I graduated from my PhD at MIT in 2020. I was fortunate to be advised by Virginia Vassilevska Williams.
I hope to build and refine theoretical models that crystallize concerns about complex systems. I strive to build networks of reductions that give shared explanations for the hardness of problems.
Research Interests: Fine Grained Complexity, Average-Case Complexity, Lower Bounds, Algorithms.
How Compression and Approximation Affect Efficiency in String Distance Measures
Andrea Lincoln, Adam Yedidia
ICALP 2020 [Invited to special issue of Theory of Computing Systems]
Closing the Gap Between Cache-oblivious and Cache-adaptive Analysis
Andrea Lincoln and Nikhil Vyas
Cache-Adaptive Exploration: Experimental Results and Scan-Hiding for Adaptivity