Professor Emma Brunskill
it is relevant to ... numerous other important fields
I work on decision making under uncertainty, artificial intelligence and machine learning. I think there have been many exciting advances.. autonomous driving cars, Watson, Siri... In my subarea I am particularly excited by the work on learning algorithms for sequential decision making that have stronger performance guarantees. I'd like our vision for what computer science is, and the application areas it covers, to expand much further. Many people outside of computer science still think computer science = programming, whereas it is relevant to marketing, healthcare, computer-assisted education, and numerous other important fields.
Professor Mor Harchol-Balter
designing new resource allocation policies for server farms and distributed systems
Mor Harchol-Balter is the Associate Department Head of Computer Science at Carnegie Mellon University. She received her doctorate from the Computer Science department at the University of California at Berkeley under the direction of Manuel Blum. She is a recipient of the McCandless Chair, the NSF CAREER award, the NSF Postdoctoral Fellowship in the Mathematical Sciences, multiple best paper awards, and several teaching awards, including the Herbert A. Simon Award for Teaching Excellence.
She is heavily involved in the ACM SIGMETRICS research community, and recently served as Technical Program Chair for SIGMETRICS. Mor's work focuses on designing new resource allocation policies (load balancing policies, power management policies, and scheduling policies) for server farms and distributed systems in general. Her work spans both queueing analysis and systems implementation, and emphasizes integrating measured workload distributions into the problem solution.
a new methodological framework for designing programming languages
My research area is programming languages. The history of my field is full of connections to formal logic. In the past ten years, focusing, a technique developed for optimizing proofs in logical calculi, has yielded groundbreaking insights in type theory and logic programming, creating a new methodological framework for designing programming languages. I'm eager to see this work influence the development of theories for interactivity and multiple loci of computation. After I graduate, I want to apply proof theory to tools for interactive creation, e.g. develop programming languages for game design.
logic, approximation algorithms, and game theory
I am a second-year computer science PhD student at Carnegie Mellon University. My advisers are Avrim Blum and Frank Pfenning. I am generally interesting in theory, specifically logic, approximation algorithms, and game theory. I am supported by an NSF GFRP fellowship, as well as the Microsoft Research Graduate Women's Scholarship. Some of my publications include "How Good Are Optimal Cake Divisions?", "An Algorithm with Additive Error for Near-Perfect Phylogeny Construction", "A Proof-Carrying Filesystem with Revocable and Use-Once Certificates", and "Security-Typed Programming within Dependently-Typed Programming".
Leigh Ann Sudol-DeLyser
strong evidence that one of the newest scientific fields is maturing
Cognitive Psychology Education
I am pursuing a self-defined degree in Computer Science and Cognitive Psychology. I study computer science education, specifically the underlying cognitive processes that lead to robust learning of CS concepts and skills. My thesis focuses on the effect of feedback regarding algorithmic abstractions on student performance when learning to program.
Over the past 10 years the acceptance of environments like Alice and Scratch as viable for novice computer scientists, allowing them to focus on concepts and not syntax has helped not only extend computer science education to lower grades, but also help change the way that beginners can approach CS. I am most excited about CS becoming a mature discipline. The past 5 years have seen computer science play an increasingly important role in all of the sciences and humanities. Our growth to not only working on problems within our own domain such as algorithms and systems, but also reaching out to fields such as computational biology and even education are strong evidence that one of the newest scientific fields is maturing.
file systems emerging to process hundreds of petabyte data
I work on distributed file systems to store big data. I believe SSDs, and perhaps nonvolatile memories, will play an important role in storage systems in the future and there will be new file systems emerging to process hundreds of petabyte data with thousands of machines.
Over the past 10 years, there have been many exciting developments within this field. For example, file systems for Data-Intensive Scalable Computing (DISC), such as Google file systems and Hadoop file systems, were developed for Internet services and are popular in cloud computing. The idea of moving computation to data changes the architecture of these systems. Instead of using separate computing and storage nodes, each node in these systems serve both for computing and storage.
I am working on a number of projects right now, and after graduation I hope to continue my work with the Academy for Software Engineering in New York City. I hope to initially find a faculty job in either CS or CS Education and work to start a center for computer science education at a major research institution.
Professor Lenore Blum
computation and complexity over the real numbers
Lenore Blum is Distinguished Career Professor of Computer Science at Carnegie Mellon. She is also the Founding Director of Project Olympus, a founder and Faculty Advisor for Women@SCS, and Co-Director of the NSF-ITR seeded ALADDIN Center. Project Olympus is a good example of Blum's creativity and determination to make a real difference in the academic community and the world beyond. Olympus has two main aims: to bridge the gap between cutting-edge university research/innovation and economy-promoting commercialization for the benefit of our communities and to creating a climate, culture and community to enable talent and ideas to grow in the region.
Blum's 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. She is particularly interested in research concerning the complexity of algorithms that solve systems of polynomial equations over the reals or complex numbers. For example in 1989, she, along with Steve Smale and Mike Shub, introduced a theory of computation and complexity over an arbitrary ring or field R that has been widely adopted by the foundations of computational mathematics community. This research also involves transfer results and problems that appear in the interface between the discrete and the continuous. In June 2012, she will be a keynote speaker at the Turing Centenary Conference in Cambridge, England.
Blum is also well known for her work on increasing the participation of women in math and computer science. She was one of the founders of the Association for Women in Mathematics, the Expanding Your Horizons Network, and the CS4HS workshops. In 2004 she received the Presidential Award for Excellence in Science, Mathematics and Engineering Mentoring (PAESMEM) and more recently she was recognized on the list of "Famous Women in Computer Science" compiled by the Anita Borg Center for Women and Technology.
Professor Manuela Veloso
Collaborate, Observe, Reason, Act, and Learn
Manuela M. Veloso is Herbert A. Simon Professor of Computer Science at Carnegie Mellon University. She directs the CORAL research laboratory, for the study of robots that Collaborate, Observe, Reason, Act, and Learn, www.cs.cmu.edu/~coral. Professor Veloso is a Fellow of the Association for the Advancement of Artificial Intelligence, and the President of the RoboCup Federation.
She recently received the 2009 ACM/SIGART Autonomous Agents Research Award for her contributions to agents in uncertain and dynamic environments, including distributed robot localization and world modeling, strategy selection in multiagent systems in the presence of adversaries, and robot learning from demonstration. Professor Veloso and her students have concretely researched in the area of robot soccer and have successfully participated in several RoboCup international competitions. Professor Veloso is the author of one book on "Planning by Analogical Reasoning" and editor of several other books. She is also an author in over 200 journal articles and conference papers.
Professor Nancy Pollard
to create robots that are more capable
My research goal is to understand dexterity. I want to understand how people use their hands (and tools, props, and other parts of their bodies) to manipulate objects in everyday life. I apply what I learn in computer graphics . to create animated characters that can appear more intelligent . and in robotics . to create robots that are more capable.
Think about how you lift a pencil and place it in your hand to write . or select a wrench from a toolbox and maneuver it into the palm of the hand in order to use it. These actions take only an instant, but the process is quite complex, involving many constantly changing contacts. It is out of our reach to robustly accomplish such tasks for robots right now. We do not fully understand how to perform such actions reliably in the face of everyday uncertainties. What interaction between learned behavior, use of our senses, and modulation of mechanical characteristics of our hand makes it possible for us to do these tasks successfully time after time?
I would say the most significant development over the past 10 years has been improvements in our ability to collect quantitative data as people perform everyday tasks. Many graphics and robotics laboratories have ready access to motion capture equipment that allows us to precisely measure how people move. This ready access has led to a revolution in how we consider identifying solutions to motion problems. If we have seen such a problem before, we can simply look up the answer! However, there are limitations to this approach, and what I find exciting about the future is that more and more researchers in computer graphics and in robotics are studying human anatomy, human motor control, and neuroscience. Insights from these fields may dramatically change the way we do research. For example, when people pick up a wrench, the way they do it is not perfect. High speed cameras show many .failures. and a good bit of fumbling around. Yet people can successfully maneuver the wrench into the hand 100% of the time. I believe that understanding the processes that make us able to cope with such .failures. . and the knowledge that we don.t have to be perfect to succeed -- can completely change the way we program robots in the future.
the web became 'intelligent'
My research interests lie in data mining in large graphs and machine learning. For me, probably the most exciting development in this field over the past 10 years is that the web became .intelligent.. I am hoping that in the future, we will see extraction of more and useful information from the data with massive parallel computations, better recommendation systems, accurate machine translation and speech understanding. After I graduate, I am most interested in academia where I can satisfy my appetite for research and teaching.
building intelligent agents for tutoring purposes
My research area includes artificial intelligence and intelligent tutoring system. I am working on building an intelligent agent that models human-like knowledge acquisition for math and science - http://www.simstudent.org/. The most exciting development in this field over the past 10 years would be building intelligent agents for tutoring purposes. Here are two examples: http://en.wikipedia.org/wiki/ACT-R and http://ict.usc.edu/projects/learning_sciences. A learning agent that models human-level knowledge acquisition would be one thing that I am most eager to see for the future of Computer Science. I'd like to continue research either as a faculty or in a research lab.
providing cyber-physical systems you can bet your life on
A bug on your windshield doesn't do much damage, but a bug in the software that controls your engine, brakes, or steering is catastrophic. Driver assistance technologies, like adaptive cruise control and automatic braking protocols, have the potential to increase the efficiency of crowded roads, but even more compelling is their capacity for reducing the number of accidents and fatalities resulting from driver-error. Yet, increased dependence on this next generation technology, however promising it may be, is only wise when its reliability has been ensured and regulated. As these technologies gain popularity and increase in complexity, this difficult job gets even tougher.
My research strives to find automated methods for formal verification of these systems. So far our research group has discovered several fundamental principles which allow large-scale systems to be verified with modular, mechanized, and semi-automated methods. We have used these methods to give the first mechanized formal verification of adaptive cruise control for a distributed highway system with an arbitrary number of cars.
Currently, I am in my third year of the Computer Science Department Ph.D. program at Carnegie Mellon. As a member of Women@SCS, I contribute to outreach programs for undergraduate women, such as the OurCS conference (Opportunities for Undergraduate Research in Computer Science). I also serve on the Board of Trustees for the Anita Borg Institute for Women and Technology, a non-profit organization which hosts the annual Grace Hopper Conference. Additionally, I am fortunate to have my research supported by a Department of Energy Computational Science Graduate Fellow.
Unfortunately, our research methods can't protect your windshield from insects as you cruise down the highway, but with continued research we can remove the dangerous software bugs in safety-critical systems that standard testing and model checking overlook. This research and the work of many others is bringing us closer to addressing Jeannette Wing's driving question: "How can we provide people with cyber-physical systems they can bet their lives on?"