Li Shang

Email: lishang@gmail.com


Research Vision

My long-term vision is to build personalized embodied intelligent systems — small, continuously learning and self-evolving artificial agents that understand and interact with the physical world. By bridging machine learning algorithms with system software and silicon, I seek to develop adaptive cyber-physical intelligence that co-evolves with individuals over time, serving as intelligent companions that augment human capability, support lifelong growth, and deepen personal understanding of the world.

Research Directions

1. Bridging Machine Learning Algorithms with System Software and Silicon

Designing vertically integrated AI systems that co-optimize models, compilers, runtimes, and hardware architectures.

2. Efficient Machine Learning Systems

Developing scalable training and inference systems that improve computational efficiency, robustness, and energy-performance tradeoffs.

3. Physical & Embodied Intelligence

Exploring adaptive, physically grounded agents capable of continual learning, perception–action integration, and sustained real-world interaction.


Research Publications

Google Scholar Profile


Teaching

Machine Learning Systems (ML Sys)
Integration of algorithms, system software, and hardware for building efficient and scalable machine learning systems.


Exploratory Thoughts with LLM

From Apprenticeship to Algorithms: What Education Becomes When Knowledge Is No Longer Scarce

From Scale to Rhythm: Nietzsche, Underestimation, and the Architecture of Inner Freedom

Geometry Before Abstraction: Multi-Scale Visual–Spatial Co-Learning

The Architecture of the Unknown: Philosophy, Wisdom, and the Human Edge

The Great Academic Re-Sorting: Research, Leverage, and Rare Minds


Contact

Email: lishang@gmail.com