My name is Sean Whalen. Here's my curriculum vitae and LinkedIn profile. I'm a researcher applying machine learning to problems in computational biology and computer security, with recent emphasis on the former. I'm now a research scientist with Katie Pollard at UCSF's Gladstone Institutes, and was previously a postdoctoral fellow in computational biology at the Mount Sinai Institute for Genomics and Multiscale Biology headed by Eric Schadt.
At Mount Sinai, I worked with Gaurav Pandey primarily on applications of ensemble learning — combining multiple (often hundreds) of machine learning classifiers — to build predictive models in various areas of genetics and genomics including genetic interactions, synergistic drug interactions, and protein function. We recently tied for 5th in the DREAM Toxicogenetics Challenge with one submission prepared in a single week.
I was also part of a team working on enhanced genotyping of the human leukocyte antigen (HLA) region using long read DNA sequencing technology in combination with error-correcting techniques utilizing short read technologies that make independent systematic errors. This work has several applications including improved compatibility between bone marrow donors and recipients. Our team recently pitched to a panel of venture capitalists and was awarded funding as part of a Sinai initiative to commercialize translational research.
I'm a recent transplant into the field, having finished a postdoctoral position during 2012 in the Intrusion Detection Systems lab at Columbia University with Salvatore Stolfo where I worked on anomaly detection and cloud security for DARPA's Mission-oriented Resilient Clouds initiative. In 2011 I finished my I3P postdoctoral fellowship at Lawrence Berkeley National Lab in the Computational Research Division where I developed several methods for anomaly detection in high performance computing systems with Sean Peisert and David Bailey.
I enjoy inter-disciplinary work involving machine learning, statistics, and network theory. I'm also interested in information visualization and virtual reality, having previously developed a complex networks visualization tool with head tracking and gesture recognition for the KeckCAVES project. I completed my Ph.D. at the University of California, Davis in 2010 and was fortunate to be jointly advised by Matt Bishop (Computer Security) and Jim Crutchfield (Physics).
My partner and frequent collaborator is Sophie Engle, currently an Assistant Professor of Computer Science at the University of San Francisco.
The following papers, book chapters, and extended abstracts have all been peer reviewed. Computer science publishes much of its research via competitive peer-reviewed conference and workshop proceedings in addition to journals, whereas biology typically reserves peer review for journals.
|A Comparative Analysis of Ensemble Classifiers: Case Studies in Genomics||to appear in Proceedings of the 13th IEEE International Conference on Data Mining||2013|
|Multiclass Classification of Distributed Memory Parallel Computations||Pattern Recognition Letters||2013||bibtex pdf|
|Visualizing Distributed Memory Computations with Hive Plots||Proceedings of the 9th ACM International Symposium on Visualization for Cyber Security (held in conjunction with the 14th Annual IEEE VIS Conference)||2012||bibtex|
|Structural Drift: The Population Dynamics of Sequential Learning||PLoS Computational Biology||2012||bibtex|
|Network-Theoretic Classification of Parallel Computation Patterns||International Journal of High Performance Computing Applications||2012||bibtex pdf|
|A Taxonomy of Buffer Overflow Characteristics||IEEE Transactions on Dependable and Secure Computing||2012||bibtex|
|This is the Remix: Structural Improvisation using Automated Pattern Discovery||Proceedings of the 4th International Workshop on Machine Learning and Music (held in conjunction with the 25th Annual Conference on Neural Information Processing Systems)||2011|
|Network-Theoretic Classification of Parallel Computation Patterns||Proceedings of the 1st International Workshop on Characterizing Applications for Heterogeneous Exascale Systems (held in conjunction with the 25th International Conference on Supercomputing)||2011||bibtex|
|Hidden Markov Models for Automated Protocol Learning||Proceedings of the 6th International ICST Conference on Security and Privacy in Communication Networks||2010||bibtex|
|A Risk Management Approach to the Insider Threat||Insider Threats in Cybersecurity — And Beyond, Springer Verlag||2010||bibtex|
|Case Studies of an Insider Framework||Proceedings of the 42nd Annual Hawaii International Conference on System Sciences||2009||bibtex|
|We Have Met the Enemy and He is Us||Proceedings of the 2008 New Security Paradigms Workshop||2008||bibtex|