Efficient Intelligence and Systems (EIS)

Our group focuses on Efficient Intelligence and Systems, investigating how far we can push the efficiency limits of AI from algorithms down to silicon, with the goal of making intelligence ubiquitous and sustainable. We are particularly interested in advancing modern foundation models and generative AI grounded in real hardware and real-world systems. Our research spans:

Extreme Model Compression

Developing quantization, pruning, and knowledge distillation techniques that reduce model size, memory footprint, and computational cost, with a particular focus on extreme low-bit and binary regimes.

Model Architectures and Inference

Designing neural architectures and inference algorithms with better capability-efficiency trade-offs, especially for reasoning, knowledge integration, and emerging computational paradigms.

AI Hardware and Acceleration

Building hardware accelerators, inference engines, and hardware-aware model designs that translate algorithmic efficiency into real execution on reconfigurable and embedded devices.

Embedded and Robotic Systems

Integrating intelligent models with sensors, wearables, and robotic platforms to enable real-time perception, interaction, and decision-making in the physical world.

Past Mentored Students

PhD Mentees

  • 2024-2026 路 Yujie Chen 路 ETH Z眉rich, with Michele Magno
  • 2025-2026 路 Shuaiting Li 路 Zhejiang University, with Yinghao Xu
  • 2024-2026 路 Nicola Farronato 路 ETH Z眉rich / IBM Research, with Michele Magno
  • 2024-2026 路 Pietro Bonazzi 路 ETH Z眉rich, with Michele Magno
  • 2024-2026 路 Nicolas Baumann 路 ETH Z眉rich, with Michele Magno and Luca Benini
  • 2021-2026 路 Xingyu Zheng 路 Beihang University, with Xianglong Liu
  • 2023-2026 路 Weilun Feng 路 Beihang University & Chinese Academy of Sciences, with Chuanguang Yang
  • 2022-2025 路 Wei Huang 路 Beihang University & The University of Hong Kong, with Xiaojuan Qi
  • 2021-2025 路 Xudong Ma 路 Beihang University, with Jie Luo

Master / Undergraduate Mentees

  • 2025-2026 路 Tianren Gu 路 ETH Z眉rich, with Yawei Li and Luca Benini
  • 2025-2026 路 Vasileios Arailopoulos 路 ETH Z眉rich, with Michele Magno
  • 2024-2025 路 Paviththiren Sivasothilingam 路 ETH Z眉rich, with Michele Magno
  • 2025 路 Stefan Zihlmann 路 ETH Z眉rich, with Michele Magno
  • 2025 路 Maxime Girard 路 ETH Z眉rich, with Michele Magno
  • 2025 路 Raphael Vogt 路 ETH Z眉rich, with Michele Magno
  • 2025 路 Ronan Lebas 路 ETH Z眉rich, with Michele Magno
  • 2025 路 Rafael Sutter 路 ETH Z眉rich, with Michele Magno
  • 2025 路 Chandra Duhra 路 ETH Z眉rich, with Michele Magno
  • 2024-2026 路 Yihua Shao 路 CASIA, with Hao Tang and Jingcai Guo; incoming PhD at Trento
  • 2025-2026 路 Tianrui Zhu 路 Nanjing University, with Kai Zhang; incoming PhD at Nanjing University
  • 2022-2024 路 Aoyu Li 路 Beihang University, with Xianglong Liu; now Tencent
  • 2025-2026 路 Haoran Chu 路 Beihang University, with Xianglong Liu
  • 2025-2026 路 Yue Feng 路 Beihang University, with Xianglong Liu
  • 2025-2026 路 Chengyuan Deng 路 Beihang University, with Xianglong Liu; incoming PhD at Zhejiang University
  • 2025-2026 路 Yuye Li 路 Beihang University, with Xianglong Liu; incoming PhD at Zhejiang University
  • 2020-2023 路 Hong Chen 路 Beihang University, with Xianglong Liu