Entries tagged with microsoft research - Channel 9

A Look at VPlay on Microsoft Surface

Larry Larsen — Tue, 13 Oct 2009 22:19:00 GMT

Stuart Taylor is a researcher at MSR Cambridge and in his spare time he likes to mix bits as a VJ. He created an application called VPlay that allows him to mix video on a Surface like you would records on a DJ turntable. He stopped by the Channel 9 studio on his way to dinner last week and took a few minutes to show us how VPlay works.

You can see more about the project here.

Anandan Talks About Digital Heritage Project

Larry Larsen — Thu, 20 Aug 2009 13:43:00 GMT

P. Anandan, who leads Microsoft Research in India, stopped by to show us a project they worked on called the India Digital Heritage Project. This was a very cool attempt to recreate the experience of visiting historic sites around India through the combined use of Photosynth, HD View, video, and ambient sound. While much of the presentation is 'on rails' like a theme park tour, just like with World Wide Telescope you can stop the tour at any time and wander off clicking and zooming and looking at the sites, and then click to jump right back into the tour. It's a very interesting example of what's possible with tools available today.

Patrice Godefroid - Automated Whitebox Fuzz Testing with SAGE

Peli de Halleux — Tue, 14 Jul 2009 18:29:00 GMT

Patrice Godefroid gives an overview of Automated Whitebox Fuzz Testing, a powerful testing technique applied at Microsoft through a tool called SAGE. Listen how he is working with the SAGE team to 'eradicate all buffer overrun bugs' in Windows...

Read more in this paper or this slide deck.

The Research in Software Engineering team (RiSE) coordinates Microsoft's research in Software Engineering in Redmond, USA.

Sebastian Burckhardt - Data Race Detection with CHESS

Peli de Halleux — Fri, 12 Jun 2009 18:31:00 GMT

Sebastian Burckhardt gives a short tutorial of some of the new features of CHESS: data race detection and ChessBoard. CHESS is a concurrency testing tool takes a concurrent unit test and executes it with different thread schedules. Sebastian explains us how CHESS can detect data races, a very subtle kind of concurrency bug. You'll also learn how to drill into concurrency issues using the ChessBoard, a little application designed to drill and investigate concurrent tests.

CHESS home page: http://research.microsoft.com/en-us/projects/chess/
CHESS forums: http://social.msdn.microsoft.com/Forums/en-us/chess/threads/

The Research in Software Engineering team (RiSE) coordinates Microsoft's research in Software Engineering in Redmond, USA.

Margus Veanes and Pavel Grigorenko - Qex - Symbolic SQL Query Exploration

Peli de Halleux — Tue, 02 Jun 2009 23:59:00 GMT

Margus Veanes and Pavel Grigorenko present a new exciting project: Qex. Pavel did an internship in the Research in Software Engineering team (RiSE) investigating automatic data generation methods for parameterized SQL queries. In this video, he shows the result of his 3-month work. Qex translates SQL queries to logic formulas and give to our in-house constraint solver, Z3. When Z3 finds a solution, Qex translates that solution back to SQL code that can be executed in the database. This is similar to how Pex works.

Find more about Qex at http://research.microsoft.com/qex or read the technical report.

The Research in Software Engineering team (RiSE) coordinates Microsoft's research in Software Engineering in Redmond, USA.

RiSE at the International Conference on Software Engineering

Wolfram Schulte — Thu, 14 May 2009 19:07:00 GMT

Many researchers from the Research in Software Engineering team (RiSE) will be attending the 31st International Conference on Software Engineering in Vancouver (ICSE'09). Here is what RiSE is presenting this year:

Does Distributed Development Affect Software Quality? An Empirical Case Study of Windows Vista (ICSE: Research paper). Christian Bird, Nachiappan Nagappan, Premkumar Devanbu, Harald Gall, Brendan Murphy Winner of ACM SIGSOFT Distinguished Papers Award. By studying the development of Windows Vista we evaluate whether distributed software development is more challenging than collocated development.
Do Crosscutting Concerns Cause Defects? (ICSE: TSE/TOSEM Session), Marc Eaddy, Thomas Zimmermann, Kaitlin D. Sherwood, Vibhav Garg, Gail C. Murphy, Nachiappan Nagappan, Alfred V. Aho. TSE/TOSEM Session. We asked the question, “How much does the amount that a concern is crosscutting affect the number of defects in a program?” and conducted three extensive case studies to help answer this question. All three studies revealed a moderate to strong statistically significant correlation between the degree of scattering and the number of defects.
Predicting Defects in SAP Java Code: An Experience Report (ICSE: Software Engineering in Practice papers), Thomas Zimmermann, Tilman Holschuh, Markus Päuser, Kim Herzig, Rahul Premraj, Andreas Zeller. In a study on a large SAP Java system, we evaluated and compared a number of defect predictors, based on code features such as complexity metrics, static error detectors, change frequency, or component imports.
HOLMES: Effective Statistical Debugging via Efficient Path Profiling (ICSE: Research papers), Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani. We describe a statistical debugging tool called HOLMES that efficiently isolates bugs by finding paths that correlate with failure.
The Secret Life of Bugs: Going Past the Errors and Omissions in Software Repositories (ICSE: Research Paper), Jorge Aranda, Gina Venolia. Every bug has a story behind it. This paper uses rich bug histories and survey results to identify common bug fixing coordination patterns and to provide implications for tool designers and researchers of coordination in software development
Guided Path Exploration for Regression Test Generation (ICSE: NIER Track).Kunal Taneja, Tao Xie, Nikolai Tillmann, Jonathan de Halleux, and Wolfram Schulte. Given two versions of the same software, the approach described in this paper can automatically generate a test suite that exercises only those program behaviors which are different. A prototype has been implemented as an extension to Pex.
Improving Bug Tracking Systems (ICSE: NIER Track), Thomas Zimmermann, Rahul Premraj, Jonathan Sillito, Silvia Breu. We present a prototype of an interactive bug tracking system that gathers relevant information from users and automatically identifies files that need to be fixed to resolve a bug.
Codebook: Social Networking over Code (ICSE: NIER Track). Andrew Begel and Robert DeLine. Codebook is a social networking service that connects software developers through the work artifacts that they share -- code, bugs, tests, specifications, etc -- to enable them to keep track of task dependencies, maintain connections to other teams, and understand the history and rationale behind the code they use.
Exploiting the Synergy between Automated-Test-Generation and Programming-by-Contract (ICSE: Demos). M. Barnett, M. Fahndrich, P. de Halleux, F. Logozzo, N. Tillman. Pex, a unit-test generator, and Code Contracts, a design-by-contract system, provide even more benefits when used together for developing high-quality robust programs.
VCC: Contract-based Modular Verification of Concurrent C (ICSE: Demos). Markus Dahlweid, Michal Moskal, Thomas Santen, Stephan Tobies, and Wolfram Schulte. Annotated C and the Verified C Compiler (VCC) form the first modular sound verification methodology for concurrent C that scales to real-world production code. VCC is currently used to verify the core of Microsoft Hyper-V, consisting of 50,000 lines of system-level C code.
Deconstructing Concurrency Heisenbugs (ICSE Demo). Thomas Ball, Sebastian Burckhardt, Madan Musuvathi, Shaz Qadeer. CHESS is a tool for finding and reproducing "Heisenbugs", which result from unexpected interference among threads. CHESS has been integrated into the test frameworks of many code bases inside Microsoft and is used by testers on a daily basis.
An Empirical Study of Testing File-System-Dependent Software With Mock Objects (AST Workshop)
Madhuri Marri, Tao Xie, Nikolai Tillmann, Jonathan de Halleux and Wolfram Schulte. A case study on how to use parameterized mock objects in unit testing in combination with the test input generation tool Pex.
A Brief History of Software - from Bell Labs to Microsoft Research (MSR workshop, keynote)

Tom will report on the power of combining statistical expertise with software engineering expertise to address pressing problems of software production in a statistically valid manner. He will trace the history from early work at AT&T to present work at Microsoft.
Making CHASE Mainstream (CHASE Workshop keynote), Rob DeLine. Rob will discuss why “people issues” have not gotten enough attention among software engineering researchers and suggests ways to make research in this area more mainstream.
Coordination in Large-Scale Software Teams (CHASE Workshop). Andrew Begel, Nachiappan Nagappan, Christopher Poile, and Lucas Layman. A survey of Microsoft engineers shows that coordination between large-scale software teams is very challenging, but can be eased with better communication and tools tailored towards each engineer’s role in the collaboration.

The Design of a Task Parallel Library (Working Group Software Engineering for parallel Systems, keynote), Wolfram Schulte. Wolfram discusses the design and implementation of the TPL, which makes it easy to exploit potential parallelism in a .NET program.
Parameterized Unit Testing (Tutorial): Principles, Techniques, and Applications in Practice.
Nikolai Tillmann, Jonathan de Halleux, Tao Xie, and Wolfram Schulte. A hands-on introduction to parameterized unit testing: how it relates to unit testing, how to leverage automated tools, what good test patterns are, and how it can be used in practice.

Cheers, Wolfram Schulte.

Manuel Fahndrich and Peli de Halleux - The Synergy of Code Contracts and Pex

Peli de Halleux — Thu, 23 Apr 2009 18:59:00 GMT

Manuel Fähndrich and Peli de Halleux sit down for a quick coding session that shows how to use Code Contracts and Pex together. Code Contracts can be used to specify what your code should do, they get turned into runtime checks which Pex can analyse and try to find counter-examples for. This was a fun session with Manuel and really shows the synergy of the two tools/approaches.

Both tools can be downloaded from Devlabs or our academic project pages.

Code Contracts: http://research.microsoft.com/contracts
Pex: http://research.microsoft.com/pex

The Research in Software Engineering team (RiSE) coordinates Microsoft's research in Software Engineering in Redmond, USA.

Herman Venter - The Common Compiler Infrastruture goes Open Source

Peli de Halleux — Wed, 15 Apr 2009 22:49:00 GMT

Herman Venter announces the Common Compiler Infrastructure (CCI) as an open source project on codeplex! CCI is a set of tools and components that are useful to build compilers: readers and writers for MSIL and symbol files, and more.
You’ve may have heard and probably used different incarnations of CCI in the past: the FxCop introspection engine, ILMerge, Spec# or Code Contracts are using CCI in many ways. Now, you can use it too: just sync the sources, build it, tweak it, etc… It’s all there on codeplex at

http://ccimetadata.codeplex.com

Enjoy!
ps: Sorry for the low quality of the sound, my new microphone is on it's way...

The Research in Software Engineering team (RiSE) coordinates Microsoft's research in Software Engineering in Redmond, USA.

Kristin Tolle on biomedical initiatives at Microsoft Research

JonUdell — Thu, 18 Sep 2008 15:37:00 GMT

Kristin Tolle is the Senior Research Program Manager for Biomedical Computing for External Research in Microsoft Research. Projects run the gamut, she says, from "bench to bedside". In this interview she discusses two major biomedical initiatives: Cell Phone as a Platform for Health Care, and Computational Challenges of Genome Wide Association Studies.

Kristin Tolle

JU: Give us a sense of the kinds of biomedical projects you're working on internally, as well as those you're working on with external partners. I spoke with George Hripcsak, one of the researchers awarded a grant under the Computational Challenges of Genome Wide Association Studies (GWAS) program, and I know there are others involved there and in other programs as well. I'm interested in what Microsoft brings to the table in terms of helping these folks out with their computational and data management challenges, and also what kinds of things Microsoft learns from these engagements.

KT: The different programs inside of External Research run the gamut from the devices and mobility space, for home health care and elder care, all the way to genome wide association studies. So, we fund projects all the way from bench to bedside.

Because we're a software company, we'll focus on the IT parts, and there's a reason for that. These are often the parts that don't get funded elsewhere, or only get funded sparsely. Our purpose for going into medical funding was to fill those gaps.

JU: And why do you think those gaps exist?

KT: I think it's a misperception, by a lot of the funding agencies, that either something doesn't fall into their area, or that it's not as important as the actual research being done.

The problem is -- and this is why we're funding this area -- you cannot do medical research without computing. You just can't.

JU: Of course not.

Areas that we've funded...well, the biggest RFP we ran this year was Cell Phone as a Platform for Healthcare, and that was 1.4 million dollars toward trying to reach rural and underserved communities with retro technologies like cellphones and televisions, because those are ubiquitous.

JU: Oh, absolutely. I've spoken to Joel Selanikio, who was recently awarded a MacArthur Grant to use handheld devices for field data collection in the third world. It's a huge opportunity, though as you say it's the sort of retro technology that doesn't make people's eyes light up in Silicon Valley, they just don't see the opportunity the same way.

KT: It's true that they don't. But interestingly we've got a lot of researchers in-house, whether we're talking about that situation or about genomics, who have a keen interest in working in these areas. So for example, we gave Fone+ devices to a couple of the people who were winners of that award. The Fone+, which was developed by Microsoft Research Asia, is a phone that sits in a cradle, it's got RGB out to a television set, and USB input ports for mouse, keyboard, etc. So basically it enables your phone to work like a PC.

Now the beauty of this is, if you hook that up to a microscopy device that can do instant visualization of blood cells, determine whether or not somebody has malaria, and display that on a television screen, you've now just set up a lab for doing microscopy anywhere in the world there's a TV and a cellphone.

Another example is something we did with Washington University in St. Louis. They're developing low-cost ultrasound probes. Same thing. They're USB out, and designed to work with laptops, but now with the Fone+ you can plug it into this little cradle and now you've got an ultrasound anywhere in the world where there's power, a TV set, and a cellphone. You can even control the ultrasound device from the phone itself, it's just an amazing technology.

So that's an example where Microsoft Research has developed a technology that facilitates providing health care to rural communities. Although it wasn't initially designed for that, it was initially designed for education. But I took it and sort of twisted it..

[laughs]

...and said, hey, that'd be really good for the cellphone as a platform for healthcare project. I got them to give me a bunch of phones and cradles, and started sending them out to the researchers who had won awards for the RFP I ran this year.

JU: What kinds of things have you heard back?

KT: We've only funded them six months ago, so we won't see results probably until sometime next year. But I've actually seen a demo with the Fone+ and the ultrasound unit already working, so that was impressive. Washington U. is ahead of the game, I'd say.

JU: Are the folks you funded to do these things expected to bring technical chops to the table, in order to extend these devices? Are you working with them to provide support?

KT: Yes, we expect them to bring something to the table. And the ones who win the awards have superior technology. We had 145 people submit to the cellphone as a platform for healthcare. We'd originally planned to fund a million dollars, so that's about 10 projects, but we had to extend it to 1.4 million because we wanted to get to 10% acceptance rate. But even that, for us, is generally fairly low. Usually our acceptance rates are much higher. But we were just bombarded by people trying to come up with solutions for this space.

It was disappointing to only be able to do 14 proposals because when I looked back through them, I'd say 85 were fundable and on the bubble. Isn't that terrible? You wish you could do more.

So, I know you've talked to George about the genome wide association study, but I'd like to head in that direction in terms of some other things we bring to the table.

When I went looking inside MSR for collaborators, what I learned was that there's a plethora of them. It's kind of surprising we hadn't been funding this area before, and it's no surprise to me now that it's become a strong pillar of funding for our organization. In fact we've trimmed a lot of other programs and will be focusing a lot on the healthcare space this time around.

When I went hunting for collaborators I had no trouble finding them, even though I was new to the team, and that was because people consider healthcare the killer application for what they're working on.

But we also had a rich group -- you know, we have a couple of MD/PhDs working here, Eric Horvitz and David Heckerman -- and David does a lot of work in the development of vaccines for HIV and malaria. But he's branching out now into this GWAS area. So he's been looking at Lou Gehrig's disease...

JU: We should define the term GWAS, for people who aren't familiar.

KT: Sure. Genome wide association studies look across the genome to find if there are particular genes implicated in disease. That's one side of it. Another side is looking across the genome to check for reactions to different pharmaceutical agents.

In simplest terms, these studies are what will deliver on being able to provide personalized medicine for all of us in the future.

JU: Exactly, because it's a scan of an individual's complete genome, looking for markers and correlations.

KT: Absolutely right, that's correct. And I believe it will really deliver on personalized medicine for the masses.

And the thing is, it's happening already. We've got 23andMe popping up, Navigenics, people are going to start using their genomic information to make informed decisions about the type of healthcare they receive. They'll be taking that to their doctors and assuming they'll be able to work with it.

So we need to push the IT component of this down so that doctors have access to the information and know how to utilize it. Right now, that's the clinical gap between the research that's taking place in this area and the doctors who are performing the services needed.

JU: So in this case you funded about a half dozen individuals to look into different aspects of this GWAS research...

KT: ... yeah, very different...

JU: Right. So what do you hope will result from it?

KT: This was a new area for us, for Microsoft Research. We'd been dabbling in genomics for a while, but here we wanted to cast a wide net, find out what was going on out there, and find out if there were potential collaborations we could take from there.

When you find people whose work you can help facilitate, you form strategic collaborations with them to take that research to the next level.

Of course we bring a lot of resources to bear on this space. For example, the Microsoft Computational Biology Tools that we've published out on CodePlex, open source.

The other thing we bring to bear is a deep knowledge of machine learning and knowledge representation. And a number of researchers who've been working in general fields, but are now turning their attention to genomics.

A couple of new examples: John Winn, and also Christopher Bishop who literally wrote the book on machine learning and pattern recognition.

JU: This is a pattern I'm seeing often in these external partnerships. In all areas of science, as you say, scientists are necessarily becoming computational in the work they do, it's just the nature of the beast. But they don't necessarily have deep domain expertise in either algorithms or data manipulation and analysis. There are lots of folks at MSR who are deep in those areas, and who can effectively partner with these folks to move things forward.

KT: And it's not just that we have these underlying analysis and infrastructure technologies, we also have the human-computer interaction technologies to make that stuff usable for clinicians, or even the public themselves. So we've got people doing interesting work in how do you make something more understandable? How do you do machine translation across sex, age, status, education?

It's the same type of machine learning problem that you have with regard to going across language. You have to translate between languages, but you even have to translate within a language between different cultures, different demographics.

JU: What does Microsoft learn as a result of these collaborations, and what is Microsoft able to do with that?

KT: Well, the overall goal for External Research is to facilitate time to discovery, and to do so in a way that extends the arm of Microsoft Research. What we learn are which directions to move in. You know, we have publishing and tenure track promotion in Microsoft Research just as in academia. So if we can make our researchers more effective in reaching their goals to publish papers in Science and Nature, that's a fabulous thing. We've facilitated them and extended their reach.

There's also corporate responsibility here as well -- Microsoft, as a company, investing in areas that are important for the future. It's also important for us to keep abreast of the times, and the things taking place now. And finally, we learn things that we may incorporate into our products through tech transfer.

JU: It may be early days to talk about tech transfer from your biomedical projects, but I'd imagine one obvious outcome will be related to the kinds of devices that will be part of the HealthVault program, as sensors start to exist in people's homes, monitoring their vital signs, and transmitting them to the cloud.

KT: Absolutely, there's no doubt about it. The more that we invest in applications, and in sensors that can feed HealthVault, the richer their offering becomes.

The other thing is that we feel we're helping the public become more knowledgeable about their own healthcare. I think that's a common goal we share with the Health Solutions Group, Peter Neupert's organization.

They have other goals as well. So for instance, they have Amalga on the clinical side, and also a project targeted at researchers, trying to take people through the literature search for drug discovery. We're working in conjunction with that. One of the projects we funded under GWAS was a system to predict possible adverse drug reactions based on genome wide association studies.

Then the Columbia project -- George Hripcsak, whom you spoke with -- he's creating tools for researchers to integrate clinical information into the genetic analysis. Well, George's project is being built on top of Amalga. So there's a lot of synergy with the Health Solutions Group. And that's not unplanned. When I was starting out I met with Peter Neupert, back when he had eight people in his organization, and I interviewed him to find out what areas we should be investing in for healthcare. I'd also visited various schools and talked with people in their biomedical programs to find out what they were investing in as well. Then I tried to identify areas that would be relevant both to Microsoft Research and the Health Solutions Group. So, it's not just serendipity.

JU: So your own background is in bioinformatics?

KT: Biomedical computing. I had to form a multidisciplinary PhD committee because my school didn't have a program for this, though they do now, at the University of Arizona. So I had to form a multidisciplinary committee to get a PhD focused on machine learning for healthcare, with computational linguistics thrown in. It was tough, but it was worth it.

JU: Natural language processing was part of your focus as a student?

KT: Absolutely. Although the systems I developed were much more broadly utilized by different organizations. In fact, homeland security has some of the code I developed, which they use to scan for terrorist activities. It was initially developed for the National Library of Medicine to scan through unstructured text and identify keywords for indexers, and also to create small indices so that you could search faster and more accurately for publications in PubMed and CancerLit and other digital libraries. But you could see there were other implications. In fact it's also been used by the Department of Justice to make correlations among police reports.

So it's a generic technology, but my piece of it was targeted toward healthcare, and that's where my background and interests have always been.

JU: Are there other areas you'd like to discuss?

KT: I think we've covered the two major ones. I see us really investing long term in the area of devices, sensors, body sensor networks, ubiquitous and pervasive computing. That'll be a fundamental theme going forward, because it's been one of the more successful areas that we've made investments in.

But I also see us keeping a strong eye on the "omics" -- proteomics, genomics, metabolomics, you name it.

A third important area, and I don't know if it will be short term or long term, which is to address the other thing we talked about, and I don't have an RFP in this, but machine translation for people to be able to understand health care documents.

The average person cannot go out on Medline and read the literature on their disorder.

JU: It is amazing, though, how much context people can assemble for themselves under pressure of intense need.

KT: No doubt about it. But it would be better if we could create facilitating interfaces that would enable people to more readily understand and interpret that information. There's a lot of it out there, it's information overload really, and if we could make it a little easier for them, that would be very valuable.

JU: I wonder how much of that will be done by machine translation, and how much by crowdsourcing various experts at various levels. I think probably both will happen.

KT: Yeah.

You know, another important area -- and I was a bit disappointed when we ran our GWAS RFP that we didn't get anything concrete in this area -- was data visualization for genome wide association studies.

I think that's because it's such a hard problem. These studies are computationally challenging as it is, there's a lot of data that gets generated. Then to visualize it, now you're adding another level of computational complexity such that it's already not realtime just looking at the data, then how do you take it to that next level of visualization? That's going to be an important emerging area going forward.

So for instance, we've been talking with the folks at Oxford about getting a Surface there for collaborative visualization of cancer pathology.

JU: Not just in this area, but in general, we are so underserved by our ability to make sense of large complex data.

KT: Yeah, and we have these cool technologies. I think the WorldWide Telescope could be redeployed in many environments, and I think healthcare is one of those killer applications. We were talking with the National Cancer Institute, and one of the things they'd like to do is take a slice out of the liver while the patient is still on the table and be able to zoom in and zoom out -- it's the same technology.

JU: It's a similar kind of thing. To the extent that we can, in different fields, standardize on data formats and define multidimensional data spaces, we can indeed have browsers and viewers for those spaces. What the Telescope does in its domain is create a browser for a web of astronomy data. So yes, we need to have browsers for webs of genome data, and all kinds of scientific data.

KT: We had a recent paper by Bongshin Lee, she's done a distance encoding tree -- she calls it Detective -- and it's a scalable visualization tool for mapping multiple traits onto evolutionary trees. So we're trying to tackle it inside Microsoft Research, but I was hoping to see more people outside MSR show interest so we could start forming interesting collaborations in that area.

JU: Well, this has been a lot of fun. I hope to follow up on some of those Fone+ applications, that sounds really inspiring.

KT: Yeah, that's the reason I've gone into this area. It is inspiring. There's not only corporate responsibility, there's personal responsibility for me as well, and that's why I like working in this particular space. It's genuinely gratifying to be able to make a difference in an area that, no question about it, is beneficial to society.

JU: Well you've landed in the perfect spot to do that, and it sounds like you're having a blast.

KT: Yes, I am. Well, thanks very much.

JU: Thanks Kristin.

How Microsoft's External Research Division works with a new breed of e-scientists

JonUdell — Thu, 31 Jul 2008 16:49:00 GMT

Tony Hey, VP for the External Research Division within Microsoft Research, leads the company's efforts to build external partnerships in key areas of scientific research, education, and computing. He's been a physicist, a computer scientist, and dean of engineering, and for five years ran the UK's e-Science program. These experiences have given him a broad view of the ways in which all the sciences are becoming both computational and data-intensive. Microsoft tools and services, he says, will support and sustain the new breed of scientists riding this new wave.

Audio: WMA, MP3

Tony Hey

JU: For this series of interviews I've spoken to a number of Microsoft folks who are working with external academic partners on projects that fall under your purview. The list includes Pablo Fernicola's Word add-in for scientific publishing, Catharine van Ingen's collaboration with Dennis Baldocchi at Berkeley on the analysis of C02 data, and Kyril Faenov's HPC++ project to bring cluster computing to the classroom. These are all pieces of your puzzle, right?

TH: Absolutely.

JU: By way of background, you've been a physicist, then a computer scientist, and then for a time led the UK's e-science program.

TH: Which would be called cyberinfrastructure in the US, yes. I'm on the NSF's advisory committee for cyberinfrastructure, it's a very similar goal.

JU: And then you surprised a lot of people by joining Microsoft. Take us through your initial role leading the TCI [technical computing initiative] and on to your current expanded role leading MSR's external research efforts.

TH: Right. So having been a physicist, and then a computer scientist working on parallel computing for years, and then chair of my computer science department and then dean of engineering, I think I understand the community we're trying to work with pretty well.

Also, as you mentioned, I worked for 5 years running the UK e-science program. That was about huge amounts of distributed data, and collaborative multi-disciplinary research in a variety of fields. The environment, bioinformatics, almost every field of science now has some element of distributed and networked collaboration.

The science agenda was for the tools and technologies to make that collaboration trivial, just as with Web 2.0 your grandmother can do a mashup.

I don't think the UK e-science program achieved that, but I do believe that Microsoft can help make tools and technologies available that will help scientists and researchers do their work.

JU: In your parallel computing phase, you helped write the MPI [message passing interface] specification, correct?

TH: Yes. I've been in this for 30 years, on and off. I have very good friends in the high-performance and parallel computing communities here in the US, and I was involved in European projects. There was a danger that the Europeans would go one way, and the US another, so it was time to see if we could get the community to put together a community standard.

It isn't an ISO standard, there wasn't a big standards body, it was a group of experts who got together with the academics and with the industry players. Rather a small set, and we used to meet every 6 weeks in Dallas airport, so you really had to be dedicated to go there.

JU: [laughs]

TH: But what came out of it was a standard which has stood the test of time. I co-authored and initiated the first draft. It's been much changed since then, and I don't take credit for the final thing, but I did try, with Jack Dongarra, to initiate the standards process, and I think I remember buying the beer at the first session.

JU: What's interesting to me is that despite that, you've been a vocal skeptic regarding raw grid capability. And you've been very careful to stress that in your view, the real challenges have to do with data -- the ability to combine large quantities of data from multiple sources, and enable people to make sense of it.

TH: Yes. I used to work in high-end supercomputing and parallel computing, but what distinguishes this decade is that we'll collect more scientific data than we have collected in the whole of human history. Instead of struggling with the problem of too little data, scientists will be struggling with the problem of huge amounts that they can't process or analyze. And it may be stored in different places, on different continents, so how do you put it together? How do you federate?

That's the real challenge. Very people want to use petaflop computers. Most of the biologists, chemists, and engineers only need lesser capabilities that can be provided by just a simple cluster. And then you put the cluster where the data is, because that's what's difficult to move around.

JU: Yes, Kryil Faenov made this same point in my interview with him. There are only a handful of intergalactic cloud infrastructures of the sort that a Google or Amazon or Microsoft can support, they're one-of-a-kind beasts, and you can't always bring your data to them. So he's interested in enabling organizations to stand up their own more modest clusters at the sites where the data lives.

So, let's discuss the opportunity that you see. In another interview you said:

Rather than wasting the enthusiasm and talents of science graduate students by assigning them the task of building systems capable of handling, analyzing and mining literally petabytes of data, scientists should look to computer scientists and the IT companies to raise the level of abstraction and to provide them with the components of a reliable and functional cyberinfrastructure.

That's the most concise mission statement I've found for what you're doing.

TH: Exactly right. Part of my reason for joining Microsoft was having had a great friendship, and many discussions and arguments, with Jim Gray, from 2001 onwards.

We argued and disagreed on many things, but we also agreed on things, and what we agreed on in particular is that a different paradigm is emerging. So for example there's experimental physics, there's theoretical physics, and now the third paradigm, it's clear, is computational physics based on simulation.

What we're looking at here is data-centric science, where you'll do collections-based research -- like you do in mashups, but now with scientific datasets. And increasingly, you'll use semantics to get from data to information to real knowledge.

So I came to Microsoft partly because of Jim Gray, but partly because I think companies can help. I struggled mightily with just open source tools. I used to produce open source tools myself, as an academic. MPI has a wonderful open source implementation, and that was one of the key things that we did.

But I also know that open source, particularly when produced by academics like myself, well, it works on my machine, but if you want it to work on your machine, that's your problem.

So one of the things I set up in the UK was, in fact, a software engineering center called the Open Middleware Infrastructure Institute, where I put a lot of money in to get these open source codes tested and documented and made more reliable and sharable.

That's why I think that a judicious mix of open source with commercial -- it could be from IBM, from Oracle, from Microsoft -- is the way to provide a more reliable infrastructure.

That's part of the motivation for the tools we're producing around the technologies that scientists use to do their publication, their data mining, and so on. I think Microsoft can really take a lead here, and that's why I joined.

JU: Elsewhere you've said:

Essentially I match up Microsoft researchers with major scientific problems that computer science technology can help to solve.

What are those major problems?

TH: So, I came with a purely scientific mission with TCI. But now I've moved into Microsoft Research, and we have a bigger agenda. In terms of external research, we focus on four themes.

One is health and wellness. That's bioinformatics, medical solutions, and so on. Really exciting, we've got some good projects in that area.

JU: I've talked to Kris Tolle and have done an interview with George Hripscak who's one of the recipients of funding in the genome-wide association studies program.

TH: Kris is great, she and Simon Mercer are looking at the biomedical area, and they've got a wonderful set of projects ranging from high-tech stuff involving RNA and HIV/AIDS down to the last mile of preventative health care, looking at ways in Latin America to take a smartphone and connect it to a low-cost diagnostic tool, like a blood-pressure monitor, and therefore do health care in these remote places.

The next major area is what we call E3 -- earth, energy, and the environment. That includes the astronomy work that Jim Gray started, which we now have followed up with the WorldWide Telescope, which is a wonderful tool.

JU: It's a brilliant thing. I've actually done two in-depth conversations about it for this series. One with Curtis Wong, and the other with Jonathan Fay.

TH: It does exactly the things we were talking about, it takes lots of distributed data sets, and allow you to search and visualize and do wonderful things.

So that's one example of an E3 project. Catharine van Ingen's project is another, and there are others. There's a project called the Swiss Experiment that's putting sensors all through the Swiss Alps to measure environmental changes.

JU: Before we discuss the other two areas, let me just ask: What is a project? I gather sometimes Microsoft Research puts out an RFP, and somebody like George Hripcsak at Columbia is awarded money to pursue his research. In other cases, though, there isn't necessarily funding, it's more of a collaboration, as with Catharine van Ingen and Dennis Baldocchi.

TH: Yes. In all cases, I want us to focus on genuine partnership with the academics. It has to be win/win on all sides. There are all sorts of ways. RFPs are one. Targeted funding, like we used to do in TCI, maybe sponsoring post-docs. But other things too, like delivering tools, data sets, services.

What can we do for the computer science community? That's another of our themes.

I used to teach in a computer science department, and I assure you my department was not atypical. We taught Linux, Apache, MySQL, PHP, Java, and they used a variety of scripting languages -- Perl, Python, and now Ruby on Rails.

To teach computer science principles it's quite clear you don't necessarily need any Microsoft technology. So the question is, how do we engage with academics in the computer science disciplines?

JU: And what are your thoughts?

TH: We have an opportunity. We need to look at what services, what data, what resources we can give them, so we can partner in a way that they feel is beneficial, so they can do research in the way they want to, and we can find out what services they need, and how we can make our tools more valuable.

Microsoft does now have the beginnings of some exciting service offerings. There's Live Mesh, and we have .NET online services coming along...I liked our internal name, CloudDB, better than SQL Server Data Services, SSDS, but...

JU: ...that's how it always goes.

TH: That's the way of it, yes. So that's in beta at the moment, and I hope by the time of the PDC in October we'll have a lot more concrete things to show. What I need to do is see what we can offer the academic community in terms of resources. Can we help them to explore multi-core? Can we get them data sets at scale that we've anonymized, so they can do research they'd otherwise not be able to do?

JU: And Dryad?

TH: Yes. We now have within Microsoft Research some internal resources -- cores -- and I want to make some of that available externally, and put some services around it, such as Dryad or Dryad/LINQ.

At the Faculty Summit I want to ask the community -- and after all, I came from that community -- how can we partner with you so that we can give you things that you value, and get your feedback?

JU: What is the Faculty Summit, who's been invited, and what do you aim to accomplish there?

TH: It's an annual event in the U.S., three or four hundred academics come, mainly computer scientists from the U.S. but there's a sprinkling from around the world -- India, China, Latin America. Really it's an opportunity for us to connect.

I've talked about health and wellness, earth/energy/environment, and computer science. Another area of focus is education and scholarly communication. We'll be unveiling plugins for our tools that make them more useful for scientists to do what they want to do.

JU: The NLM add-in for Word is an obvious example. Are there others?

TH: Yes, we'll announce a Creative Commons plug-in. Many people use Word, PowerPoint, and Excel, and are happy to share their documents. We'd like to give them a plug-in that will help them attach Creative Commons licenses to those documents.

We'll also have a research repository. At the university, I was supposed to monitor the output of my faculty -- 200 academics and 500 post-docs and grad students. What we did was insist on keeping a digital copy of not only publications, but also presentations at conferences, research reports, videos, data...

JU: ...especially data. That's a huge new area.

TH: It is in my view, yes. My undergraduates and engineering faculty never went into the library for traditional library purposes. They went there for a cup of coffee, a chat with their friends, a warm place to work, but not as a library.

So what is the role of the library? My view is very much the MIT DSPACE view that's been promoted. The role of a research library in a university is to be the guardian of the intellectual output of the university. And that needn't just be research, it can be teaching materials.

So we've used SQL Server, and the Entity Framework -- a bit like the RDF model of Tim Berners-Lee and friends -- to capture some semantic knowledge. So it tells you this is a presentation, Tony Hey gave it, the local organizers were so and so, it was done on this date, and so on.

JU: There's also the general notion of wrapping services around raw data sets. I've talked with Timo Hannay at Nature about how often, nowadays, somebody winds up publishing a paper as a "fig leaf of analysis" to cover what's really the publication of some data set.

TH: Timo and I absolutely agree on this. Research repositories which contain text and also data are going to be increasingly important.

JU: Although you're not wild about the term "data services", it's actually useful. I was talking with Jonathan Fay about his discovery of all the astronomical data that's online. On the one hand, it was astonishing to find that it was available at all. On the other hand, in the grand tradition of academia, these were gzipped tarballs that you could only use if you had an extreme amount of specialized knowledge and capability.

What you get, with WorldWide Telescope, is a service layer wrapped around all that raw data that makes it available to a vastly wider audience.

TH: Absolutely. Same with Catharine van Ingen's project. This stuff was locked away in files, and nobody knew what was there. By making it available and exposing it in new ways...you're right, these data services are very important.

And they're the basis of some of our other projects. So for example, Valerie Daggett at the University of Washington does protein folding, but she also does protein unfolding. She regards protein folding ab initio, right from the beginning with just the structure, as too difficult. So she takes the folded structure and unfolds it, and then looks at the possible foldings you can get. She calls this dynameomics. It involves storing detailed simulations, and we've made a database to help her do that.

JU: How would you characterize the nature of the collaboration between Microsoft Research and Valerie Daggett?

So, for example, with Catharine van Ingen and Dennis Baldocchi, it was a really interesting mesh of interests and capabilities. Dennis is a climate scientist who's plugged into a worldwide network of sensors, but he's not an informatician, he's not someone with deep training in how to probe and reshape a body of data. But that's what Catharine brings to the table.

So in this protein-folding collaboration, what's the partnership really about?

TH: It's on two levels. Valerie really is a computational scientist. She does these computationally-intensive calculations, and she uses national supercomputers.

One of the things we've done is give them experimental Windows HPC clusters, so instead of doing it remotely they can actually get a lot of calculations done on local machines.

The other part is that they don't have particular expertise in databases. So Stuart Ozer, who used to be in Jim Gray's group and now is back with SQL Server, collaborated with them to set up a data cube.

JU: It seems like the transfer of database expertise is a common thread in a lot of these collaborations. Although many of these folks may be computationally-oriented scientists, and may know how to work with algorithms and with code, the data management is another kind of discipline, and not one that necessarily comes naturally.

TH: That's right. By the way, we're also active in computational education for scientists. When I did that in the 80s and 90s it was about algorithms and parallelism and things like that. But you're quite right, it's now, in addition to those things, about knowing how to deal with data.

We have projects with two Nobel Prize winners, Phil Sharp at MIT, and Carl Wieman at Vancouver, looking at what you teach biologists and physicists about new skills, in order to produce a new generation of computational scientists who understand the data as well as the computation.

And I'd be remiss if I didn't mention Stephen Emmott. I emphasize the data, but he'd say that the complexity of the modeling that you have to do with this data is as important. And therefore, some of the abstractions from computer science can really help the modeling side of science.

One of our engagements is a joint bioformatics modeling institute in Trento, and that's an initiative of Stephen Emmott and his team.

JU: I guess that most people know Microsoft has a massive research arm, and there's been a lot said and written about internal technology transfer -- something gets invented in MSR, then it's thrown over the wall into a product group. People have heard that story, but this other story about external collaboration isn't so well known.

TH: That's true, though it does link to our research within MSR. In terms of the computer science and education communities, we have wonderful tools here that actually don't end up in products. One of the things I hope to do is make more of these available.

We now, at Microsoft, have two OSI-approved open source license, Ms-PL and Ms-RL. I'd like to make some of our tools, which aren't going into products, available so that we can build communities and show what great tools there are. Tools that really do things the computer science community and science community want.

So, I talked about our four themes -- health and wellness, earth/energy/environment, computer science, education and scholarly communication. In addition we have what we call ARTS: Advanced Research Tools and Services. There we're trying to develop tools and services that academics and computer scientists will find valuable.

And there are many others. We just did a count, and in total, with RFPs and small projects and big projects, we had, over the whole of Microsoft Research something, like 400 projects with external partners in universities.

My challenge is to focus that a bit more, and make sure we capture and build on the ones that are successful.

JU: Well, very good, Tony. Thanks a lot!

TH: Thanks very much, Jon.