Papers

2

Total Citations

12

H-Index

2

About

Qilin Chen is a pioneering researcher at the intersection of computer architecture and smart materials, whose work bridges hardware acceleration for artificial intelligence with bio-inspired flexible systems. His primary research areas include many-core processor design for deep neural network (DNN) inference and stimulus-responsive flexible actuators. Chen’s most notable contribution is the development of MAICC, a lightweight many-core architecture that leverages in-cache computing to enable efficient multi-DNN parallel inference—a critical advancement for autonomous driving and intelligent robotics, where diverse neural networks must run simultaneously with low latency. This work has garnered 9 citations since its 2023 publication, highlighting its growing influence in the field of domain-specific computing. Additionally, Chen has explored smart bionic applications through a GO-PDANP/PDMS bilayer flexible actuator, which responds to multiple stimuli to produce mechanical motion, earning 3 citations and demonstrating potential in biosensors and soft robotics. His interdisciplinary approach—combining hardware efficiency with material innovation—positions him as a rising figure in next-generation computing and intelligent systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
MAICC : A Lightweight Many-core Architecture with In-Cache Computing for Multi-DNN Parallel Inference
9 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Tsinghua University, Wuhan University of Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago