search
ICLR 2021 (Spotlight) · UAI 2019
Geometry-aware gradient algorithms for NAS achieving near-oracle-optimal performance. Established random search as a strong baseline, improving reproducibility standards in the field.
ASHA
MLSys 2020
A system for massively parallel hyperparameter tuning that scales linearly with workers. Converges to high-quality configurations in half the time of Google's Vizier with 500 workers. Powers distributed tuning at scale.
Hyperband
JMLR 2018 · ICLR 2017
A bandit-based approach to hyperparameter optimization that provides over an order-of-magnitude speedup through adaptive resource allocation and early-stopping. Foundational algorithm implemented in all major HP tuning libraries.