Cheng Chu
Computer Science · Indiana University
Publications
13
Citations
70
Est. group size
—
Recurring co-author estimate
Active years
21
Publishing since 2004
Cheng Chu works on computer hardware and architecture for artificial intelligence and emerging computing systems. Their research includes designing specialized accelerators (custom chips) to run deep learning more efficiently and reliably, as well as architectures for quantum computing and processing-in-memory systems. The overall focus is on making advanced computation faster, more energy-efficient, and fault-tolerant.
Publication activity has been relatively low and intermittent over the past decade, with a peak around 2020-2021 and occasional output since.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- TITAN: A Fast and Distributed Large-Scale Trapped-Ion NISQ Computer
2024
- Accelerating Deformable Convolution Networks with Dynamic and Irregular Memory Accesses
ACM Transactions on Design Automation of Electronic Systems · 2023
- HyCA: A Hybrid Computing Architecture for Fault-Tolerant Deep Learning
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2021
- Energy-Efficient Accelerator Design for Deformable Convolution Networks
arXiv (Cornell University) · 2021
- HyCA: A Hybrid Computing Architecture for Fault Tolerant Deep Learning
arXiv (Cornell University) · 2021
- RECOIN
2021
- A Hybrid Computing Architecture for Fault-tolerant Deep Learning Accelerators
2020
- Multi-task Scheduling for PIM-based Heterogeneous Computing System
2020
- arXiv (Cornell University)×2
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems×1
- ACM Transactions on Design Automation of Electronic Systems×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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