Yang Li

I am a Ph.D. candidate at Carnegie Mellon University (CMU). My advisor is Prof. José M. F. Moura, member of the National Academy of Engineering. My research areas are deep learning and computer architecture. During my Ph.D. study, I have also worked as a research intern at IBM Research and Microsoft Research.

Before joining CMU, I received an M.S.E. from the University of Texas at Austin and a B.E. from Tsinghua University.

Mailing address: 5000 Forbes Avenue, Hamerschlag Hall Room 1301, Pittsburgh, PA 15213

E-mail: yangli1@andrew.cmu.edu

Research Interests

My research interests include

deep learning, focused on sequence models
computer architecture, especially on resource management for cloud infrastructures

Selected Publications

[HPCA'19]: Y. Li, C. R. Lefurgy, K. Rajamani, M. S. Allen-Ware, G. J. Silva, D. D. Heimsoth, S. Ghose, and O. Mutlu, "A Scalable Priority-Aware Approach to Managing Data Center Server Power," in IEEE International Symposium on High-Performance Computer Architecture, 2019.

The algorithm and architecture proposed in this work will appear in next-generation IBM Cloud.

[EuroSys’18]: C. Xu, K. Rajamani, A. Ferreira, W. Felter, J. Rubio, and Y. Li, "dCat: Dynamic Cache Management for Efficient, Performance-Sensitive Infrastructure-as-a-Service," in ACM European Conference on Computer Systems, 2018.

[IEEE Cluster’17]: Y. Li, S. Ghose, J. Choi, J. Sun, H. Wang, and O. Mutlu, "Utility-based Hybrid Memory Management," in IEEE International Conference on Cluster Computing, 2017.

[HPCA’16]: Y. Li, D. Wang, S. Ghose, J. Liu, S. Govindan, S. James, E. Peterson, J. Siegler, R. Ausavarungnirun, and O. Mutlu, "SizeCap: Efficiently Handling Power Surges for Fuel Cell Powered Data Centers," in IEEE International Symposium on High Performance Computer Architecture, 2016.

[DAC’13]: Y. Li, and D. Z. Pan, "An Accurate Semi-Analytical Framework for Full-Chip TSV-induced Stress modeling," in IEEE/ACM Design Automation Conference, 2013.