Description: Neil Shah, Scientist, Snap Research
research (8973) artificial intelligence (4313) machine learning (3819) phd (893) data mining (576) computational social science (30) anomaly (30) graph mining (7) outlier (7) user modeling (4)
I am a research scientist and manager at Snap Research, where I lead a team of research scientists, engineers and interns on academic, applied research, and engineering initiatives in user modeling and personalization across Snapchat. I am especially interested in pushing forward the state-of-the-art in machine learning algorithms and applications on large-scale graph data. My work broadly spans the machine learning, data mining, network science, computational social science and softare engineering domains.
Before I joined Snap, I defended my PhD thesis in the Computer Science Department at Carnegie Mellon University , where I worked on discovering and modeling various types of abusive online behaviors as anomaly detection problems in large networks. I was very fortunate to have been advised by Christos Faloutsos .
Prior to this, I received my B.S. in Computer Science from the Department of Computer Science at North Carolina State University . There, I worked with Nagiza Samatova on reduction, indexing and storage systems for large-scale scientific data.
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