Unifying puzzles in social, technical, and biological systems using networks
Dissertation proposal
Kishore Vasan
PhD Student
Past Talk
Hybrid talk
Friday
Apr 26, 2024
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2:30 pm
EST
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177 Huntington Ave.
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
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The foundation of scientific progress lies in unraveling the phenomena, or puzzles, that characterize every scientific discipline. Despite the apparent differences between these puzzles across fields, they share a common thread: the potential for resolution through networks as a shared toolset and methodological approach. Using data from social, technical, and biological systems, the proposed dissertation showcases the value of network-based thinking under different constraints. In the first proposed project, I use the protein-protein interaction (PPI) network, a sub-cellular web that is used by pharmaceutical scientists to develop drugs, and study the emergence of a drug discovery winter in clinical trials, and formulate mechanisms to optimize drug exploration. In the second proposed project, I study mobility in the metaverse, and show that in the absence of physical distances and commuting costs, mobility networks, where nodes are locations and an edge defines movement between two locations, can explain individual and macroscopic mobility patterns. Finally, in the third proposed project, I investigate gender-based segregation in chess, a gender-invariant sport, and its impact on career longevity and fame of female athletes using player networks, where a node is a player and an edge defines matches between two players. This dissertation ultimately exemplifies the universal capabilities of networks to offer explanations to puzzles across multiple scientific domains.
About the speaker
About the speaker
Kishore is a PhD student at the Network Science Institute at Northeastern University. He utilizes computational techniques and big data to study network processes at different scales, and across multiple domains.
Kishore is a PhD student at the Network Science Institute at Northeastern University. He utilizes computational techniques and big data to study network processes at different scales, and across multiple domains.