Abdullah Mueen is an assistant professor at the department of computer science in the University of New Mexico. Earlier, he served as a scientist in Microsoft Corporation (2012-2013). Dr. Mueen is interested in analyzing large data to discover patterns and anomalies. He is the runner-up of ACM SIGKDD Doctoral Dissertation Award 2012 and his paper on mining trillion subsequences has won the best paper award in the ACM SIGKDD conference in 2012.

    Research Interest
    My interest is in time series data (i.e. real-valued sequence) mining. I am particularly interested in pattern based mining algorithms such as similarity search, correlation join, classification, clustering and rule/association mining, for both archived and streaming time series data. I am also interested in pattern-based mining algorithms for other semi-structured data types such as XML, audio, reviews, etc.
    I recently developed interest in mining activity sequences of social media users. I look at unusual behaviors of frauds, bots, trolls, shill bidders and account farmers. I find temporal patterns associated to their activities to detect them.
    Doctoral Dissertation Award Runner-up, SIGKDD 2012
    Best Paper Award SIGKDD 2012