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Intel Research Seattle Seminars occur on Wednesdays from 4 to 5pm (unless otherwise noted) at the Intel Research Seattle office (location information), and are open to the research community.   We are pleased to have you join us for light refreshments and tea prior to the event to meet the guest speaker and audience.

Upcoming Seminars

• Name: Emma Brunskill
• Date: Wed, June 25, 2008
• Time: 4:00 - 5:00pm
• Host: Ali Rahimi

• Title:  Learning in continuous-valued domains with noisy offset dynamics

• Abstract: Many interesting artificial intelligence planning problems involve continuous-valued state spaces and stochastic, switching dynamics, such as autonomous traversal of varying terrain. In this talk I'll describe a reinforcement learning algorithm for learning and acting in continuous-valued domains with switching noisy offset dynamics. This approach automatically trades off the value of taking an action to better estimate the world dynamics (exploration) versus taking the best action given the current estimate of the dynamics model (exploitation). I'll show that in certain environments the algorithm will perform close to optimally on all but a number of samples that scales polynomially with the state-space dimension. I'll also report the results of an experiment in which a robotic car drives over varying terrain: these results suggest that our dynamics representation can adequately capture real-world dynamics, and that our algorithm can be used to efficiently solve such problems.  This is joint work with Bethany Leffler, Lihong Li, Michael Littman and Nicholas Roy.

• Bio: Emma Brunskill is a doctoral student in Computer Science at the Massachusetts Institute of Technology. She received a B.S. in Computer Engineering and Physics from the University of Washington and a M.Sc. in Neuroscience from Oxford University as a Rhodes scholar. Her research interests span machine learning, robotics, and the role information communication technologies can play in international development.

• Name: Margie Morris
• Date: TBD
• Time: 4:00 - 5:00pm
• Host: Beverly Harrison
• Title: Results from a Mobile Heart Health Study

• Abstract:

• Bio:  

• Name: Brian Koppell
• Date: Wed, July 16, 2008
• Time: 4:00 - 5:00pm
• Host: Ben Greenstein
• Title:

• Abstract:

• Bio:  

Past Seminars

• Name: Michael Beigl
• Date: Mon, June 9, 2008
• Time: 4:00 - 5:00pm
• Host: Anthony LaMarca
• Title:  Collaboration and Integration in Ubiquitous Computing

• Abstract: This talk will present the most recent results in research and development of collaboration-based Ubicomp, and its integration in business and Internet enabled processes. Collaboration, as a main design principle, is e.g. used for exploring low-level networking, namely the Distributed Jam Signalling and Energy Shift Keying concepts. Integration is e.g. used to couple business processes via Internet based systems. This talk will include a presentation of the latest advances in Particle/uPart small wireless sensor system, and Examples of industry-driven research, including hazardous environments, retail-stores and home automation projects.

• Bio: Michael Beigl is professor for Ubiquitous and Distributed systems at the Carl-Friedrich Gauss Faculty of the Technische Universität Braunschweig. Before this he was Research Director of TecO, University of Karlsruhe and guest professer at Keio University in 2005. He obtained both his MSc (1995) and PhD (Dr.-Ing)(2000) from University of Karlsruhe. His research interests cover wireless sensor systems, mobile and ubiquitous networks, distribution of Ubicomp enabled information via Internet, location models and systems, novel sensor technology and context awareness.

• Recorded Talk

• Name: Desney Tan of Microsoft Research
• Date: Wed, May 21, 2008
• Time: 4:00 - 5:00pm
• Host: Jaeyeon Jung
• Title: Cyberware Engineering: Interfacing Directly with Human Physiological Signals

• Abstract: One of the things that distinguishes human beings from other animals is the degree to which we fill our environments with various technologies in order to augment ourselves both physically and cognitively. In fact, we have become human-technology symbionts, quite ineffective at functioning without our various augmentations. In our work, we embrace the notion of human augmentation and propose that there is large untapped potential in interfacing directly with the human body and decoding physiological signals. Specifically, I will describe some of our recent work measuring cognitive load and categorizing images with brain-computer interfaces as well as creating a novel input modality with muscle-computer interfaces. I will also present some of the new projects we are working on in the medical sensing and healthcare domains.

• Bio:  Desney Tan is a Researcher in the Human Centered Computing research area at Microsoft Research, where he manages the Computational User Experiences (CUE) group. He also holds an affiliate faculty appointment in the Department of Computer Science and Engineering at the University of Washington. Desney’s research interests include Human-Computer Interaction and Physiological Computing, specifically Brain-Computer Interfaces. However, he is a somewhat schizophrenic researcher and has worked on projects in domains such as virtual and augmented reality, large and multiple display interfaces, handwriting recognition, as well as adaptive interfaces.
  Desney received his Bachelor of Science in Computer Engineering from the University of Notre Dame in 1996, after which he spent a couple of years building bridges and blowing things up in the Singapore Armed Forces. He later returned to Carnegie Mellon University, where he worked with Randy Pausch and earned his PhD in Computer Science in 2004. In 2007, he was honored as one of MIT Technology Review's Young Innovators Under 35 for his work on brain-computer interfaces.

• Recorded Talk

• Name: Gonzalo Ramos, Live Labs
• Date: Wed, May 14, 2008
• Time: 4:00 - 5:00pm
• Host: Beverly Harrison
• Title: Video Browsing by Direct Manipulation

• Abstract: Time is the dominating dimension we use to experience and navigate through video content, yet sometimes thinking about a video in terms of time is not ideal, e.g., when our focus is locked on the objects or scene captured within. In this presentation, I will talk and demonstrate a novel method for browsing videos by directly dragging their content. This browsing method not only makes space a video’s dominant dimension, but also brings the benefits of direct manipulation to an activity typically mediated by indirect widgets. I will elaborate as to how we support this new type of interactivity by: 1) automatically extracting motion data from videos; and 2) introducing an interaction technique called relative flow dragging that lets users control video playback by moving objects of interest along their visual trajectory. I will demonstrate a video player that implements browsing by direct manipulation and I will share the results of a study showing that this novel browsing method can out-perform the traditional seeker bar in video browsing tasks that focus on visual content rather than time.

• Bio: Gonzalo Ramos received his Honors Bachelors in Computer Science from the University of Buenos Aires where he worked on image compression and wavelets. He later obtained my M.Sc. in Computer Science at the University of Toronto, Canada where he focused on numerical analysis and scientific visualization issues. During his graduate studies, he interned trice at Microsoft Research and was later awarded a Microsoft Research Fellowship. Gonzalo completed his doctoral studies in Computer Science at the University of Toronto where he worked with Professor Ravin Balakrishnan at the Dynamic Graphics Project Lab.

• Recorded Talk

• Name:  Ashish Khisti, MIT
• Date: Tue, May 13, 2008
• Time: 10:00 - 11:30am
• Host:Ben Greenstein

• Title: Multi-layer architectures for secure communication: information theoretic perspectives 

• Abstract: In the traditional network hierarchy, reliability and security are handled in different protocol layers.   In particular, information is encrypted at the application layer, while lower layers provide an error-free transmission link.   Likewise compression is also addressed separately.   However, many emerging applications such as wireless ad hoc networks, sensor networks and pay TV systems are vulnerable to new attacks that are not addressed by such separation.  In this talk, I will present new architectures in which encryption and source/channel coding are performed jointly, and analyze them within an information theoretic framework.  Among other results, we will develop 1) fundamental limits and insights into the role of multiple antennas for protecting confidentiality of information; and 2) source coding techniques for secret key generation and their application to privacy-preserving biometric systems.   As will be apparent, good solutions to such problems bring together techniques not only from information theory, but from convex optimization, random matrix theory, signal processing, and graphical models as well.   As time permits some recent extensions to joint source and channel coding problems with secrecy constrains will also be discussed. 

• Bio: Ashish Khisti received the B.A.Sc degree in Engineering Sciences (Electrical Engineering option) from University of Toronto in 2002 and S.M degree in Electrical Engineering and Computer Sciences from Massachusetts Institute of Technology (MIT) in 2004, where he is currently a PhD candidate. His research interests are in the area of information theory and its applications to wireless and multimedia systems. He is a recipient of the Harold L. Hazen Teaching Award and the Joseph Levin Masterworks award from the EECS department at MIT. He is also a recipient of the Hewlett-Packard PhD fellowship, NSERC fellowship for post-graduate studies, and the Lucent global science scholar award. He has been a visiting student at EPFL-Lausanne, ETH-Zurich, and HP Labs, and a summer intern at Mitsubishi Electrical Research Labs (MERL).

• Recorded Talk

• Name:  Xiaofeng Ren, Toyota Technological Institute at Chicago
• Date: Thur, May 8, 2008
• Time: 10:00 - 11:30am
• Host: Ali Rahimi
• Title: Image and Video Parsing: a Gestalt Approach

• Abstract: The grand goal of computer vision is to parse and label every perceptual structure in images. Such a complete understanding requires the use of a wide range of visual cues and the incorporation of associated processes at all levels of abstraction. I have taken an integrated approach to vision with a focus on mid-level processing, including contour/region grouping and figure/ground organization, a crucial part of visual perception that bridges together low-level signals (e.g. edges and texture) and high-level knowledge (e.g. object shape).  In this talk I will introduce a compact mid-level image representation using piecewise straight approximation of contours and the constrained Delaunay triangulation (CDT). On top of the CDT graph I will develop a unified probabilistic framework for mid-level vision, using conditional random fields (CRF) to enforce consistencies at junctions. For the first time mid-level vision is shown to be both feasible and useful, through quantitative evaluations on large human-annotated datasets. I will also demonstrate that mid-level representation and processing can apply to, and greatly facilitate, many visual tasks such as tracking objects, segmenting objects from background, and recognizing objects in both still images and videos.

• Bio: Xiaofeng Ren received his B.S. from Zhejiang University, his M.S. from Stanford University, and his Ph.D. from the University of California at Berkeley in 2006. He is currently a research assistant professor at the Toyota Technological Institute at Chicago. His research interests lie broadly in the areas of computer vision. His recent work focuses on probabilistic modeling of mid-level vision and its applications in parsing images and video.

• Recorded Talk

• Name:  Andreas Krause, CMU
• Date: Tue, May 6, 2008
• Time: 10:00 - 11:30am
• Host: Ali Rahimi
• Title: Optimizing Sensing from Water to the Web

• Abstract: Where should we place sensors to quickly detect contaminations in drinking water distribution networks? Which blogs should we read to learn about the biggest stories on the web? These problems share a fundamental challenge: How can we obtain the most useful information about the state of the world, at minimum cost?  Such sensing, or active learning, problems are typically NP-hard, and were commonly addressed using heuristics without theoretical guarantees about the solution quality. In this talk, I will present algorithms which efficiently find provably near-optimal solutions to large, complex sensing problems. Our algorithms exploit submodularity, an intuitive notion of diminishing returns, common to many sensing problems; the more sensors we have already deployed, the less we learn by placing another sensor. To quantify the uncertainty in our predictions, we use probabilistic models, such as Gaussian Processes.  In addition to identifying the most informative sensing locations, our algorithms can handle more challenging settings, where sensors need to be able to reliably communicate over lossy links, where mobile robots are used for collecting data or where solutions need to be robust against adversaries and sensor failures.  I will also present results applying our algorithms to several real-world sensing tasks, including environmental monitoring using robotic sensors, activity recognition using a built sensing chair, deciding which blogs to read on the web, and a sensor placement competition.

• Bio: Andreas Krause is a Ph.D. Candidate at the Computer Science Department of Carnegie Mellon University. He is a recipient of a Microsoft Research Graduate Fellowship, and his research on sensor placement and information acquisition received awards at several conferences (KDD '07, IPSN '06, ICML '05 and UAI '05). He obtained his Diploma in Computer Science and Mathematics from the Technische Universitat Munchen, where his research received the NRW Undergraduate Science Award.

• Recorded Talk

• Name:  Jim Prager, UW
• Date: Thur, May 1, 2008
• Time: 10:00 - 11:30am
• Host: Josh Smith
• Title: Experimental Investigation of Plasma Downstream of a High Power Helicon Thruster

• Abstract: The High Power Helicon (HPH) is a compact, electrode-less plasma propulsion device based on a radio frequency helicon discharge. Designing and constructing the most efficient thruster requires that the physics of the helicon wave be well understood. Currently it is unclear how energy from the antenna is coupled to the plasma to produce directed ion flow. HPH operates in at a different power level, pressure, frequency and magnetic field geometry than other helicon experiments. I will present measurements that demonstrate ion acceleration downstream of the helicon, which is not observed at other helicon experiments. I will also present measurements that demonstrate the influence of the helicon wave far downstream of the antenna. These measurements provide an explanation of the physics that drives the ion acceleration.

• Bio: Jim Prager received his Bachelor of Science in physics from Lehigh University in Bethlehem, PA in January 2001. His senior research focused on methods of determining orbits of long-period binary star systems. In 2002 he moved to Seattle to begin graduate school in physics at the University of Washington. There he joined the Advanced Propulsion Laboratory to study radio frequency helicon waves in plasmas with applications to advanced space propulsion. He will receive his Ph.D. in June 2008.

• Recorded Talk

• Name:  Aseem Agarwala, Adobe Systems, Inc.
• Date: Wed, Apr 30 2008
• Time: 4:00 - 5:00pm
• Host: Jaeyeon Jung
• Title: Matching the Mind's Eye: Getting more from our Photos and Videos

• Abstract: Digital cameras are our primary tools for capturing the moments and memories of our lives. Our typical mental model is that photographs and videos are veridical records of what we saw with our own eyes. The reality, however, is that they are only interpretations of scenes, and they often fail to meet our expectations. In this talk I'll describe two very recent research projects that help us push our digital captures towards what we remember or hope to communicate. The first project looks at what large collections of photographs (e.g., Flickr) can tell us about the cameras that captured them. Specifically, we form novel statistical priors for large photo collections and use them to recover radiometric distortions of the appearance of a scene introduced by a specific camera model, such as a non-linear response curve, vignetting, and dead pixels on a camera sensor. These distortion parameters can then be used to undistort our photographs. In the second project, I describe a new way to perform local color and tonal adjustment within a single image or video. For example, a user may remember the scene as having a bluer sky, greener grass, and brighter people. The typical approach to making these adjustments within an image is to tediously mask out the separate regions. Instead, we allow the user to draw rough scribbles on different content and attach adjustments to them. Our algorithm then interpolates these adjustments to the rest of the image or video in a content-aware fashion. Specifically, we interpolate adjustments with an optimization that combines a boosting-based classifier on pixel appearance with an edge-weighted least-squares spatial regularization process

• Bio: Aseem Agarwala is a senior research scientist at Adobe Systems, Inc. and an affiliate assistant professor at the University of Washington. He completed his Ph.D. in 2006 at the University of Washington, and his B.S. and M.Eng. at MIT in 1999. His work experience includes two years as a research scientist at Starlab in Brussels, Belgium, and research internships at Mitsubishi Electric Research Laboratory (MERL) and Microsoft Research. His areas of research are computer graphics, computer vision, and computational imaging. He received the Honorable Mention (runner-up) for the 2006 ACM Doctoral Dissertation Award, and a 2004 Microsoft Research Fellowship. His work can be also found in several products, including Adobe Photoshop and Adobe Photoshop Elements.

• Recorded Talk

• Name:  Shwetak Patel, GaTech
• Date: Tue, Apr 29, 2008
• Time: 10:00 - 11:30am
• Host: Anthony LaMarca
• Title: Bringing Sensing to the Masses: An Exploration in Infrastructure Mediated Sensing

• Abstract: The use of sensing systems in the home has the potential to impact various research areas such as chronic care management, aging in place, and sustainability. A major challenge remains in identifying and developing truly ubiquitous sensing solutions that address deployment challenges of cost-effectiveness, installation, maintenance, and overall acceptability for a general audience. In the home, the goal of practical ubiquity had led me to develop a new sensing approach, which I call "Infrastructure Mediated Sensing," or IMS. Infrastructure mediation refers to the simple augmentation and probing of existing home infrastructure, such as the electrical power lines, plumbing, or HVAC systems, to sense human activity. I will present three different IMS systems I have built that leverage the electrical and HVAC systems in a home for the purposes of location tracking and activity detection. I will describe an in-depth study of home mobility patterns enabled by an IMS-based positioning system, as well as motivate a wide variety of other applications this sensing approach enables. I will also describe research opportunities in exploring IMS outside of the domestic space.

• Bio: Shwetak N. Patel is a Ph.D. candidate in Computer Science in the School of Interactive Computing at the Georgia Institute of Technology, where he is a member of the Ubiquitous Computing Research group, serves as the assistant director of the Aware Home Research Initiative, and is a National Science Foundation Graduate Research Fellow. His research is in the areas of Human-Computer Interaction and Ubiquitous Computing with a particular emphasis on developing and applying new low-cost, easy-to-use hardware and software solutions to enable novel application deployment and evaluation. Shwetak’s published work has received various best paper awards and nominations. His past work on camera detection and neutralization received the designation of a Top Technology Idea of the Year from New York Times Magazine in 2005. Shwetak’s research has also been the basis of various commercialization efforts.

• Recorded Talk

• Name:  Helen Wang of Microsoft Research
• Date: Wed, Apr 23, 2008
• Time: 2:00 - 3:00pm
• Host: Jaeyeon Jung
• Title: Protection and Communication Abstractions for Web Browsers in MashupOS

• Abstract: The advent of AJAX and client mashups has turned Web browsers into a multiprincipal operating environment. But browser support for Web programmers has lagged behind and remained in a single-principal world: The Same Origin Policy that dictates today's browser-security model offers either no trust through complete isolation between principals (sites) or full trust by incorporating third-party code as libraries. The consequences of such limited support include cross-site-scripting attacks that seriously plague today's Web and undesirable programming practices that make tradeoffs between security and functionality. In the MashupOS project, we address this deficiency. Our goal is to enable a browser to be a multiprincipal OS. Our initial focus is on protection and communication abstractions. Protection is to provide default isolation boundaries among principals (sites), while communication enables custom, fine-grained access control. We have designed our abstractions to be backward-compatible and easily adoptable. We have built a MashupOS prototype that we will demonstrate. Our experience and evaluation show that our abstractions make it easy to build more secure and robust client-side Web mashups and can be implemented easily in browsers with negligible performance overhead.

• Bio: Helen J. Wang is a senior researcher and leads a security research group at Microsoft Research, Redmond. Her research interests are in system/network security, mobile/wireless computing, and wide-area large scale distributed system design. She received her Ph.D. degree from the Computer Science department of U. C. Berkeley in December, 2001. She obtained her Bachelor of Science in Computer Science from U. T. Austin, and Master of Science in Computer Science from U. C. Berkeley, respectively.

• Recorded Talk

• Name:  Alexander Berg of Yahoo! Research
  Date: Tue, Apr 22, 2008
• Time: 10:00 - 11:30am
• Host: Ali Rahimi
• Title: Computational visual recognition

• Abstract: Computational visual recognition concerns identifying what is in an image, video, or other visual data, enabling applications such as measuring location, pose, size, activity, and identity as well as indexing for search by semantic content. Recent progress in making economical sensors and improvements in network, storage, and computational power make visual recognition practical and relevant in almost all experimental sciences and many commercial applications including image search. My work in visual recognition brings together machine learning, insights from psychology and physiology, computer graphics, algorithms, and a great deal of computation.
  I will present work on many aspects of attacking this challenge from low level image and video descriptors, to geometric models for deformable objects including humans, to techniques for parsing images of architectural scenes. This will include related work on modifying support vector machine approaches in order to increase recognition performance and speed on vision tasks. The applications in the presentation span object category recognition, image classification, action recognition, video search, biological monitoring, face recognition, and pedestrian detection.

• Bio: Alex Berg's research concerns computational visual recognition. He is currently a research scientist at Yahoo! Research and a visiting scholar at U.C. Berkeley. He has worked on general object recognition in images, action recognition in video, human pose identification in images, image parsing, face recognition, image search, and machine learning for computer vision. His PhD at U.C. Berkeley developed a novel approach to deformable template matching.  He earned a BA and MA in Mathematics from Johns Hopkins University and learned to race sailboats at SSA in Annapolis.

• Recorded Talk

• Name: Johnny Lee of CMU
• Date: Tue, Apr 15, 2008
• Time: 10:00 - 11:30 am
• Host: Josh Smith
• Tiitle: Enhancing the Practicality and Reachability of Interactive Technology

• Abstract: As researchers, one of our common goals is to expand our reach and our capabilities as human beings through the development of new technologies and new ideas. Often we use immense resources to explore this new territory. However, an unfortunate side effect of this essential activity is that the number of individuals that can participate in this search becomes smaller and smaller as the resources become greater and greater. My primary motivation in research is to develop and demonstrate new techniques that substantially increase the practicality and reachability of technology. My work solves real world problems of applying research concepts by simplifying implementation and reducing system cost. This does two things: first, it enables more researchers to explore the domain advancing the state of research; second, it results in a more practical commercialization increasing distribution, adoption, and overall impact. In this talk, I will describe how I have successfully applied this philosophy in my research projects ranging from projector calibration, augmented reality, multi-touch interaction, immersive displays, animation, biometric interaction, to filmmaking.

• Bio: Johnny Chung Lee is a PhD. Graduate student at Carnegie Mellon University in the Human-Computer Interaction Institute. His primary research interests are in developing technologies and techniques that increase the accessibility and practicality of technology. His previous work includes a diversity of topics ranging from projector calibration, augmented reality, brain-computer interfaces, haptic, animation, multi-channel audio, and filmmaking tools.

• Recorded Talk

• Name: Matt Welsh of Harvard,  EECS
• Date: Wed, Mar 26, 2008
• Time: 4:00-5:00pm
• Host: Jaeyeon Jung
• Title: Fiji: A Platform for Data-Intensive Sensor Network Applications

• Abstract: Sensor networks are becoming increasingly important for data-intensive applications that involve moderate to high data rates, fine-grained timestamping of recorded signals, and computationally-intensive processing within the network. Examples of this new class of applications include volcano monitoring, structural health monitoring, and biomedical data capture. In contrast to the first generation of sensor networks, which were focused on low-duty-cycle data collection and aggregation, these new applications demand much greater data fidelity and computational sophistication.  At the same time, wireless sensor platforms are inherently resource-constrained, leading to severe limitations of computational horsepower, memory capacity, and radio bandwidth. The stringent application demands and resource constraints conflate to make programming complex sensor applications a very difficult task, even for experts in embedded systems. As a result there is a vast gap between the needs of domain scientists wishing to develop and deploy a sensor network and the level of expertise required to realize a resource-efficient implementation.
  In this talk, I will present Fiji, a new programming platform intended to make it much easier for domain scientists to leverage wireless sensor networks. Fiji is based on the concept of macroprogramming, in which a program describing the global behavior of the network is compiled down to an efficient node-level binary. This is accomplished using a flexible dataflow-based intermediate form supported by multiple compilers for each target language. Fiji also provides a powerful node-level runtime and OS for resource-aware programming, allowing applications to naturally adapt to varying resource availability.

• Bio: Matt Welsh is an associate professor of Computer Science at Harvard University. His research interests span many aspects of complex systems, including Internet services, distributed systems, and sensor networks. His current projects include macroprogramming language, operating system, and resource management techniques for sensor networks. He is the co-founder of AID Networks, an early-stage company developing wireless sensor platforms for emergency medicine. He is also a long-time Linux hacker and is the author of "Running Linux", published by O'Reilly and Associates.

• Name:  Bhaskara Marthi of MIT
• Date: Tue, Mar 25
• Time: 10:00 - 11:30am
• Host: Matthai Philipose
• Title: State estimation and decision making in complex systems

• Abstract: I will describe an algorithm for probabilistic filtering, the problem of maintaining a probability distribution over the hidden state of a dynamical system given periodic noisy observations. This problem appears in various guises in practice, such as activity monitoring, state estimation, visual tracking, and fault diagnosis. Our algorithm, known as decayed MCMC, scales better than exact methods on many problems, and is less susceptible to losing track of the mode than the popular sequential Monte Carlo or particle filtering methods. Standard Markov chain Monte-Carlo mixing time analyses are insufficient to bound the complexity of our algorithm, and so we extend them to the setting of convergence of a marginal distribution. Time permitting, I will also briefly describe some other recent work on reinforcement learning with partial programs, and hierarchical planning for robotic manipulation.

• Bio: Dr. Bhaskara Marthi is currently a postdoctoral research associate at MIT, working with Leslie Kaelbling and Tomas Lozano Perez on hierarchical planning and robotic manipulation. He received his PhD in 2006 from the University of California, Berkeley, working with Stuart Russell on reinforcement learning with partial programs, and its application to AI design for large real-time strategy video games. His other interests include probabilistic reasoning, relational and first-order models, and Monte Carlo algorithms.

• Recorded Talk

• Name: Tawanna Dillahunt of CMU
• Date: Wed, Mar 12, 2008
• Time: 4:00-5:00pm
• Host: Beverly Harrison
• Title: Leveraging internet scale technologies to help individuals to reduce energy consumption

• Abstract: The average American consumes 12.5 times the energy of the average citizen of Africa or Asia. With approximately 300 million citizens, that adds up to 2 billion metric tons of CO2, or just over a 3rd of the total waste produced across all sectors of the U.S. economy. Of the other two thirds, much is produced as a by product of the process of meeting the needs of individuals. For example, the transportation of food, production of goods, and so on all generates waste. As a result personal choice can have a huge impact on energy consumption and waste production. The impact of individual choice can be seen in the increasing popularity of organic foods, hybrid cars, and other environmentally friendly consumption choices. What role can social technologies play in supporting large-scale group action and change?
  Tawanna will discuss Footprints, a project aimed at encouraging sustainable behaviors through the use of social technologies. She will discuss StepGreen, a website that allows individuals to report and track their environmental impact and displays the results on popular social networking sites like Facebook and Myspace. She will then discuss the results of a pilot study of the motivational value of emotional attachment to a virtual polar bear. Finally, Tawanna will talk about UbiGreen, a collaboration with Intel, the University of Washington, and Carnegie Mellon to explore how concepts like the polar bear can be used in a mobile setting to motivate change. UbiGreen is a mobile application designed which displays feedback about environmentally sustainable transportation choices using either a polar bear or a tree. Tawanna will discuss the field study of UbiGreen that we are currently planning, and seek feedback on our future directions.

• Bio: Tawanna is a first year Ph.D. student at Carnegie Mellon's Human Computer Interaction Institute and is advised by Jennifer Mankoff. Tawanna received her undergraduate degree from North Carolina State University in Computer Engineering. She completed her masters in Computer Science, with an an emphasis in Human Computer Interfaces from the Oregon Graduate Institute at the Oregon Health and Science University while working full-time as a Software Engineer at Intel. Tawanna worked at Intel for 7 years before starting at Carnegie Mellon. Her interests lie in using social computing to motivate and encourage positive behaviors and ubiquitous computing.

• Recorded Talk

• Name: Ara Knaian of MIT
• Date:  Tue, Mar 11, 2008
• Time: 10:00 - 11:30am
• Host: Josh Smith
• Title: Electromagnetics and Acoustics for Ubiquitous Computing

• Abstract:  will present several projects on the theme of using electromagnetics and acoustics for sensing, actuation, communications, and power delivery for ubiquitous computing and robotics.  I will describe my ongoing thesis work, on CMOS micro-robotics. We are constructing a millimeter-scale three-axis motion stage, with millimeter-scale travel, for applications in programmable matter and automation for biology and chemistry. The system uses custom-designed high-voltage CMOS IC's, which are designed to move when the dice are placed face-to-face. Each chip has a square array of micron-scale electrodes, which can be switched to +40V, grounded, or placed in a high-impedance input state. By driving and reading out the state from these electrodes, electrostatic actuation, communication, localization, and wireless energy transfer from IC to IC should be possible. E Ink Corporation developed and now manufactures electrophoretic displays for electronic books. Unlike liquid-crystal displays, electrophoretic displays are bistable and have a Lambertian reflectance characteristic, leading to low system power consumption, sunlight readability, wide viewing angle, and ink-on-paper aesthetic appearance.  Because electrophoretic displays are bistable, areas of the display with differing switching history require differing voltage or pulse width to be switched to the same reflectance. If waveforms that account for differences in switching history are not used, artifacts such as "ghosting" result. I will describe my work on drive waveforms and
  display controllers to account for switching history, and describe the algorithms and metrology equipment we developed to optimize these waveforms. 
  The MIT Autonomous Underwater Vehicle Team, Project ORCA, competes in an annual competition sponsored by the Office of Naval Research. As a founder and member of the team, I built a three-dimensional underwater acoustic direction finder, which enabled our vehicle to autonomously locate and center over a submerged acoustic beacon. The system used four hydrophones in a pyramidal array, coupled to a digital signal processor which performed pair-wise cross-correlation to recover time delays and geometric calculations to identify the direction of the incoming wave front.
  Finally, I will sketch some project ideas, including wireless power for mobile electronics and electromagnetic localization of home robots.

• Bio: Ara Knaian is a PhD candidate in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. His is interested in the application of electromagnetics to problems in robotics and human-computer interaction. He also has interests in distributed computing, machine design, and computational geometry. Before returning to graduate school, Ara Knaian worked for E Ink Corporation, where he developed the electrophoretic display drive waveforms used in the SONY Reader and Amazon Kindle.

• Recorded Talk

• Name: Miryung Kim of UW
• Date:  Wed, Mar 5, 2008
• Time: 4:00 - 5:00pm
• Host: Jaeyeon Jung
• Title: Analyzing and Inferring the Structure of Code Changes

• Abstract: There is a significant gap between how programmers think about code changes and how change is represented in most change-centric software engineering tools such as diff, CVS, and Unix patch. To bridge this gap, I developed a new program differencing approach that automatically extracts a high-level change description from two program versions. The core of this approach is a novel rule-based change representation that explicitly and concisely captures systematic changes to a program's structure and a rule learning algorithm that automatically infers such rules.
  In this talk, I will also present my empirical studies on duplicated code, which partially motivated my program differencing approach. It has been long believed that code clones---syntactically similar code fragments---indicate bad smells of poor software design and that refactoring code clones improves software quality. By analyzing how code clones actually change over time, I found that code clones are not inherently bad and that immediate and aggressive refactoring may not be the best solution for managing code clones.

• Bio: Miryung Kim is a Ph.D. candidate working with Dr. David Notkin at the University of Washington in Seattle. She earned her Bachelor's degree at the Korea Advanced Institute of Science Technology in 2001 and her Master's degree at the University of Washington in 2003. Her current research interests are software evolution, mining software repositories, and human aspects of software development.

• Recorded Talk

• Name: Yang Li of UW
• Date:  Wed, Feb 27, 2008
• Time: 4:00 - 5:00pm
• Host: Beverly Harrison
• Title: Rapid Prototyping of Ubiquitous Computing Applications: Tools & Frameworks

• Abstract: Pervasive or ubiquitous computing (ubicomp) applications can support people’s everyday activities in the physical world by leveraging advances in sensor technologies and computing infrastructures. Designing ubicomp applications is challenging because our everyday activities are more complex, dynamic and less structured than the tasks supported by traditional desktop computing. Ubicomp design is difficult, time-consuming, and requires a high level of technical expertise, especially with sensor technologies. To address this, I created a set of rapid prototyping tools and frameworks. My early work with Topiary introduces high-level abstractions, such as maps and scenarios, for designers to easily model location contexts and specify location-based behaviors. Topiary also allows a design to be tested in the field via a Wizard of Oz approach, without deploying a location sensor infrastructure. My recent work is focused on activity-based ubicomp prototyping, a process for enabling long-term activities (such as keeping fit)-a larger unit for design than the tasks that are the focus of traditional design. To support such a process, I created ActivityDesigner, a system that allows designers to create functional prototypes of ubicomp applications based on field observations, and easily deploy and test these prototypes in situ.

• Bio: Yang Li is a research associate in the Computer Science and Engineering Department at the University of Washington. He works in the areas of human-computer Interaction and ubiquitous computing, focusing on activity-based ubiquitous computing, rapid prototyping tools and pen-based interaction techniques. Previously, he was a postdoctoral researcher in EECS at the University of California at Berkeley. He received his PhD in computer science from the Chinese Academy of Sciences. http://www.cs.washington.edu/homes/yangli

• Recorded Talk

• Name: Richard Davis of University of California, Berkeley
• Date:  Wed, Feb 13, 2008
• Time: 4:00-5:00pm
• Host: David Wetherall
• Title: K-Sketch: A "Kinetic" Sketch Pad for Novice Animators

• Abstract: Because most animation tools are complex and time-consuming to learn and use, most animations today are created by experts. To help novices create a wide range of animations quickly, we have developed a general-purpose, informal, 2D animation sketching system called K-Sketch. Field studies investigating the needs of animators and would-be animators helped us collect a library of usage scenarios for our tool. A novel optimization technique enabled us to remove unnecessary complexity from the interface. The result is a pen-based system that relies on users' intuitive sense of space and time while still supporting a wide range of uses. In a laboratory experiment that compared K-Sketch to a more formal animation tool (PowerPoint), participants worked three times faster, needed half the learning time, and had significantly lower cognitive load with K-Sketch. Participants reported that they were no less comfortable showing their animations to others, and that they were more comfortable creating K-Sketch animations in front of others. 

• Bio: Richard Davis is a candidate for a Ph.D. in Computer Science from the University of California at Berkeley with a focus on Human-Computer Interaction. He specializes in systems that help everyday computer users express and manipulate rough ideas, including animations (K-Sketch) and notes taken in meetings (NotePals) or while listening to voice mail (Jotmail). His SketchWizard system helps designers simulate rough ideas for pen-based interfaces. In industry, he developed systems that helped people manipulate whiteboard notes (mimio), circuit signals (Simulink), microchip design information (Intel), and video productions (BorisFX). Richard earned bachelor's and Masters degrees in Electrical Engineering and Computer Science (with a minor in Theater Arts) from the Massachusetts Institute of Technology in 1995. He currently resides in Seattle and works with his research advisor James Landay at the University of Washington. More information on his current and past projects is available at
  http://www.eecs.berkeley.edu/~rcdavis.    

• Recorded Talk

• Name: Emily Cooper of Alium Labs
• Date:  Tue, Feb 5, 2008
• Time: 10:00-11:30am
• Host: Josh Smith
• Title:  Sensors, Miniaturization, and Sensor Miniaturization 

• Abstract:  Miniaturized sensing systems can enable novel detection methods to drive research science and new applications through reduced package size and greater integration.  However, shrinking feature sizes raises new challenges as devices become more sensitive to materials properties --- especially edge effects --- and geometric constraints imposed by fabrication methods.  This talk will present approaches to sensing and miniaturization challenges through case studies from biosensing and navigation, including:

  • fields and forces in biomolecular sensing: managing the charge microenvironment for improved potentiometric sensing

  • applying optical interferometry to accelerometry

  • a case against MEMS (MicroElectroMechanical Systems) implementation: miniaturizing a fluxgate magnetic field sensor

• Bio: Emily Cooper received her PhD in Electrical Engineering at the Massachusetts Institute of Technology, where her thesis work focused on the development of novel detection strategies for bioscience.  Working at the multi-disciplinary MIT Media Lab, she designed, fabricated, and applied MicroElectroMechanical (MEM) sensors, developed microfluidic systems for assay handling,  and applied scanning probe techniques to nanolithography and surface analysis.  After completing her graduate work, she joined TIAX, formerly the Technology and Innovation division of Arthur D. Little, where she developed applications in healthcare, portable power, data storage, environmental sensing, and navigation.  Dr. Cooper currently runs a small technical and strategic consultancy. 

• Name: Kevin Fu of UMASS Amherst
• Date: Thur, Jan 31, 2008
• Time: 1:30-2:00pm
• Host: Jaeyeon Jung
• Title: Maximalist cryptography and computation on the WISP UHF RFID tag.

• Abstract:  With continuous improvements in the efficiency of microelectronics, it is now possible to power a general-purpose microcontroller wirelessly at a reasonable range. Our implementation of RC5-32/12/16 on the WISP UHF RFID tag shows that conventional cryptography is no longer beyond the reach of a general-purpose UHF tag. In this paper, (1) we provide preliminary experimental data  on how much
  computation is available on a TI MSP430F1232 microcontroller-based RFID tag containing approximately 8~KBytes of flash and 256~bytes of
  RAM, and (2) we show that symmetric cryptography is feasible on an RF-powered, general-purpose RFID tag --- providing the first
  implementation of conventional cryptography on an RF-powered UHF RFID tag as far as we are aware.

• Bio:  Kevin Fu is an assistant professor in the Department of Computer Science at the University of Massachusetts Amherst, and is the principal investigator of the RFID Consortium on Security and Privacy (RFID CUSP).  Kevin investigates the security and privacy of pervasive and invasive computation --- including RFID, implantable medical devices, and file systems.  Kevin's contributions include key regression for efficient decentralized access control of storage; the SFS read-only file system for fast integrity-protected content distribution; proxy re-encryption file systems for managing distributed access control; and the security analysis of RFID-enabled credit cards, Web authentication, and software updates.  Kevin received his M.Eng. and Ph.D. in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology in 1999 and 2005 respectively, and his S.B. in Computer Science and Engineering from MIT in 1998.  He has served on numerous program committees of prestigious conferences in computer security and cryptography.  His research has appeared in The New York Times and The Wall Street Journal.  Kevin also holds a certificate of achievement in artisanal bread making from the French Culinary Institute.

• Recorded Talk

• Name: Oren Etzioni of UW, CSE
• Date: Wed, Jan 30, 2008
• Time: 4:00-5:00pm
• Host: Matthai Philipose
• Title: Everything I know I Learned from Google: Machine Reading of Web Text

• Abstract: Is it possible to capture a massive body of high-quality knowledge from the Web? my talk will describe our KnowItAll research project, which has been investigating this and related questions over the last five years. We have scaled and generalized information extraction methods to process arbitrary Web text, and to handle unanticipated concepts, but many challenges remain. One the most formidable challenges is moving from extracting isolated nuggets of information to capturing a coherent body of knowledge that can support automatic inference. My talk will highlight this and other exciting directions for future work.

• Bio: Oren Etzioni received his bachelor's degree in Computer Science from Harvard University in June 1986 where he was the first Harvard student to "major" in Computer Science.   Etzioni received his Ph.D. from Carnegie Mellon University in January 1991, and joined the University of Washington's faculty in February 1991, where he is now a Professor of Computer Science.    Etzioni received a National Young Investigator Award in 1993, and was selected as a AAAI Fellow a decade later.  In 2007, he received the Robert S. Engelmore Memorial Award.  He is the founder and director of the University of Washington's Turing Center.
  His current research interests include:  fundamental problems in the study of intelligence,  Web search, Machine Reading, and data mining.  Etzioni has been serving as a director of  the non-profit AI Access Foundation  since 1993. The foundation was created by Steve Minton to publish the Journal of AI Research --- one of the very first electronic journals distributed over the Web.  Etzioni is an Associate Editor of the ACM Transactions on the Web.

• Recorded Talk

• Name: Nati Srebro of Toyota Technological Institute
• Date: Wed, Dec 19, 2007
• Time: 4:00 - 5:00 pm
• Host: Tanzeem Choudhury
• Title: Does a large data-set mean more, or less, work?

• Abstract: In this talk we will consider how the computational cost of several machine learning tasks depends on the amount of available information (data set size). In devising methods for optimization problems associated with learning tasks, and in studying the runtime of these methods, we usually think of the runtime as increasing with the data set size. However, from a learning performance perspective, having more data available should not mean we need to spend more time optimizing. At the extreme, we can always ignore some of the data if it makes optimization difficult. But perhaps having more data available can actually allow us to spend less time optimizing?
  I will describe two types of behaviors:
  (1) a phase transition behavior, where a computationally intractable problems becomes tractable, at the cost of excess information. I will demonstrate this through a detailed study of informational and computational limits in clustering.
  (2) the scaling of the computational cost of training, e.g. support vector machines (SVMs). I will argue that the computational cost should scale down with data set size, and up with the "hardness" of the decision problem. In particular, I will describe a simple training procedure, achieving state-of-the-art performance on large data sets, whose runtime does not increase with data set size.
  Joint work with Sam Roweis (U Toronto/Google), Gregory Shakhnarovich (Brown), Shai Shalev-Schwartz (TTI) and Yoram Singer (Google).

• Bio: Nathan Srebro received his PhD from MIT in 2004. After visiting the University of Toronto and IBM Haifa Research Labs, he is now an assistant professor at the Toyota Technological Institute--Chicago (a philanthropically endowed academic computer science institute) and at the University of Chicago.

• Name: Daniel Gatica-Perez of IDIAP Research Institute
• Date: Tue, Dec 11, 2007
• Time: 10:30-11:30am
• Host: Tanzeem Choudhury
• Title: Modeling social interaction in small group meetings

• Abstract: In this talk, I will present ongoing work on automatic analysis of social interaction patterns in small group meetings from sensor data, in the context of a meeting room equipped with multiple cameras, microphones, and text capture devices.   I will discuss statistical models to recognize (1) visual attention and (2) perceived dominance of meeting participants, which integrate specific aspects of the multiparty, multimodal nature of group conversations. I will discuss our experience on what perceptual cues - some of which have been borrowed from social psychology - have worked well (or not) for our goals, and on issues related to performance evaluation of methods for social interaction recognition and discovery.

• Bio: Daniel Gatica Perez is a senior researcher at IDIAP Research Institute in Martigny, Switzerland, and a collaborator/lecturer at the Swiss Federal Institute of Technology in Lausanne (EPFL).  His research interests include multimedia signal processing and information retrieval, social computing, and machine learning applied to these domains. He has worked on automatic modeling of human activity in the context of Swiss, European, and US funded research projects since 2002. He got a PhD in Electrical Engineering from the University of Washington in 2001, and currently is an Associate Editor of the IEEE Transactions in Multimedia.

• Name: Dan Olsen of BYU
• Date: Thur, Nov 15, 2007
• Time: 3:00-4:00pm
• Host: Beverly Harrison
• Title: Cubic Inch Computing

• Abstract: Advances in digital electronics have made computing smaller and cheaper. If your personal computer is less than 1 cubic inch in volume, how will you interact with it? The problem is that personal computing is rapidly dropping below the physical limitations of human beings. This talk will discuss the challenges of highly nomadic personal computing and the UI architectures that can overcome those limitations. Example implementations of nomadic interactions where interactive resources such as displays and input devices are annexed rather than carried will be presented.

• Bio: Dan Olsen is a Professor and past Chair of Computer Science at Brigham Young University and currently directs the ICE (interactive computing everywhere) project there. He is a recognized expert in HCI, novel UI and interaction techniques, and applying machine learning for non-expert users. Dan founded and directed the HCI Institute at CMU, is an ACM Fellow, recipient of a CHI Lifetime Achievement award, Father of UIST award to name but a few. He is an active and visible member of most HCI conferences and committees, has published extensively, and was most recently invited to speak at the UW Distinguished Lecture series

• Recorded Talk

• Name: Maya Gupta of UW
• Date: Wed, Nov 14, 2007
• Time: 4:00-5:00pm
• Host: Ali Rahami
• Title: Recent Advances in Nearest Neighbor Learning: Weights, Neighbors, and Estimates

• Abstract: Recent advances in nearest-neighbor learning are shown for finding neighborhoods, neighborhood weighting, and estimating given nearest-neighbors. In particular, it is shown that weights that solve linear interpolation equations minimize the first-order learning error, and when coupled with the principle of maximum entropy this results in significantly improved nearest-neighbor classification performance. We show how these weights are related to weights formed by local linear regression. New approaches to adaptively determining neighborhoods are discussed. Standard weighted nearest-neighbor estimation maximizes likelihood, and it is shown that minimizing expected Bregman divergence instead leads to optimal solutions in terms of expected misclassification cost.

• Bio: Maya Gupta completed her Ph.D. in Electrical Engineering in 2003 at Stanford University as a National Science Foundation Graduate Fellow, after taking a BS in Electrical Engineering and a BA in Economics from Rice University in 1997. From 1999-2003 she worked for Ricoh's California Research Center as a color image processing research engineer. In the fall of 2003, she joined the EE faculty of the University of Washington as an Assistant Professor. She was awarded the 2007 Office of Naval Research Young Investigator Award, and the 2007 Univ. of Washington Outstanding Teaching Award.

• Recorded Talk

• Name: Meeyong Cha of KAIST
• Date:  Wed, Oct 17, 2007
• Time: 4:00 - 5:00pm
• Host: Jaeyeon Jung
• Title: I Tube, You Tube, Everybody Tubes: Analyzing the World's Largest User Generated Content Video System

• Abstract: User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. In this talk, I will present the intrinsic statistical properties of UGC video popularity based on real traces from YouTube, the world's largest UGC sharing web site. Understanding the popularity characteristics is important because it can bring forward the latent demand created by bottlenecks in the system ( e.g., poor search and recommendation engines, lack of metadata). I will also discuss the potential for more efficient UGC VoD systems (e.g., P2P distribution, caching).

• Bio: Meeyoung Cha is a PhD student in Computer Science at KAIST, Korea. Her advisor is Dr. Sue Moon. She is working on the network design and support for multimedia streaming services. Previously, she was an intern at AT&T Labs Research in NJ, where she participated in the cost comparison of IPTV backbone designs. Recently, she was an intern at Telefonica Research in Barcelona, Spain, and in University of Cambridge, UK, where she analyzed a nationwide IPTV system and the world's largest VoD for user-generated contents, YouTube. She also maintains interests in path diversity issues in intra- and inter-domain routing. She expects to graduate in Feb 2008.

• Name: Phil Levis of Stanford University
• Date: Wed, Sep 26, 2007
• Time: 4:00 - 5:00pm
• Host: Ben Greenstein
• Title: Visibility: A New Metric for Protocol Design

• Abstract: After nearly ten years of research, industrial development, and successful deployments, deploying wireless sensor networks remains difficult and labor-intensive. This encountered complexity is more than an artifact of dealing with a novel technology: energy constraints make it an essential consideration that will not go away.  In practice, distributed algorithms, limited state, energy, and low-power local communication make it difficult to observe or understand a network's internal operations and decisions. This challenge has led to a variety of management and debugging systems, such as SNMS, Sympathy, Marionette, and Clairvoyant, all of which seek to give an administrator the ability to peek into the state of the network. 
  In this talk, we propose a different approach. Instead of adding visibility layers on top of an inherently obfuscated system, we ask the question: "How can we design a network architecture to improve the visibility of its internal decisions?" We present the MNet architecture, a network architecture for wireless networks which has visibility as its major design principle. We define a quantitative measure for visibility. We describe the responsibilities of the MNet protocol stack, including the Fair Waiting Protocol (FWP), the architecture's narrow waist protocol that sits between multihop layers and a CSMA/CA link layer. We present the Pull Collection Protocol as an example of visibility-driven protocol design; to reduce failures, PCP shifts the communication burden from data sources to the data sink, which pulls packets in from the rest of the network. We conclude with comments on areas of current and future work in the MNet architecture.

• Bio: Philip Levis is an Assistant Professor in the Computer Science and Electrical Engineering Departments of Stanford University. He researches embedded wireless networks, including programming languages, operating systems, network protocols, algorithms and applications. His prior work includes TOSSIM, the TinyOS simulator, the Trickle algorithm for data dissemination in wireless networks, application-specific virtual machines, sensornet OS power management, wireless measurement, and wireless protocol design. He is the chair of the Core Working Group of the TinyOS Alliance.

• Name: Shaz Qadeer of Microsoft Research
• Date:  Wed, Aug 29, 2007
• Time: 4:00 - 5:00pm
• Host: Tanzeem Choudhury
• Title: Iterative context-bounding: a new approach for finding errors in large multithreaded programs

• Abstract: Multithreaded programs are difficult to get right. The interaction of concurrently executing threads leads to a huge number of program
  behaviors. Programmers, unable to account for all possible interactions among threads, often make errors which are difficult to find by traditional testing methods. In this lecture, I will present CHESS, a software model checker for systematically enumerating such behaviors.
  CHESS implements iterative context-bounding, a new approach for effectively searching the state space of a multithreaded program. In an execution of a multithreaded program, a context switch occurs when a thread temporarily stops execution and a different thread starts.  Iterative context-bounding gives priority to executions with fewer context switches, exploring all executions with no context switches followed by all executions with one context switch and so on.  For a fixed number of context switches, the total number of executions in a program is polynomial in the number of steps taken by each thread.  This theoretical upper bound makes it practically feasible to scale systematic exploration to large programs without sacrificing the ability to go deep in the state space. Our experience applying CHESS to large real-world programs shows that systematic search with a small number of context switches has the ability to expose nontrivial concurrency bugs.  CHESS has uncovered 9 previously unknown bugs in our benchmarks, each  exposed by an execution with at most 2 context switches.

• Bio: Shaz Qadeer is a researcher in the Software Reliability Research group at Microsoft Research. The goal of his research is to develop tools for
  improving the productivity of programmers. He has worked on many program verification tools, spanning the range from run-time verification to model checking to static analysis, with a special emphasis on tools for concurrent programs. Shaz received his Ph.D. at UC Berkeley and worked at Compaq Systems Research Center before joining Microsoft Research.

• Name: Ari Juels of RSA Laboratories
• Date:  Wed, Aug 22, 2007
• Time: 4:00 - 5:00pm
• Host: Tanzeem Choudhury
• Title: RFID Security: In the Shoulder and on the Loading Dock

• Abstract: RFID (Radio-Frequency IDentification) tags are microchips that communicate via radio. In common use today, they promise to become a ubiquitous tool for labeling objects and identifying people. RFID thus carries a strong imperative for protection against counterfeiting and privacy infringement.  In this talk, I'll give a brief introduction to RFID use today and describe some challenges and potential solutions in special operating environments. I'll discuss human-implantable RFID devices and the intricate privacy and security problems associated with these "prosthetic biometrics." I'll also talk about the problem of secure key distribution, a perennial challenge in computing systems that is particularly thorny in RFID-enhanced supply chains.

• Bio: Dr. Ari Juels is Chief Scientist and Director of RSA Laboratories, where he works to bring sparks of invention and insight from RSA's scientists and affiliates to the company as a whole. He joined RSA (now a division of EMC) in 1996 after receiving his Ph.D. in Computer Science from UC Berkeley.

• Name: Jesse Walker of Intel Corporation
• Date:  Wed, Jul 25, 2007
• Time: 4:00 - 5:00pm
• Host: Ben Greenstein
• Title: 802.16e security

• Abstract: This talk discusses WiMAX security as defined by 802.16e. It examines the 802.16e security architecture, the data protection mechanisms, key management, and authentication procedures...

• Bio: Dr. Jesse Walker is Intel’s Network Security Architect. He is responsible for developing and proliferating Intel’s guidelines to ensure secure networked communications with Intel-based devices. Dr. Walker is recognized as a security expert. He is the Technical Editor for 802.11 security enhancements, worked on the original 802.11 specification, and was the first person to publicly identify security vulnerabilities in the 802.11 WLAN protocol. Jesse has been with Intel for five years. Before joining Intel he worked at Shiva, Raptor Systems, Rockwell International, Datapoint Corporation, Iowa State University, and the University of Texas. Dr. Walker holds a Ph.D. in Mathematics from the University of Texas at Austin, and a B.A. in Liberal Arts (also from UT). Jesse has published extensively in academic and technical journals, including the May 2003 issue of Communications of the ACM. He has also performed a number of high-visibility speaking engagements.
  http://www.intel.com/technology/techresearch/people/bios/walker_j.htm

• Recorded Talk

• Name: Wanda Pratt of University of Washington
• Date:  Wed, Jul 18 , 2007
• Time: 4:00 - 5:00pm
• Host:  Sunny Consolvo

• Title: Managing Health Information in Your Life

• Abstract:  As clinicians are forced to decrease time spent with patients and as the specialization and fragmentation of care increases, patients are required to play an increasingly active role in their health care. Yet, few information tools exist to support patients in this active role. Patients often must coordinate their health care across multiple clinicians, learn new health terminology, make treatment choices, manage their home care, track insurance benefits, etc. These information rich tasks demand information management work of patients. The long-term objectives of this research are both to understand patients' information management work and to develop new technology that will support that work. Thus, we hope to help patients actively participate in their health care as they maintain the personal and professional aspects of their lives. In this talk, I will connect some of my older research on search interfaces to this emerging work on personal health information management.

• Bio:  Dr. Pratt is an Associate Professor in both the Information School and the Division of Biomedical & Health Informatics in the Medical School at the University of Washington. She is also the Director of the Graduate Program in Biomedical and Health Informatics. She received her Ph.D. in Medical Informatics from Stanford University, her M.S. in Computer Science from the University of Texas, and her B.S. in Electrical and Computer Engineering from the University of Kansas. Her published papers span a wide range of topics whose central theme is to understand the problem of information overload in a variety of health contexts and to develop new types technology to address those problems. She received an NSF CAREER Award for her work on literature-based discovery systems, is on the editorial board for the Journal of Biomedical Informatics, and serves on the standing NIH grant-review committee for the National Library of Medicine.

• Recorded Talk

• Name: Mitch Lum of University of Washington
• Date:  Wed, Jul 18 , 2007
• Time: 4:00 - 5:00pm
• Host:  Josh Smith

• Title: NASA NEEMO XII participation

• Abstract:  Telemedicine is already changing the means by which patients receive healthcare. Telesurgery will provide new opportunities for surgical intervention. Mobile Robotic Telesurgery (MRT) particularly in Extreme Environments has the potential to deliver emergency medical care to the critically injured; be it soldiers on a battlefield, civilians in a disaster zone or even astronauts in a deep space mission. The University of Washington, BioRobotics Lab has developed a new MRT platform, the RAVEN. In collaboration with the University of Cincinnati, the RAVEN was tested in the National Oceanic and Atmospheric Administrations (NOAA) Aquarius Undersea Habitat as part of the NASA Extreme Environments Mission Objective 12 (NEEMO 12). Surgeons located in Seattle, WA teleoperated the RAVEN, located at a depth of 60 feet inside the Aquarius Habitat, three and a half miles offshore from Key Largo, FL. This experiment tested both the RAVENs ability to operate in an extreme environment as well as the surgeons' skill in operating under variable time delay. Further this mission demonstrated the ability to use a single platform for multiple objectives, including educational outreach and geological sample handling and analysis.

• Bio: Mitchell Lum is a PhD candidate in the University of Washington, Dept. of Electrical Engineering, BioRobotics Lab. He joined the lab as a sophomore undergraduate in 1999. In 2002 he finished his BSEE and continued with the UW BioRobotics Lab for his graduate work, on a research grant from the US Army Medical Research and Materiel Command to create a new surgical robot system. As a research assistant on the RAVEN Surgical Robot he has been involved with its development from concept to its current state, having led the team on two successful mobile robotic telesurgery (MRT) missions.

• Recorded Talk  

• Name: Huong Q. Nguyen of University of Washington
• Date:  Wed, Jun 27, 2007
• Time: 4:00 - 5:00pm
• Host:  Sunny Consolvo

• Title: Utility of Technology-Enabled Interventions to Support Sustained Exercise

• Abstract:  Despite optimal medical therapy, patients with chronic obstructive pulmonary disease (COPD) continue to experience dyspnea (shortness of breath) with their activities of daily living. Exercise is one such evidence-based intervention that is effective in reducing dyspnea and improving functional capacity. However, exercise persistence for patients with COPD can be especially challenging given the chronic progressive nature of the illness. The thoughtful integration of information and communication technologies for tailored, real-time support may help patients persist with exercise over time. This presentation will cover the following areas: 1) development and current implementation of a PDA-based exercise intervention for patients with COPD; 2) lessons learned and opportunities for improvement and expansion to a broader older adult population and 3) potential collaborative research projects and funding mechanisms.

• Bio: Dr. Nguyen is currently an Assistant Professor in the Department of Biobehavioral Nursing and Health Systems at the University of Washington. Her research program has been focused on developing and testing technology-enabled interventions to support self-management in older patients with chronic illnesses. She is currently involved in two NIH funded projects that are evaluating interventions to support exercise persistence in patients with chronic lung disease. Dr. Nguyen is also receiving training as a K12 Multidisciplinary Clinical Research Scholar.

• Recorded Talk