The Cake Lab

About Us

Hello! Welcome to The Cake Lab. We are a research group from the Department of Computer Science at Worcester Polytechnic Institute. Our group focuses on optimizing the performance and security of critical and emerging systems, including distributed systems, cloud and mobile applications, and embedded systems.

Our work is generously supported by the National Science Foundation and Google Cloud.


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Tian Guo

Assistant Professor

Robert Walls

Assistant Professor

PhD Students

Sam Ogden

Mobile deep inference

Shijian Li

Distributed training

Yiyang Zhao

Neural architecture search

Xin Dai

Mobile-aware DNN (co-advise with Xiangnan Kong)

Guin Gilman

GPU memory management

Graduate Students

Yiqin Zhao

Mobile augmented reality

Jean-Baptiste Truong

Secure mobile deep learning

Undergraduate Students

Jake Grycel

Systems security

Karitta Zellerbach

Mobile deep inference (2019 REU)

Ioannis Kyriazis

Secure mobile deep learning (2019 REU)

Matt LeMay

Multi-tenant cloud inference


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DNN Model Execution Caching

The *Ripcord* project proposes new research for improving the performance of deep learning model serving. Show More

Confidential and Private Deep Learning on End-user Devices

The CAPR-DL project is exploring new techniques for providing on-device model confidentiality and user privacy. Show More

Mobile-aware Cloud Resource Management

The MOBILESCALE project proposes new research on resource management for mobile workload that differs significantly from traditional cloud workload. Show More

Embedded Systems Security

The embedded systems security project aims to protect critical embedded devices with techniques that lie at the intersection of hardware and software. Show More

Efficient Distributed Deep Learning

The *Cornucopia* project aims at identifying and mitigating the performance bottlenecks of distributed deep learning from both systems and machine learning perspective. Show More

Efficient Mobile Deep Inference

The MODI project proposes new research in designing and implementing a mobile-aware deep inference platform that combines innovations in both algorithm and system optimizations. Show More

Selected Publications

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DRAB-LOCUS: An Area-Efficient AES Architecture for Hardware Accelerator Co-Location on FPGAs

Jacob T. Grycel and Robert J. Walls

IEEE International Symposium on Circuits and Systems


Control-Flow Integrity for Real-Time Embedded Systems

Robert J. Walls, Nicholas F. Brown, Thomas Le Baron, Craig A. Shue, Hamed Okhravi, Bryan C. Ward

31st Euromicro Conference on Real-Time Systems (ECRTS 2019)


Speeding up Deep Learning with Transient Servers

Shijian Li, Robert J. Walls, Lijie Xu, Tian Guo

The 16th IEEE International Conference on Autonomic Computing, arXiv:1903.00045