2007年“二十一世纪的计算”学术研讨会

Lenore Blum is Distinguished Career Professor of Computer Science at Carnegie Mellon University where she co-Directs the ALADDIN Center (opens in new tab) for Algorithm ADaptation, Dissemination and INtegration and is faculty advisor to the student organization, Women@SCS (opens in new tab).

She received her Ph.D. in mathematics from M.I.T. in 1968 (the same year Princeton first allowed women to enter their graduate program). She then taught at UC Berkeley, founded the Mills College Department of Mathematics and Computer Science (the first CS department at a women’s college), was senior researcher at the International Computer Science Institute and Deputy Director of the Mathematical Sciences Research Institute in Berkeley. Straddling the historic handover of Hong Kong from Britain to China on July 1, 1997, Lenore spent two years, 1996-1998, at the City University of Hong Kong as Visiting Professor of Mathematics and Computer Science. Here she completed her book, Complexity and Real Computation, with colleagues and co-authors Felipe Cucker, Mike Shub and Steve Smale. Her research, from her early work in model theory and differential fields (logic and algebra) to her more recent work in developing a theory of computation and complexity over the real numbers (mathematics and computer science), has focused on merging seemingly unrelated areas.

Lenore is also well known for her work in increasing the participation of girls and women in mathematics and scientific fields. In 2005, in recognition of this work, she received the US Presidential Award for Excellence in Science, Mathematics and Engineering Mentoring. She has served the professional community in numerous capacities including as President of the Association for Women in Mathematics, vice-President of the American Mathematical Society and is currently a member of the M.I.T. Mathematics Visiting Committee. Her most recent creation, and passion, is Project Olympus (opens in new tab), a high tech innovation center at Carnegie Mellon.

Lenore first visited China in 1979 as universities were re-opening after years of turmoil. She is excited to see the amazing changes that have taken place in less than 20 years and to meet current students with promise to become the innovative thinkers for the 21st Century.

Presentation Title: Machine Understanding / Thinking Out of the Box

Abstract:
Machine Understanding: Machine Learning is a well-researched area of computer science. It has many applications from helping stem the current flood of email spam to recognizing objects in visual images.

Manuel will present a new area — currently under construction — which we call Machine Understanding. The goal of Machine Understanding is to make Machine Learning more robust by extending it to high-level (abstract) relationships between learned concepts. In our approach, a machine understands material by searching for and detecting significant properties of what it is studying, attaching names (mnemonics) to those properties, preparing templates (models) for future use, then continuing recursively to build on this foundation.

To give an idea how this works, we will look at Freudenthal’s LINCOS (LINgua COSmica), a language designed for communication with extraterrestrial beings. These beings are presumed to be intelligent aliens who have no other knowledge of our world or language except what is conveyed by LINCOS itself. We discuss the design of a program/computer that can learn on its own to understand any language such as LINCOS that is designed to be inferable by an intelligent motivated but otherwise unknowledgeable entity.

This is joint work with Ryan Williams.

Thinking Out of the Box: What does it mean to think out of the box? How is it done? What are some examples? Yun Ying, a semi-retired physics professor in Nanjing has been promoting out-of-the-box thinking in her physics classes, see:
http://www.sciencemag.org/cgi/content/full/317/5834/74b (opens in new tab)

Lenore will discuss our own experience with promoting out-of-the-box thinking, both in education (with examples from CS4ALL, a program for high school (and K-8) teachers of computer science) and in the research arena (with examples from the ALADDIN Center which promotes synergy between algorithm theory and practice).

Manuel Blum, the Bruce Nelson Professor of Computer Science at Carnegie Mellon University, is a pioneer in the field of theoretical computer science and the winner of the 1995 Turing Award in recognition of his contributions to the foundations of computational complexity theory and its applications to cryptography and program checking, a mathematical approach to writing programs that check their work.

He was born in Caracas, Venezuela, where his parents settled after fleeing Europe in the 1930s, and came to the United States in the mid-1950s to study at the Massachusetts Institute of Technology. While studying electrical engineering, he pursued his desire to understand thinking and brains by working in the neurophysiology laboratory of Warren S. McCulloch and Walter Pitts, then concentrated on mathematical logic and recursion theory for the insight it gave him on brains and thinking. He did his doctoral work under the supervision of Artificial Intelligence pioneer Marvin Minsky, and earned a Ph.D. in mathematics in 1964.

He began his teaching career at M.I.T. as an assistant professor of mathematics and, in 1968, joined the faculty of the University of California at Berkeley as tenured associate professor of electrical engineering and computer sciences. He was named the Arthur J. Chick Professor of Computer Science in 1995. Dr. Blum accepted his present position at Carnegie Mellon in 2001. The problems he has tackled in his long career include, among others, methods for measuring the intrinsic complexity of problems. Blum’s Speedup theorem is an important proposition about the complexity of computable functions. The Blum axioms give a machine-independent way to understand the complexity of computation, whether that computation is done by human or by computer.

A member of the National Academy of Science and the National Academy of Engineering, he is a fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, and the Institute of Electrical and Electronics Engineers. Dr. Blum has held a Sloan Foundation Fellowship and received a University of California at Berkeley Distinguished Teaching Award and Sigma Xi’s Monie A. Ferst Award, among other honors. He is the author of more than 50 papers published in leading scientific journals and has supervised the theses of 30 doctoral students, many of whom are today’s leaders in the field.

Presentation Title: Machine Understanding / Thinking Out of the Box

Abstract:
Machine Understanding: Machine Learning is a well-researched area of computer science. It has many applications from helping stem the current flood of email spam to recognizing objects in visual images.

Manuel will present a new area — currently under construction — which we call Machine Understanding. The goal of Machine Understanding is to make Machine Learning more robust by extending it to high-level (abstract) relationships between learned concepts. In our approach, a machine understands material by searching for and detecting significant properties of what it is studying, attaching names (mnemonics) to those properties, preparing templates (models) for future use, then continuing recursively to build on this foundation.

To give an idea how this works, we will look at Freudenthal’s LINCOS (LINgua COSmica), a language designed for communication with extraterrestrial beings. These beings are presumed to be intelligent aliens who have no other knowledge of our world or language except what is conveyed by LINCOS itself. We discuss the design of a program/computer that can learn on its own to understand any language such as LINCOS that is designed to be inferable by an intelligent motivated but otherwise unknowledgeable entity.

This is joint work with Ryan Williams.

Thinking Out of the Box: What does it mean to think out of the box? How is it done? What are some examples? Yun Ying, a semi-retired physics professor in Nanjing has been promoting out-of-the-box thinking in her physics classes, see:
http://www.sciencemag.org/cgi/content/full/317/5834/74b (opens in new tab)

Lenore will discuss our own experience with promoting out-of-the-box thinking, both in education (with examples from CS4ALL, a program for high school (and K-8) teachers of computer science) and in the research arena (with examples from the ALADDIN Center which promotes synergy between algorithm theory and practice).

Tony Chan’s scientific background is in mathematics, computer science and engineering. He received his B.S. and M.S. degrees (in engineering) from CalTech and his Ph.D. (in computer science) from Stanford University, worked at CalTech (Applied Math) as a Research Fellow, and taught at Yale (Computer Science) before joining the UCLA faculty in 1986 as Professor of Mathematics. He became Chair of the Department of Mathematics in 1997. Currently, he also holds honorary joint appointments with the BioEngineering Department and the Computer Science Department at UCLA.

He was one of the principal investigators who made the successful proposal to NSF to form the Institute for Pure and Applied Mathematics (IPAM) at UCLA, with a vision to promote collaborations between the mathematical sciences with the general scientific and engineering disciplines. He served as IPAM’s Director from 2000-2001. From July 2001 to June 2006, he served as Dean of Physical Sciences at UCLA, overseeing a Division with over 200 faculty FTEs, 700 graduate students, 700 undergraduate majors and $70M annual federal research support. Since October 2006, he has been on temporary leave from UCLA to serve as Assistant Director of the Directorate for Mathematical and Physical Sciences at the National Science Foundation. The MPS Directorate encompasses five Divisions (Astronomy, Chemistry, Materials Research, Mathematical Sciences and Physics) and is the largest Directorate at NSF with an annual budget of just over $1B. He had served as founding co-Director of the Center for Computational Biology at UCLA, an NIH-funded interdisciplinary center under the NIH Roadmap initiative, until he had to relinquish that role to take the position at NSF.

He is an active member of many scientific societies, including the Society of Industrial & Applied Mathematics (where he is currently a member of the Board of Trustees), the American Mathematical Society and the Institute of Electrical & Electronic Engineers. He has served on the editorial boards of many journals in mathematics and computing, including SIAM Review, SIAM J. Sci. Comp. and the Asian J. of Math and is one of three Editors-in-Chief of Numerisch Mathematik. He co-wrote the proposal to start a new SIAM Journal of Imaging Sciences and serves on its inaugural editorial board. He formerly served on the NSF Mathematical and Physical Sciences Advisory Committee and is a current member of the US National Committee on Mathematics, and represented the US to the 2006 General Assembly of the International Mathematics Union in Spain.

His current research interests include mathematical image processing and computer vision, VLSI physical design and computational brain mapping. He has published over 200 refereed papers and is one of the most cited mathematicians according to http://isihighlycited.com/. He has mentored over 25 Ph.D. students and 15 postdoctoral fellows.

He has given many invited plenary talks at national and international meetings, including the 1989 SIAM National Meeting, the 2002 Joint Mathematics Meeting, the 2005 Asian Mathematics Conference, and the 2001 International Conference of Chinese Mathematicians. He has won two Best Paper awards (IEEE and ISPD). He has also served on many advisory committees, including the Lawrence Livermore National Lab, and the Hausdorf Center for Math in Bonn.

Presentation Title: Cyber-enabled Scientific Discovery

Abstract:
Computational simulation has become one of three main ways to explore modern science, complementary to theory and experiment. This has had enormous and fundamental impact in the advent of science and engineering. The US National Science Foundation, being the main federal agency responsible for supporting basic science and engineering, has made major commitments and investments in the broad area of Cyber-enabled scientific discovery. We take a broad-based approach and consider the whole spectrum of activities ranging from modeling complex systems, fast and accurate computational algorithms, cyber-infrastructures to provide both capability and capacity, handling of and extracting knowledge from large data sets, and virtual organizations to facilitate collaboration of scientific communities. In this talk, I’ll review some of the activities and investments that NSF has started in this area.

John E. Hopcroft is the IBM Professor of Engineering and Applied Mathematics in Computer Science at Cornell University. He received his B.S. (1961) from Seattle University and his M.S. (1962) and Ph.D. (1964) in electrical engineering from Stanford University. His research centers on theoretical aspects of computer science. He served as dean of Cornell University’s College of Engineering from 1994 until 2001. He is a member of the National Academy of Engineering and a fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the Institute of Electrical and Electronics Engineers, and the Association of Computing Machinery. In 1986 he was awarded the A. M. Turing Award for his research contributions. In 1992, he was appointed by President Bush to the National Science Board, which oversees the National Science Foundation, and served through May 1998. He received the IEEE Harry Goode Memorial Award in 2005 and the Computing Research Association’s Distinguished Service Award in 2007. He serves on the Packard Foundation’s Science Advisory Board and is a member of the board of directors of the Boyce Thompson Institute.

Presentation Title: Future Directions in Computer Science

Abstract:
The last forty years have seen computer science evolve as a major academic discipline. Today the field is undergoing a major change. Some of the drivers of this change are the internet, the World Wide Web, large quantities of information in digital form and wide spread use of computers for accessing information. This change is requiring universities to revise the content of computer science programs. This talk will cover the changes in the theoretical foundations needed to support information access in the coming years.

Rico Malvar is a Distinguished Engineer at Microsoft, and the Managing Director of Microsoft Research in Redmond, WA. He holds a Ph.D. from M.I.T. in Electrical Engineering and Computer Science. Before Joining Microsoft in 1997, he was a Vice President of Research and Advanced Development at PictureTel Corporation, and prior to that he was with the faculty of University of Brasilia for 14 years. As the Director at Microsoft Research, he oversees the activities of over 25 research groups, in many areas related to computers science. His technical interests include multimedia signal compression and enhancement, fast algorithms, multi-rate filter banks, and wavelet transforms; he has over 140 publications and over 70 patents in those areas. Dr. Malvar is a Fellow of the IEEE, a member of the editorial board of the journal Applied and Computational Harmonic Analysis, and a former Associate Editor of the journal IEEE Transactions on Signal Processing. He received the Young Scientist Award from the Marconi International Fellowship in 1981, the Best Paper Award in Image Processing from the IEEE Signal Processing Society in 1992, the 2002 Technical Achievement Award, also from the IEEE SP Society, and the Wavelet Pioneer Award from the SPIE in 2004.

Presentation Title: Ensuring Microsoft’s Future: An Overview of Microsoft Research

Abstract:
Microsoft’s continuing success in the software industry depends heavily on successful deployment of innovative technologies, and Microsoft Research is in the forefront of driving technological innovation for Microsoft. In this talk we present an overview of Microsoft Research; we discuss the culture and missions of our Research Labs, our emphasis on diversity, and our strong ties with Academia, which are fundamental for the success of a true research organization. We present an overview of the research areas and groups, and several examples of advanced technologies developed at Microsoft Research.

Currently charged with oversight of Microsoft Research 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 a professor of computer science at Carnegie Mellon University. During his tenure there, 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 a master of Science degree (1977) and doctorate (1980) in Computer Science from the University of Rochester. He graduated with honors in mathematics and comparative literature from Stanford University in 1974.

Presentation Title: 10 years into the future

Abstract:
By looking at technologies in research labs today you can get insights into what opportunities technology will enable during the next 10 years. In this talk I will look at some exciting research technologies and their implications on the world of 2017.

S. Shankar Sastry is currently the Dean of Enginnering at University of California, Berkeley. From 2004 to 2007 he was the Director of CITRIS (Center for Information Technology in the Interests of Society) an interdisciplinary center spanning UC Berkeley, Davis, Merced and Santa Cruz. In Februrary 2007, he was appointed the faculty co-director of the Blum Center for Developing Economies. He has served as Chairman, Department of Electrical Engineering and Computer Sciences University of California, Berkeley from January, 2001 through June 2004. From 1999-early 2001, he served as Director of the Information Technology Office at DARPA. From 1996-1999, he was the Director of the Electronics Research Laboratory at Berkeley.

Dr. Sastry received his Ph.D. degree in 1981 from the University of California, Berkeley. He was on the faculty of M.I.T. as Asst. Professor from 1980-82 and Harvard University as a chaired Gordon Mc Kay professor in 1994. His areas of personal research are embedded and autonomous software for unmanned systems (especially aerial vehicles), computer vision, computation in novel substrates such as quantum computing, nonlinear and adaptive control, robotic telesurgery, control of hybrid and embedded systems, network embedded systems and software. Most recently he has been concerned with cybersecurity and critical infrastructure protection, and has helped establish an NSF Science and Technology Center, TRUST (Team for Research in Ubiquitous Secure Technologies)

He has coauthored over 350 technical papers and 9 books, including Adaptive Control: Stability, Convergence and Robustness (with M. Bodson, Prentice Hall, 1989) and A Mathematical Introduction to Robotic Manipulation (with R. Murray and Z. Li, CRC Press, 1994), Nonlinear Systems: Analysis, Stability and Control (Springer-Verlag, 1999), and An Invitation to 3D Vision: From Images to Models (Springer Verlag, 2003) (with Y. Ma. S. Soatto, and J. Kosecka). Dr. Sastry served as Associate Editor for numerous publications, including: IEEE Transactions on Automatic Control; IEEE Control Magazine; IEEE Transactions on Circuits and Systems; the Journal of Mathematical Systems, Estimation and Control; IMA Journal of Control and Information; the International Journal of Adaptive Control and Signal Processing; Journal of Biomimetic Systems and Materials. He is currently an Associate Editor of the IEEE Proceedings.

Dr. Sastry was elected into the National Academy of Engineering in 2001 and the American Academy of Arts and Sciences (AAAS) in 2004. He also received the President of India Gold Medal in 1977, the IBM Faculty Development award for 1983-1985, the NSF Presidential Young Investigator Award in 1985 and the Eckman Award of the of the American Automatic Control Council in 1990, the Ragazzini Award for Distinguished Accomplishments in teaching in 2005, an M.A. (honoris causa) from Harvard in 1994, Fellow of the IEEE in 1994, the distinguished Alumnus Award of the Indian Institute of Technology in 1999, and the David Marr prize for the best paper at the International Conference in Computer Vision in 1999.

He has supervised over 50 doctoral students to completion and over 50 M.S. students. His students now occupy leadership roles in several locations and on the faculties of many major universities in the United States and abroad.

Presentation Title: Generalized Principal Component Analysis: An Introduction

Abstract:
There are a large number of problems in which we encounter the problem of modeling large amounts of data, by what is referred to as a “mixture of models”, that is to say that the data can be segmented into finitely many sub components, each of which can be separately modeled. In the context of the identification of hybrid systems it is easy to see how this would arise when the input-output behavior depends on the “discrete state” of the hybrid system. Of course, the applications in computer vision, signal and image processing and indeed more generally in statistics are extremely numerous. This area of work has found a tremendous outpouring of effort and methods in recent years in the signal processing, hybrid systems, statistics and learning systems literature. However, it is our perception that the conceptual and theoretical underpinnings of the bulk of the literature are weak.

In the course of a recent set of papers with Yi Ma of the University of Illinois, Urbana Champaign and Rene Vidal of Johns Hopkins University and their students, we have developed what we believe to be an interesting new approach to simultaneously segmenting and modeling data from mixtures of models. The heart of our approach lies in what is called “Generalized Principal Component Analysis”. This in turn has many connections with such classical problems as Hilbert’s Nullstellensatz and many unsolved problems in statistics. In my talk at this workshop, I will give a brief overview of the approaches and their applications to date. The work is being incorporated into a monograph to appear in 2008 and a preview of this monograph is available at: http://black.csl.uiuc.edu/~yima/psfile/book-VMS.pdf. (opens in new tab)

The website for the code for GPCA is http://perception.csl.uiuc.edu/gpca/ (opens in new tab)

Dr. Harry Shum is a Corporate Vice President at Microsoft. He oversees the research activities at Microsoft Research Asia and the lab’s collaborations with universities in Asia Pacific. Recently, Dr. Shum has taken the additional responsibility of driving the long-term and short-term technology investments in search and advertising at Microsoft.

Dr. Shum is an Institute of Electrical and Electronics Engineers (IEEE) Fellow and an American Computational Machinery (ACM) Fellow. He serves on the editorial board of the International Journal of Computer Vision, and is a Program Chair of the International Conference of Computer Vision (ICCV) 2007. Dr. Shum has published more than 100 papers in computer vision, computer graphics, pattern recognition, statistical learning, and robotics. He holds more than 50 U.S. patents.

Dr. Shum joined Microsoft Research in 1996 where he worked in Redmond, WA as a researcher on computer vision and computer graphics. In 1999, Shum moved to Beijing to help start Microsoft Research China (later renamed Microsoft Research Asia). His tenure there began as a research manager and subsequently moved up to Assistant Managing Director, Managing Director of Microsoft Research Asia, Distinguished Engineer, and Corporate Vice President. In 2007, Shum became Microsoft Corporate Vice President, and was lauded for his leadership in technology and management.

Dr. Shum received a doctorate in robotics from the School of Computer Science at Carnegie Mellon University in Pittsburgh, PA. In his spare time, he enjoys playing basketball, rooting for the Pittsburgh Steelers, and spending quality time with his family.

Presentation Title: Internet Services: Technology Challenges and Business Opportunities

Abstract:
The internet has drastically changed the way people live, communicate, share, entertain, learn and do business. Novel internet services continue to emerge and bring new user experiences and business opportunities. In this talk, through demonstration of the latest research results from Microsoft Research Asia, Dr. Shum will analyze the unique features of the internet and internet services, identify the key technology challenges, and forecast the huge business opportunities with the Internet Services.

Victor Zue is the Delta Electronics Professor of Electrical Engineering and Computer Science at M.I.T. and the Director of the Institute’s Computer Science and Artificial Intelligence Laboratory (CSAIL). In the early part of his career, Victor conducted research in acoustic phonetics and phonology, codifying the acoustic manifestation of speech sounds and the phonological rules governing the realization of pronunciation in American English. Subsequently, his research interest shifted to the development of spoken language interfaces to make human-computer interactions easier and more natural. Between 1989 and 2001, he headed the Spoken Language Systems Group at the M.I.T. Laboratory for Computer Science, which has pioneered the development of many systems that enable a user to interact with computers using spoken language.

Outside of M.I.T., Victor has consulted for many multinational corporations, and he has served on many planning, advisory, and review committees for the US Department of Defense, the National Science Foundation, and the National Academies of Science and Engineering. From 1996-1998, he chaired the Information Science and Technology, or ISAT, study group for the Defense Advanced Research Projects Agency of the U.S. Department of Defense, helping the DoD formulate new directions for information technology research. In 1999, he received the DARPA Sustained Excellence Award. Victor is a Fellow of the Acoustical Society of America, and a member of the U.S. National Academy of Engineering.

Presentation Title: On Organic Interfaces

Abstract:
For over four decades, the research community has taken remarkable strides in advancing human language technologies. This has resulted in the emergence of spoken dialogue interfaces that can communicate with humans on their own terms. For the most part, however, we have assumed that these interfaces are static; it knows what it knows and doesn’t know what it doesn’t. In my opinion, we are not likely to succeed until we can build interfaces that behave more like organisms that can learn, grow, reconfigure, and repair themselves, much like humans. In this talk, I will argue my case and outline some new research challenges.

Andrew Herbert is a distinguished engineer, a fellow of the Royal Academy of Engineering and managing director of Microsoft Research in Cambridge, England. Initially joining Microsoft Research in 2001, as an assistant director, in March 2003 he succeeded the founding director, Roger Needham.

Herbert’s research interests include networks, operating systems, programming languages and distributed information sharing.

Before joining Microsoft Research in 2001, he was director of Advanced Technology at Citrix Systems Inc, where he was instrumental in steering the company toward internet thin-client technologies and initiating development of products for web-based application deployment and for the emerging application service provider market.

Herbert joined Citrix in 1998 from Digitivity Inc, which he founded in 1996 to develop a product to enable secure deployment of Java clients for business-to-business applications. Digitivity was spun-off from APM Ltd, a research and consulting company Herbert founded in 1985. APM managed ANSA, an industry-sponsored programme of research and advanced development into the use of distributed systems technology to support applications integration in enterprise-wide systems. ANSA’s work included research on support for interactive multimedia services, object technology for World Wide Web applications, distributed systems management, mobile object systems and security for electronic commerce. Herbert led ANSA’s technical programme, built up its team, created its architecture, and made ANSA known and respected in the industry.

Before starting ANSA in 1985, Herbert was a faculty member in the Computer Laboratory at the University of Cambridge in England, where he worked with Roger Needham and Maurice Wilkes on seminal developments in local area networks (LANs) and distributed computing. In 1979 Herbert helped Needham and Wilkes edit «The Cambridge CAP Computer and Its Operating System», and in 1982 he co-authored «The Cambridge Distributed Computing System» with Needham. In 2003, Herbert co-edited a monograph of papers written in tribute to Needham, «Computer Systems: Theory, Technology and Applications», with Karen Spärck Jones.

Herbert is a fellow of Wolfson College Cambridge, a member of St. John’s College Cambridge, and a liveryman of the City of London Worshipful Company of Information Technologists. In 1975 he graduated from the University of Leeds with a BSc in computational science and in 1978 with a Ph.D. from Cambridge University in computer science.

Presentation Title: Software Transactions

Abstract:
Web software is necessarily concurrent: a server has to process requests from many clients and rich client interfaces often connect to multiple web service simultaneously. Coupled with the hardware trend towards multi-core and many-core processors it is increasingly urgent to give programmer better abstractions for handling parallel computation and concurrent access to data. In most current languages concurrency features consist of a thread library and some basic synchronization based on locks, a model that has not changed much since the late 60s. These models are notoriously difficult to use and debug and do not readily permit programmes to be built by combining independent software components. Recent work on software transactions has shown promise as an approach that overcomes these problems and the ideas have been widely explored by researchers in the Microsoft Cambridge and Redmond laboratories. The talk will introduce the key design and implementation concepts behind software transaction memory and discuss a number of important open issues.