2006年“二十一世纪的计算”学术研讨会

Currently charged with oversight of Microsoft Research’s worldwide operations, Rick Rashid previously served as the director of Microsoft Research, focusing on operating systems, networking, and multiprocessors. In addition to running Microsoft Research, Rashid also was instrumental in creating Microsoft’s Digital Media Division and directing Microsoft’s first e-Commerce group.

Before joining Microsoft in September 1991, Rashid was professor of computer science at Carnegie Mellon University (CMU). During his tenure at CMU, Rashid developed the Mach multiprocessor operating system, which has been influential in the design of many modern operating systems and remains at the core of a number of commercial systems.

Rashid’s research interests have focused on artificial intelligence, operating systems, networking, and multiprocessors.

Rashid received master of science (1977) and doctoral (1980) degrees in computer science from the University of Rochester. He graduated with honors in mathematics and comparative literature from Stanford University in 1974.

Microsoft Research: Turning ideas into reality for 15 years

This year Microsoft Research celebrates its 15^th anniversary. In this talk I will describe how Microsoft Research came into existence and the decisions, events and factors that I believe have lead to its success. I will talk about the role of basic research in Industry and how it relates to both academic research and product development and I will look forward to the future and the technologies that will shape the next 15 years.

Professor Yao was born in Shanghai, China. He received a BS in Physics from National Taiwan University, a PhD in Physics from Harvard University, and a PhD in Computer Science from the University of Illinois. His research interests include analysis of algorithms, computational complexity, cryptography, and quantum computing. Professor Yao has been on the faculty at MIT, Stanford, UC Berkeley, and Princeton University. In 2004 he left Princeton to become a Professor of Computer Science at Tsinghua University in Beijing. He is also a Distinguished Professor-at-Large at the Chinese University of Hong Kong.

Professor Yao was the recipient of the prestigious A.M. Turing Award in 2000 for his contributions to the theory of computation, including communication complexity and pseudorandom number generation. He has received numerous other honors and awards, including the George Polya Prize from SIAM, the Donald E. Knuth Prize from ACM/IEEE, and many honorary degrees. He is a member of the US National Academy of Sciences, the American Academy of Arts and Sciences, and the Chinese Academy of Sciences.

A Modern Theory of Trust-but-Verify

Professor Eric Grimson is the Bernard Gordon Professor of Medical Engineering in MIT’s Department of Electrical Engineering and Computer Science. He is a member of MIT’s Computer Science and Artificial Intelligence Laboratory, and Head of its Computer Vision Group. He also holds a joint appointment as a Lecturer on Radiology at Harvard Medical School and at Brigham and Women’s Hospital.

He received a BS in Mathematics and Physics from the University of Regina in 1975 and a PhD in Mathematics from MIT in 1980.

Professor Grimson is currently the Head of the Department of Electrical Engineering and Computer Science at MIT. Prior to this position, he has served as Associate Department Head for Computer Science and as Education Officer for the Department.

Professor Grimson is a Fellow of the IEEE and of AAAI, and a recipient of the Bose Award for Undergraduate Teaching at MIT.

Professor Grimson has research interests in computer vision and in medical image analysis. Since 1975, he and his research group have pioneered state of the art methods for activity and behavior recognition, object and person recognition, image database indexing, site modeling, stereo vision, and many other areas of computer vision. Since the early 1990’s, his group has been applying vision techniques in medicine for image-guided surgery, disease analysis, and computational anatomy.

Computer Science is Everywhere: Leveraging interconnections to other fields

Enrollments in computer science departments are changing dramatically in American universities, in part because computer science is perceived differently by today’s students. These changes are both in numbers of students and in the interests of students, in particular that current students have broad interests across interdisciplinary boundaries. MIT is engaged in a comprehensive redesign of its curriculum, partly in response to changes, aimed at increasing interest in computer science as a profession, and in providing better connections between computer science and related fields: life sciences, finance, management, and communications. These proposed changes include: greater hands-on experiences, grounding fundamentals in practical applications, including industrial experiences and exposure to practicing engineers, opportunities for global experiences, and exploration of the role of computer science in other fields.

Jim Gray is a Technical Fellow at Microsoft Research’s eScience Group (opens in new tab). His primary research interests are in databases and transaction processing systems, with particular focus on using computers to make scientists more productive. He and his group are working in the areas of astronomy, geography, hydrology, oceanography, biology, and health care. He continues a long-standing interest in building supercomputers with commodity components, thereby reducing the cost of storage, processing, and networking by factors of 10 to 1000 below low-volume solutions. This includes work on building fast networks, on building huge web servers with CyberBricks , and building very inexpensive and very high-performance storage servers. Jim is also working with the astronomy community to build the world-wide telescope (opens in new tab) and has been active in building online databases such as http://terraService.Net (opens in new tab) and http://skyserver.sdss.org (opens in new tab). When the entire world’s astronomy data is on the Internet and is accessible as a single distributed database, the Internet will be the world’s best telescope. This is part of the larger agenda of getting all information online and easily accessible. More generally, he is working with the science community to build the world-wide digital library that integrates all the world’s scientific literature and data in one easily-accessible collection.

Jim is active in the research community, is an ACM, NAE, NAS, and AAAS Fellow, and received the ACM Turing Award for his work on transaction processing. He also edits a series of books on data management.

eScience – A Transformed Scientific Method

Jim has been working for the last decade to get all scientific data and literature online and cross-indexed. Progress has been astonishing, but the real changes will happen in the next decade. First, the funding agencies are forcing peer-reviewed science literature into the public domain and peer-reviewed science literature is being curated in new ways — cross-indexed to the data that produced it. Scientific data has traditionally been hoarded by investigators (with notable exceptions). The forced electronic publication of scientific literature and data poses some deep technical questions: just exactly how does anyone read and understand it? How can we preserve so that it will be readable in a century? Incidental to this, each intellectual discipline X is building an X-informatics and computational-X branch. It is those branches in collaboration with Computer Science that are faced with solving these issues. Jim has been pursuing these questions in Geography, Astronomy, and more recently in bio informatics.

As Microsoft Research Asia’s managing director, Harry Shum oversees all research activities and collaboration with universities in the Asia-Pacific region. He also holds the title of Microsoft Corporation Distinguished Engineer.

An Institute of Electrical and Electronics Engineers (IEEE) Fellow, Shum serves on the editorial boards of both the Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Vision. He was general co-chair of the 10th IEEE International Conference on Computer Vision in Beijing in 2005. Shum has published more than 100 papers in fields such as computer vision, computer graphics, pattern recognition, statistical learning, and robotics. He holds more than 20 U.S. patents.

After joining Microsoft in Redmond, Washington in 1996, Shum was a researcher for Microsoft Research, focusing on computer vision and computer graphics. In 1999, Shum moved to Beijing to help start Microsoft Research China (later renamed Microsoft Research Asia). Before taking the helm as managing director of Microsoft Research Asia, he held a number of senior positions, including research manager, senior researcher, and assistant managing director. In 2006, Shum was named a Microsoft Corporation Distinguished Engineer, and lauded for technical leadership and contributions to the company.

Shum received a doctorate in robotics from the School of Computer Science at Carnegie Mellon University, an MS from Hong Kong University, and a BS from Southeast University in China.

Research 2.0

Niklaus Wirth was born in February 1934 in Winterthur, Switzerland. He studied electrical engineering at ETH (Federal Institute of Technology) in Zürich, graduated in 1959, received an MSc degree from Laval University in Quebec, and a PhD from the University of California at Berkeley in 1963.

Wirth has been an Assistant Professor of Computer Science at Stanford University (1963-67) and, after his return to Switzerland, a Professor of Informatics at ETH from 1968 through 1999. His principal areas of contribution were programming languages and methodology, software engineering, and the design of personal workstations. He designed the programming languages Algol W (1965), Pascal (1970), Modula-2 (1979), and Oberon (1988), was involved in the methodologies of Structured Programming and Stepwise Refinement, and designed and built the workstations Lilith, with high-resolution display, mouse, and high-level language compiler in 1980, and Ceres in 1986.

He has published several text books for courses on programming, algorithms and data structures, and logical design of digital circuits. He has received many prizes and honorary doctorates, including the Turing Award (1984), the IEEE Computer Pioneer (1988), the Award for outstanding contributions to Computer Science Education (ACM 1987), and the IBM Europe Science and Technology Award in 1989.

A Brief History of Software Engineering

We present a personal perspective of the Art of Programming. We start with its state around 1960 and follow its development to the present day. The term Software Engineering became known after a conference in 1968, when the difficulties and pitfalls of designing complex systems were frankly discussed. A search for solutions began. It concentrated on better methodologies and tools. The most prominent were programming languages reflecting the procedural, modular, and finally object-oriented styles. Software engineering is intimately tied to their emergence and improvement. Also of significance were efforts of systematizing, even automating, program documentation and testing. Ultimately, analytic verification and correctness proofs were to replace testing.

More recently, the rapid growth of computing power made it possible to apply computing to ever more complicated tasks. This trend dramatically increased the demands on software engineers. Programs and systems became complex and almost impossible to fully understand. However, the sinking cost and the abundance of computing resources inevitably reduced the care for good design. Quality seemed too extravagant, a loser in the race for profit. We should be concerned about the resulting deterioration in quality. Our limitations are no longer given by slow hardware, but by our own intellectual capability. Programming, after all, is NOT easy. From experience we know that most programs could be significantly improved, made more reliable, economical, comfortable to use. What can we do?

Professor Pat Hanrahan is on the faculty of the Computer Science and Electrical Engineering departments at Stanford University. His current research involves rendering algorithms, high performance graphics architectures, and systems support for graphical interaction. He also has worked on raster graphics systems, computer animation and modeling, and scientific visualization, in particular, volume rendering.

Pat is a member of the National Academy of Engineering. He has received technical awards from the American Academy of Motion Picture Arts and Sciences and from ACM SIGGRAPH (Stephen A. Coons Award).

Pat received a doctorate degree from University of Wisconsin in 1986.

The Big Idea in Computer Graphics

Ed Lazowska is professor and chair of the Department of Computer Science & Engineering at the University of Washington. Dr. Lazowska received his PhD from the University of Toronto in 1977. He has been at the University of Washington since that time.

Ed’s research concerns the design and analysis of distributed and parallel computer systems. Dr. Lazowska is a member of the NSF CISE Advisory Committee, Chair of the Computing Research Association, a member of DARPA ISAT, and a member of the Technical Advisory Board for Microsoft Research. He is a member of the NRC’s Computer Science and Telecommunications Board (CSTB) and served on the CSTB committee that produced «Evolving the High Performance Computing and Communications Initiative to Support the Nation’s Information Infrastructure.» He is a Member of the National Academy of Engineering, and a Fellow of the ACM and of the IEEE. He is a leader in the Learning Federation, a group that is concerned with using information technology to improve learning at the college level.

Computer Science: Past, Present, and Future

The next 10 years of advances in computer science will be far more significant and far more interesting than the past decade. Ed will review the progress in the field, and present a number of «grand challenge» problems that computer scientists should be prepared to tackle in the coming decade.