Michael Spiegel Ph.D. Candidate Department of Computer Science School of Engineering and Applied Science University of Virginia 151 Engineer's Way, P.O. Box 400740 Charlottesville, VA 22904-4740 Email: Office: 229 Olsson Hall, UVa URL: http://www.cs.virginia.edu/~ms6ep Jobs: Curriculum vitae

Research I am a member of the Modeling and Simulation Technology Research Initiative (MaSTRI) team. My research interests are in the development of high-productivity programming models for high-performance computing (HPC). While hardware performance has been growing exponentially – with gate density doubling every 18 months, storage capacity every 12 months, and network capability every 9 months – it has become clear that capable hardware is not the only requirement for computation-enabled discovery1. The limits to productivity in computational science are no longer in the hardware. The limits are in the expresiveness of our language tools. Scientific computing has a reliance on sequential, imperative languages with no built-in support for domain-specific language extensions. I have been involved with the following three research projects over the course of my graduate career to address these issues.

Fortress - Fortress is a new programming language designed for high-performance computing with high programmability. Fortress will support features such as transactions, specification of locality, and implicit parallel computation as integral features built into the core of the language. Features such as the Fortress component system and test framework facilitate program assembly and testing, and enable powerful compiler optimizations across library boundaries. The syntax and type system of Fortress are custom-tailored to modern HPC programming, supporting mathematical notation and static checking of properties such as physical units and dimensions, static type checking of multidimensional arrays and matrices, and definitions of domain-specific language syntax in libraries.

OpenMx - The OpenMx Project intends to rewrite and extend the popular statistical package Mx to address the challenges facing a large range of modern statistical problems such as: (i) the difficulty of measuring behavioral traits; (ii) the availability of technologies - such as such as magnetic resonance imaging, continuous physiological monitoring and microarrays - which generate extremely large amounts of data often with complex time-dependent patterning; (iii) increased sophistication in the statistical models used to analyze the data. To address these problems, the Mx Structural Equation Modeling software will be rewritten so as to: (i) split OpenMx into modules that interoperate with the R statistical package; (ii) release OpenMx as open source so as to provide a stable path for future maintenance and development; (iii) integrate OpenMx with the Swift (formerly VDL) parallel workflow software.

RiskModelica - RiskModelica is my thesis project to construct a language for the formal representation of uncertainty in modeling and simulation. RiskModelica is an extension to the Modelica programming language, which is an acausal object-oriented language for hybrid continuous and discrete-event simulations. RiskModelica will serve as a platform for the research into representation and calibration of imprecise probabilities in quantitative risk analysis simulations. The explicit representation of imprecise probability theories will facilitate the development of efficient algorithms for expressing, computing, and calibrating imprecise probability structures. The purpose of imprecise probability structures is to conduct quantitative risk analyses that is more informative than analysis using traditional probability theory.

1 "Cyberinfrastructure Vision for 21st Century Discovery." National Science Foundation Cyberinfrastructure Council, March 2007.

Computer Science Canon For a young field with only 60 years of modern history, there is very little emphasis on studying the development of computer science. I like to read these formative papers in order to (a) understand the intellectual development of computer science, and (b) inspire new avenues of thinking in future research. Here is my first draft of a "Great Works in Computer Science" reading list. Please email me with your additions, deletions, or modifications to the list. I am particularly interested in nominations from the '80s, '90s, and '00s. Community Projects In order to preserve my geek credibility, I am a developer for several open source projects. They are all wonderful tools, and I highly recommend checking them out.

JabRef - a graphical frontend to manage BibTeX databases, the standard LaTeX bibliography reference format. JabRef is build to be platform independent (requires Java >= 1.4.2). JabRef provides nearly all of the functionality of a commercial citation manager, at open-source prices and open standards compliance.

Linux Users Group - I just noticed that both the Swarthmore Linux Users Group (SLUG) and the University of Virginia Linux Users Group (uvaLUG) don't have webpages. So use those links to reach the mailing list info. UPDATE: UVaLUG now has a wiki.

Netflix Queue

Michael's queue

1. The Diving Bell and the Butterfly 2. Hannah Takes the Stairs 3. Deep Water 4. Southland Tales 5. The Savages 6. Atlantic Records: The House that Ahmet Built 7. The Great Happiness Space 8. The Man from Earth 9. Frank and Ollie 10. Futurama: The Beast with a Billion Backs 11. The Counterfeiters 12. Batman: Gotham Knight 13. Stargate Continuum 14. This American Life: Season 1 15. Talking Heads: Stop Making Sense 16. Jim Henson's The Storyteller 17. Secrecy

Rachel's queue

1. Good Night, and Good Luck 2. The Man Who Cried 3. Annie Hall 4. The Treatment 5. Me and You and Everyone We Know 6. LOL 7. Lovely & Amazing 8. Walking and Talking 9. Mansfield Park 10. Only You 11. Definitely, Maybe 12. The Shape of Things 13. Father Goose 14. An Affair to Remember 15. Then She Found Me 16. Young @ Heart

• Dave: queue history
• Free: queue history
• Jeanne: queue history
• Nate: queue history
• Rachel: queue history
• Rob: queue history
• Scott: queue history
• Spiegel: queue history