Laxman Dhulipala

Laxman Dhulipala serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, while also working as a research scientist at Google Research with the Graph Mining team.

Dr. Dhulipala earned his Ph.D. from Carnegie Mellon University under Guy Blelloch's supervision and completed a postdoctoral fellowship at MIT with Julian Shun. His research centers on efficient parallel algorithms, particularly for parallel clustering and graph processing, along with developing computational models for emerging hardware technologies.

His scholarly output demonstrates significant expertise across parallel computing domains, with particular emphasis on scalable graph algorithms, dynamic data structures, and computational geometry. Dr. Dhulipala's work bridges theoretical computer science with practical systems implementation, producing algorithms that achieve both theoretical optimality and real-world performance.

His research group has made substantial contributions to benchmarking frameworks including the Graph Based Benchmark Suite (GBBS) and ParClusterers Benchmark Suite, establishing standardized evaluation methods for graph processing systems. The collective work shows progression from theoretical foundations to practical implementations that handle massive-scale datasets.

• Best Paper Award at SPAA 2022
• Best Paper Runner Up at VLDB 2022
• Distinguished Paper Award at PLDI 2019
• Memorable Paper Award Finalist at NVMW'20
• CMU's SCS Dissertation Award Honorable Mention

As an educator, Dr. Dhulipala mentors numerous graduate students while teaching advanced courses in algorithm design and parallel computing. His research collaborations span multiple institutions including Carnegie Mellon University, MIT, and Google Research, reflecting his position at the intersection of academia and industry research.