Goal and Mission
Leading the role in leveraging AI accelerators for cryptographical acceleration such as Fully Homomorphic Encryption to achieve better energy efficiency and faster performance compared to existing CPU, GPU, and FPGA.
Cloud Providers like Google and IBM will purchase US for ensuring real-time privacy protection in untrusted cloud environments.
Contact: jtong45@gatech.edu
Meet our amazing team.
We’re a talented group of creative individuals interested in Computer Architecture, Full-stack Privacy-preserving Machine Learning Serving. Get to know us and what we can do for you!
Jianming Tong
Ph.D. (Georgia Tech)
Researcher (MIT)Jianming Tong is a CS Ph.D. student at Georgia Institute of Technology starting from Spring 2021, advised by Prof. Tushar Krishna . His research is funded by Qualcomm Innovation Fellowship and SRC Jump 2.0. His primary research area is Computer Architecture with major interest on software-system-hardware full-stack optimizations for privacy-preserving and performance-oriented AI workloads, i.e. make both AI and privacy-preserving AI faster and more efficient.
Zishen Wan
Ph.D. (Georgia Tech)
Zishen Wan is a 4th-year Ph.D. student at Georgia Tech, advised by Prof. Arijit Raychowdhury and Prof. Tushar Krishna. I also closely work with Prof. Vijay Janapa Reddi. His research interests are in computer architecture and VLSI, with a focus on designing efficient and reliable hardware and systems for autonomous machines and cognitive intelligence.
Jingtian Dang
Ph.D. (Georgia Tech)
Jingtian Dang is an incoming Ph.D. student at Georgia Tech. He focuses on accelerating Fully Homomorphic Encryption and Zero-Knowledge Proof via model-system-hardware co-design.
Get a project quote today!
We plan to launch our product within six months and are seeking new pilot partners and investors. Let’s build something together!