Undergraduate Researcher
CurrentResearch focus: Computational Neuroscience/Biology, Computer Science, & Data Science.Working on Arkouda project and developing new network centrality measures.Helping to create documentation and guides to open-source projects, such as Arkouda, as well as creating interactive notebooks demonstrating the advantages of massively paralleled programs (such as Arkouda) as compared to other open-source network analysis tools (such as NetworkX).Working on a collaborative project with Harvard to conduct netowrk analysis and Motif Finding on a petabyte-scale data set containing every neuron of a fruit fly connectome fully sequenced. To achieve this, new algorithms using Breadth First Search (BFS) and parallel programming techniques are leveraged to enhance computational efficiency and ultimately develop new subgraph isomorphism algorithms implemented in Chapel.Conducted literature reviews, implemented and ran existing algorithms, and conducted extensive analyses on speedup and execution comparison.
