Helen Xu

Helen Xu is an Assistant Professor at Georgia Tech's School of Computational Science and Engineering (College of Computing). She holds a Ph.D. from MIT (2022) under Charles E. Leiserson and was a Grace Hopper Postdoctoral Fellow at Lawrence Berkeley National Lab (2022). Her research focuses on parallel algorithms, cache-efficient data structures, and high-performance computing. Xu has interned at Microsoft Research, NVIDIA Research, and Sandia National Laboratories, and her work has been supported by prestigious fellowships including the National Physical Sciences Consortium and Chateaubriand awards.

**Education**:

• Ph.D., Computer Science, MIT, 2022
• Postdoctoral Research, Lawrence Berkeley National Lab (2022)

**Research Interests**:

• Parallel and cache-friendly algorithms
• Dynamic graph and data structure optimization
• Algorithm performance engineering
• Sparse matrix/tensor operations

**Awards**: Grace Hopper Postdoctoral Scholar (2022), Best Artifact Award (PPoPP 2024), National Physical Sciences Consortium Fellowship, Chateaubriand Fellowship.

**Advising & Teaching**: Advises PhD/M.S. students in parallel computing and high-performance systems. Teaches courses like CSE 6220 (Introduction to HPC) and CSE 6230 (HPC Tools). Supervised MIT M.Eng. projects on BP-Trees and parallel prefix sums.

**Labs/Teams**: Active in Georgia Tech's High-Performance Computing community, collaborating with researchers like Aydın Buluç and Prashant Pandey on graph containers and dynamic data structures.