Lisa Wills

Clare Boothe Luce Assistant Professor of Computer Science and Electrical and Computer Engineering

Appointments and Affiliations

  • Assistant Professor of Computer Science

Contact Information


  • Ph.D. Columbia University, 2014

Research Interests

I enjoy solving difficult problems surrounding computations with the goal to process large volumes of data efficiently. My research interests include computer architecture and microarchitecture, hardware-software co-designs, accelerators, and emerging application domains ― especially those in big data analytics such as genomics, graphs, and databases. One of my research goals is to greatly simplify the design, deployment, and usage of custom hardware and to leverage this research in hardware acceleration to advance state-of-the-art research in the healthcare domain as well as other natural sciences.

Courses Taught

  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 552: Advanced Computer Architecture I
  • ECE 494: Projects in Electrical and Computer Engineering
  • COMPSCI 590: Advanced Topics in Computer Science
  • COMPSCI 550: Advanced Computer Architecture I
  • COMPSCI 210D: Introduction to Computer Systems

In the News

Representative Publications

  • Xu, C., P. Sharma, T. Wang, and L. W. Wills. “Fast, Robust and Transferable Prediction for Hardware Logic Synthesis.” In Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2023, 167–79, 2023.
  • Alcorta, E. S., A. Gerstlauer, C. Deng, Q. Sun, Z. Zhang, C. Xu, L. W. Wills, et al. “Special Session: Machine Learning for Embedded System Design.” In Proceedings - 2023 International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 2023, 28–37, 2023.
  • Xu, C., C. Kjellqvist, and L. W. Wills. “SNS's not a Synthesizer: A Deep-Learning-Based Synthesis Predictor.” In Proceedings - International Symposium on Computer Architecture, 847–59, 2022.
  • Robson, E., C. Xu, and L. W. Wills. “Prose: The architecture and design of a protein discovery engine.” In International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS, 655–68, 2022.
  • Ang, P., B. Dhingra, and L. W. Wills. “Characterizing the Efficiency vs. Accuracy Trade-off for Long-Context NLP Models.” In NLP-Power 2022 - 1st Workshop on Efficient Benchmarking in NLP, Proceedings of the Workshop, 113–21, 2022.