I had the pleasure of chairing the technical program for Pervasive. Here is a link to the proceedings:http://dl.acm.org/citation.cfm?id=1532200&picked=prox C.V.: CPR-1
Computer Science, as a single discipline, can no longer speak to the broad relevance of digital technologies in society. The Department of Informatics in the Donald Bren School of Information and Computer Sciences at the University of California, Irvine, serves as the institutional home for research on relationships between technological, organizational, and social aspects of…
We describe the design of the NomaticBubbles, a visualization that provides cues of communal whereabouts. Unlike most location displays showing whereabouts on a geographical map, the NomaticBubbles depicts historical and aggregate traces of participants’ whereabouts in an abstract and ambiguous manner. We describe the design of the NomaticBubbles, and discuss some early experiences and feedback…
I am honored to receive the UCI Donald Bren School for Information and Computer Science School’s Dean’s Award for Undergraduate Teaching. This award is for 2008 and is on behalf of the UCI ICS School which grants these honors annually to teachers who have demonstrated excellence in undergraduate education.
This $449,765 “HCC: Computing Place Context” grant was awarded by the Div. of Information and Intelligent Systems of the National Science Foundation. The official record of the award can be found here. A New Approach to Discovering Interruptibility This is a project to develop a new approach to interruptibility and related issues in instant messaging…
quub was a start-up that I worked on with several folks, including George Ruan and Nathan Esquenazi. quub was a commercialization of Nomatic*IM. Basically it was supposed to be automatic status updates that your computer would generate for you based on what it could detect about you from sensors. The ideal case would be to…
Intelligent assistants that support human communication need to respect the difficulty of understanding the context surrounding the interchange. Rather than attempting to directly communicate for a user, intelligent assistants should support decision making on the part of the involved parties so that complex social negotiations are preserved. We describe an intelligent assistant that does this…
In this article we discuss an assisted cognition information technology system that can learn personal maps customized for each user and infer his daily activities and movements from raw GPS data. The system uses discriminative and generative models for different parts of this task. A discriminative relational Markov network is used to extract significant places…
This paper introduces a hierarchical Markov model that can learn and infer a user’s daily movements through an urban community. The model uses multiple levels of abstraction in order to bridge the gap between raw GPS sensor measurements and high level information such as a user’s destination and mode of transportation. To achieve efficient inference,…
Henry Kautz, Dieter Fox, Lin Liao and I collaborated to write this chapter in Pervasive Computing in Healthcare by Alex Mihailidis, Jakob E. Bardram. It talks about how we used artificial intelligence to see when people made transportation errors associated with early-stage Alzheimer’s disease (local copy). C.V.: BCN-1
In this paper we present a social and technical architecture which will enable the study of localization from the perspective of crowds. Our research agenda is to leverage new computing opportunities that arise when many people are simultaneously localizing themselves. By aggregating this and other types of context information we intend to develop a statistically…
In this paper we present results related to achieving fine grained activity recognition for context-aware computing applications. We examine the advantages and challenges of reasoning with globally unique object instances detected by an RFID glove. We present a sequence of increasingly powerful probabilistic graphical models for activity recognition. We show the advantages of adding additional…
I am thrilled and honored to have been awarded the 2005 ISWC Best Paper award for our paper on “Fine-grained Activity Recognition by Aggregating Abstract Object Usage“. It was a collaborative effort amongst myself, Dieter Fox, Henry Kautz and Matthai Philipose. There are few research honors that are exhilarating as a best paper award.
We present an automated transportation routing system, called “Opportunity Knocks,” whose goal is to improve the efficiency, safety and independence of individuals with mild cognitive disabilities. Our system is implemented on a combination of a Bluetooth sensor beacon that broadcasts GPS data, a GPRS-enabled cell-phone, and remote activity inference software. The system uses a novel…
In this paper we discuss a system that can learn personal maps customized for each user and infer his daily activities and movements from raw GPS data. The system uses discriminative and generative models for different parts of this task. A discriminative relational Markov network is used to extract significant places and label them; a…
Assistant/Associate Professor in the Department of Informatics with a courtesy appointment in the Department of Computer Science at the University of California, Irvine.
From 1999 to 2005 I was a graduate student in the Department of Computer Science at the University of Washington in Seattle. For the first couple of years I worked in Sieg Hall and then moved into Allen Hall once it was complete. My advisors were Henry Kautz and Dieter Fox. I also owe a debt…
This is my thesis, the focus of which was on “Assisted Cognition”. It was the result of close work with my advisors Henry Kautz and Dieter Fox at the University of Washington Computer Science and Engineering Department (now a school). I am also very grateful to support from Gaetano Borriello and Ed Lazowska in getting me…
Many recent studies have underscored the applicability to healthcare of a system able to observe and understand day-to-day human activities. The Guide project is aimed at building just such a system. The project combines novel sensing technology, expressive but scalable learners and unsupervised mining of activity models from the web to address the problem. An…
One the best qualitative and quantitative tools that elder–care specialists have to monitor the health of elderly individuals is Activity of Daily Living (ADL) tracking [1,2]. By watching the frequency and competency with which an individual can cook, clean the house, engage in socializing, etc, short– and long– term changes in health can be identified.…
Elevated serum phosphate levels have been linked with vascular calcification and mortality among dialysis patients. The relationship between phosphate and mortality has not been explored among patients with chronic kidney disease (CKD). A retrospective cohort study was conducted from eight Veterans Affairs’ Medical Centers located in the Pacific Northwest. CKD was defined by two continuously…
Recognizing and recording activities of daily living is a significant problem in elder care. A new paradigm for ADL inferencing leverages radio-frequency-identification technology, data mining, and a probabilistic inference engine to recognize ADLs, based on the objects people use. ( local copy ) Published in IEEE Pervasive Computing C.V.: JR-01
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A system that can do this requires models of the activities of interest, but model construction does not scale well: humans must specify low-level details, such…
The modern knowledge worker has become very adept at working with desktop computers through familiar user interface devices such as keyboards, mice and screens. This interaction has relied on human adaptation for people to enter into the digital world by learning to type, double-click, etc. This paradigm has been sufficient to assist people in an…
We present a method of learning a Bayesian model of a traveler moving through an urban environment. This technique is novel in that it simultaneously learns a unified model of the traveler’s current mode of transportation as well as his most likely route, in an unsupervised manner. The model is implemented using particle filters and…
This paper presents an overview of the research on learning statistical models from relational data being carried out at the University of Washington. Our work falls into five main directions: learning models of social networks; learning models of sequential relational processes; scaling up statistical relational learning to massive data sources; learning for knowledge integration;…
I did two summer internships at Intel Research Seattle while in graduate school at UW. That organization ceased to exist around 2012-2013, but it was a moment in time that was very cool. The dawn of ubiquitous computing and lots of great researchers working on it. I designed and implemented a modeling language and statistical…
I am honored to be part of a lineage of grad students who have been awarded the University of Washington Computer Science and Engineering Educator’s Endowed Fellowship. It is a validation of the effort that I put into teaching and an honor to know that my colleagues notice and care about it.
Assisted Cognition systems provide active cognitive aids for people with reduced memory and problem-solving abilities due to Alzheimer’s Disease or other disorders. Two concrete examples of the Assisted Cognition systems we are developing are an ACTIVITY COMPASS that helps reduce spatial disorientation both inside and outside the home, and an ADL PROMPTER that helps patients…
In this paper, we introduce the Activity Compass, a cognitive aid for early-stage Alzheimer’s patients. This device has a simple user interface based on the metaphor of a traditional navigation compass. By following an arrow and an icon, users who are disoriented or forgetful are assisted in reaching their destination. A server-based AI engine learns…
While I was in graduate school I did some work with the Seattle Institute for Biomedical and Clinical Research. I did data modeling with the researchers there using the VA’s electronic medical record system, CHIPS. We published an influential paper on kidney disease that is one of my highest cited papers.
Accurate splice site prediction is a critical component of any computational approach to gene prediction in higher organisms. Existing approaches generally use sequence-based models that capture local dependencies among nucleotides in a small window around the splice site. We present evidence that computationally predicted secondary structure of moderate length pre-mRNA subsequences contains information that can…
University of Washington, Seattle, Washington Master’s of Science in Computer Science 2001
Stochastic search algorithms have proven to be very fast at solving many satisfiability problems [2,3,8]. The nature of their search requires careful parameter tuning to maximize performance, but depending on the problem and the details of the stochastic algorithm, the correct tuning may be difficult to ascertain [9]. In this paper we introduce Auto-Walksat, a…
I am honored to be part of a lineage of undergraduate and graduate students who have been awarded the University of Washington Computer Science and Engineering Bob Bandes Award. It is an award that honors the memory of a great grad TA by encouraging new generations of teachers.
I am honored to have been awarded a National Defense Science and Engineering Graduate (NDSEG) Fellowship. This generous competitive award funds doctoral students in disciplines that are deemed to be supportive of the U.S. National Defense for 3 years. It does not require military service. In is comparable to the NSF Graduate Fellowship.
I was the Navigator and Operations Officer on the USS SIMON LAKE (AS-33) from 1997-1999. I was originally stationed in Sardinia Italy, deployed to the Persian Gulf, then decommissioned the ship in Norfolk, VA.
I was the Gunnery Officer and Strike Officer on the USS CURTIS WILBUR (DDG-54) from 1995-1997. I was originally stationed in San Diego, deployed to the Persian Gulf, then homeport shifted to Yokosuka, Japan where I lived for a year.
During 1994 and 1995 I earned a Masters of Engineering at Cornell University in the Department of Electrical and Computer Engineering. I worked with Jon Belina on ambulatory ECG monitors implemented on digital signal processors.
I am honored to have been awarded a Association of Naval Engineering Scholarship. This competitive award provides stipends to graduate and undergraduate students in disciplines that support Naval Engineering.
From 1990 – 1994 I earned a Bachelor of Science degree in Computer Science (with Distinction) at Cornell University, Ithaca, New York.
I am honored to have been awarded a Naval Reserve Officer Training Corps (NROTC) Scholarship. This generous competitive award provides tuition and stipends to undergraduate students who intend to pursue a career in the Navy
I graduated from the Thomas Jefferson High School for Science and Technology with a High School Diploma in 1990.
I am an Eagle Scout. I earned my award in 1989 with an Eagle Scout project that entailed using a very early database system to catalog tombstones in the Fairfax County area. Most of the tombstones were under threat from development and contained genealogy information that is otherwise unavailable.