Dr. Xuanle Ren joined the School of Information Science and Technology at ShanghaiTech University in November 2024 as an Assistant Professor, Principal Investigator, and Ph.D. Advisor. He received his Bachelor's degree from Peking University (2012) and his Ph.D. from Carnegie Mellon University (2018), under the supervision of Professor Shawn Blanton. His research focuses on privacy-preserving computing hardware-software co-design. 

After completing his Ph.D., Dr. Ren worked as a research scientist at Alibaba DAMO Academy and Bitmain, where he conducted research in the fields of privacy-preserving computing and chip design, successfully translating technological advancements into industrial applications. 

To date, he has published over 10 papers in top-tier conferences and journals such as DAC, DATE, TCAD, and VLDB, and has filed 18 patents in China and the U.S. Additionally, he has received several prestigious honors, including the Shanghai Elite Industrial Talent Award and the National Award for Outstanding Self-Financed Students Abroad. He has also been recognized as a Senior Engineer in the Integrated Circuit Engineering Series in Shanghai.

In the era of big data, data has become the driving force behind an increasing number of applications. However, acquiring data is not always straightforward, and sharing it is often prohibited for certain organizations, such as healthcare systems, banks, and governments. Privacy-preserving computation seeks to address this issue by enabling the sharing of only encrypted data, thus preventing the exposure of sensitive information. To achieve this goal, the community has developed several protocols and algorithms, including secure multi-party computation, homomorphic encryption, and federated learning. These approaches allow multiple parties to collaboratively train a shared predictive model with minimal data exchange. However, these algorithms often incur significant computational overhead. Designing efficient and practical algorithms, software, and hardware remains a critical research challenge.

Therefore, my research focuses on the following topics:

• Homomorphic Encryption (HE) algorithm and architecture design, especially heterogeneous system design

• Algorithm and protocol design for privacy preservation

• Privacy-preserving systems based on trusted execution environments (TEEs)

• AI-driven EDA algorithm design