Kefu Lu Assistant Professor of Computer Science

Kefu Lu

Parmly 412
540-458-8813
klu@wlu.edu
Website - Curriculum Vitae

Education

Ph.D., Computer Science at Washington University in St. Louis (2019)

B.A. Physics and Computer Science from Washington University in St. Louis (2014)

Research

Research Interests include approximation algorithms, parallel computing, machine learning and data analysis.

Current Research:
As computers become more and more parallel, Professor Lu is interested in how to best harness the power of these complex systems. Professor Lu seeks to develop faster and more efficient algorithms for data analysis methods. His recent works include developing distributed algorithms for data clustering, finding approximation algorithms in the massively parallel model, and analyzing online scheduling algorithms for optimizing the performance of parallel processors.

Teaching

Professor Lu teaches the introductory computer science courses, data structures, algorithms, and upper-level electives focused on parallel computing, optimization, and large-scale data analysis - including a new course on Cloud Computing. He is the primary instructor for all courses in theoretical computer science such as the Theory of Computation and the Analysis of Algorithms.

Selected Publications

Authors are ordered alphabetically by convention in theoretical computer science.

  • Kefu Lu, Mason Marchetti. "Maximizing Throughput for Parallel Jobs with Speed-up Curves". Workshop on Approximation and Online Algorithms (WAOA '24).
  • Jeremy Buhler, Thomas Lavastida, Kefu Lu, Benjamin Moseley. "A Scalable Approximation Algorithm for Weighted Longest Common Subsequence". European Conference on Parallel Processing (Euro-Par '21), pages 368-384.
  • Silvio Latanzi, Thomas Lavastida, Kefu Lu, Ben Moseley. "A Framework for Paralleling Hierarchical Clustering Methods". Machine Learning and Knowledge Discovery in Databases:  European Conference (ECML PKDD '19), pages 73-89.
  • Kunal Agrawal, Jing Li, Kefu Lu, Ben Moseley. "Scheduling Parallelizable Jobs to Maximize Throughput". Latin American Symposium on Theoretical Informatics (LATIN '18), pages 755-776.
  • Shalmoli Gupta, Ravi Kumar, Kefu Lu, Ben Moseley, Sergei Vassilvitskii. "Local Search Methods For k-means With Outliers". Proceedings of the VLDB Endowment (VLDB '17), pages 757-768.