I am Andrew G. West, a Principal Research Scientist at Verisign in the Washington D.C. area. In my role with the Strategy & Analytics group I apply deep learning, machine learning, forecasting, and other data science techniques across our domain name business and associated marketing efforts. I publish my research and pursue intellectual property protection via my affiliation with Verisign Labs. Prior to Verisign, I completed my Ph.D. at UPenn in 2013 (MSE 2010) and received my B.Sc. at Washington & Lee University in 2007.
My recent work has focused on: (1) Leveraging deep learning for generative and classification tasks, (2) modeling and forecasting many aspects of the domain name lifecycle, (3) applying big data techniques to Internet-scale quantification problems, and (4) designing crowd-sourced data collection for market measurement and competitive intelligence. Complementing this work are broader research interests that include reputation management, metadata analysis, email/Web 2.0 abuse, underground economies, behavioral profiling, and Internet virality. Though the majority of my insights are now internally facing, my research approach draws from a rigorous background of 35+ peer-reviewed publications and a desire to bring emergent techniques to bear on business problems.
Before my current role, my dissertation research investigated security in "open collaboration" applications. I examined how user-generated content and collaborative semantics change how abuses manifest and can be detected. This yielded tools still in popular use, notably “STiki”, which has been used to remove 1.1+ MILLION damaging revisions from Wikipedia. Media outlets such as the Chronicle of Higher Education and Gizmodo have recognized my contributions, and I remain an active volunteer in the Wikipedia community.
http://www.andrew-west.com -- my professional website, has my full C.V., copies of my publications, and enumerates my academic and professional involvement.
Much has been written about wikis’ reliability and use in the classroom. This research bulletin addresses the negative impacts on institutional welfare that can arise from participating in and supporting wikis.