VeriMake
Embodiverse

Building silicon life, layer by layer

VeriMake builds silicon life from the ground up — the chips it thinks with, the data it learns from and the bodies it acts through. Today we design edge accelerators, capture real-world experience with our EGO devices, and build robots that work alongside people in everyday places.

About the team Join us

Research Areas

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01

Domain-Specific Accelerators

  • FPGA
  • Low-precision arithmetic
  • LLM quantization
  • AI for EDA
 02

Edge Perception & Interaction

  • Multimodal perception
  • On-device inference
  • Speech interaction
  • HCI
 03

Robot Bodies & Robot Learning

  • Robot platforms
  • Embedded control
  • Robot learning
  • Manipulation
 04

Real-World Data & Collective Learning

  • Egocentric data
  • Robot learning datasets
  • Open hardware

Ongoing Projects

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Classroom Assistant Robot

An in-house R&D project — a humanoid teaching-assistant robot for K-12 language classrooms, starting with English, that explains, asks, listens and gestures alongside the teacher.

Lyra: AI Creative Collaboration for Music Makers

An AI music-creation tool, founded by Chenye Wang, that turns a prompt, a recording or a MIDI sketch into editable tracks — so creators can shape music by the feeling they want, not by technical vocabulary.

Selected Publications

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  1. Journal
    Vina-FPGA-Cluster: Multi-FPGA Based Molecular Docking Tool With High-Accuracy and Multi-Level Parallelism
    Ming Ling, Zhihao Feng, Ruiqi Chen, Yi Shao, Shidi Tang, Yanxiang Zhu
    IEEE Transactions on Biomedical Circuits and Systems, 2024
    DOI
  2. Conference
    Graph-OPU: An FPGA-Based Overlay Processor for Graph Neural Networks
    Ruiqi Chen, Haoyang Zhang, Yuhanxiao Ma, Enhao Tang, Shun Li, Yanxiang Zhu, Jun Yu, Kun Wang
    FPGA '23: The 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2023
    DOI
  3. Journal
    Vina-FPGA: A Hardware-Accelerated Molecular Docking Tool With Fixed-Point Quantization and Low-Level Parallelism
    Ming Ling, Qingde Lin, Ruiqi Chen, Haimeng Qi, Mengru Lin, Yanxiang Zhu, Jiansheng Wu
    IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2023
    DOI