Spring 2011

ABSTRACT: On Feb 14th, 15th & 16th, the Jeopardy! TV game show aired a unique exhibition match: a contest between the two most well-known Jeopardy! champions, Ken Jennings and Brad Rutter, and an IBM computer, nicknamed Watson. In this talk I will give an overview of the challenges facing an open-domain automatic question-answering system, specifically in the context of Jeopardy! I will describe the high-level architecture of Watson, how its performance has evolved over the last four years and why IBM was interested in this task. I will describe some of the approaches taken by Watson and look at some interesting questions – in particular, I will discuss “Toronto”. I will try to leave a lot of time for questions.

ABSTRACT: This talk will cover several research projects centered around the use of vision and motion capture for animation, recognition, and gaming. This includes human movements as diverse as subtle eye-blinks, lip-motions, spine-deformations, human walks and dances, politicians, base-ball pitchers, and the production of the largest motion capture game to date. The technical content of the talk focuses on the trade-off between data-driven models of human motion vs. analytically derived and perceptually driven models using dancers, animators, linguists, and other domain experts. This is demonstrated by sub-pixel tracking in Hollywood productions, reading the body-language of public figures, visualizing the pitches of NY Yankees Mariano Rivera, and the making of crowd mocap games in various cultures.

ABSTRACT: One of the core problems in geometry processing is the problem of comparing shapes and finding correspondences between different, but similar shapes. Maybe the most popular instance of this problem is matching and comparing surfaces (2-dimensional manifolds), a crucial component in a large number of applications ranging from matching of cortical surfaces, faces, bones or other biological surfaces, to more synthetic applications like shape morphing and attribute transfer. In this talk we will present a few applications of conformal geometry to the problems of surface matching and comparison. In particular, we will show how certain ideas originated in the theory of conformal geometry can be used to define novel metrics measuring dissimilarities and finding correspondences betweens pairs of surfaces automatically. The key idea is to utilize the prominent low-dimensionality of conformal mappings to construct metrics that are computationally efficient. I will report results on a few datasets of biological surfaces as well as other standard 3D surface datasets. I will end the talk with a broader picture of how ideas originated from differential geometry can be proven useful in describing and constructing algorithms for solving different geometric problems.

ABSTRACT: Software interfaces offer immense potential to support individual user needs through adaptation. Benefits of personalization include, for example, hiding unnecessarily complex options for only a basic task, or interpreting input specifically to accommodate a user with a severe motor impairment. However, effectively tapping into this potential is a major challenge; automatically adapting the user interface can improve performance and satisfaction, but, if not done well, it can also have the opposite effect. The overarching goal of my research is to accommodate diverse user needs through personalized adaptation, reducing information complexity, improving performance, and facilitating access for users with a range of motor and cognitive abilities. In this talk, I will first give an overview of my dissertation work on fundamental aspects of personalized interaction in the context of automatically adapting command structures (e.g., menus and toolbars) to reduce software application complexity. I will also discuss two ongoing projects where I am applying personalization to specific problem domains: (1) improving touch screen text input and (2) easing input for users with motor impairments.

ABSTRACT: In the past few years, we have seen a tremendous growth in public human communication and self-expression, through blogs, microblogs, and social networks. In addition, we are beginning to see the emergence of a social technology stack on the web, where profile and relationship information gathered by some applications can be used by other applications. This technology shift, and the cultural shift that has accompanied it, offers a great opportunity for computer scientists, artists, and sociologists to study (and organize) people at scale. In this talk I will discuss how the changing web suggests new paradigms for search and discovery. I will discuss some recent projects that use web search to study human nature, and use human nature to improve web search. I will describe the underlying principles behind these projects and suggest how they might inform future work in search, data mining, and social computing.

ABSTRACT: Advances in high-throughput technologies such as DNA sequencing are enabling the generation of massive amounts of biological data. This data is providing unprecedented opportunities to gain a systematic understanding of the genome of organisms and the regulation of genes encoded in them, but calls for new computational approaches for its analysis.

To address these challenges, I have developed computational methods for genome interpretation and for understanding gene regulation. (1) I developed a clustering method, STEM, for the analysis of short time series gene expression data, and initially applied it to data on immune response in human. STEM has since become a widely used method in many species and contexts. (2) I developed DREM, a method for integrating time series gene expression data with transcription factor-gene interactions, which reveals gene regulation temporal dynamics, which I applied originally in yeast and most recently in the context of the Drosophila modENCODE project. (3) I developed a method for predicting targets of transcription factors across the human genome by integrating sequence, annotation, and chromatin features, given the increasing availability of epigenetic information on chromatin modifications. (4) To exploit epigenomic information more systematically, I developed an algorithm for discovering and characterizing biologically-significant combinations of chromatin modifications across a genome, or ‘chromatin states’, based on their recurring patterns across the genome. (5) I used these chromatin states to study the dynamics of epigenetic changes across nine cell types in the context of the human ENCODE project, revealing a dynamic epigenomic landscape, that reveals causal regulators for cell type-specific enhancers, and provides new insights for interpreting disease-associated SNPs from genome-wide association studies (GWAS).

These methods provide a systematic way to discern regulatory information amidst the vast non-coding space of the human genome, towards a systematic understanding of gene regulation in the context of health and disease.

ABSTRACT: Emerging technologies, such as cloud and mobile computing, offer previously unimaginable global access to data; however, they also threaten our ability to control the use of our data, its lifetime, accessibility, privacy, management properties, etc. My research focuses on restoring to users control they’ve ceded to the cloud and mobile devices. In this talk I will describe two examples of this work. First, I’ll present Keypad, an auditing file system for theft- and loss-prone mobile devices that permits users to track and control accesses on their mobile data, even after a device has been stolen. Second, I’ll describe Vanish, a global-scale distributed-trust system that allows users to cause all copies of desired Web data objects, online or offline, to simultaneously self destruct at a specified time. A common thread of these efforts is the integration of systems and crypto techniques to solve new problems in data management brought on by technological change.

ABSTRACT: There is often a profound disconnect between our everyday behaviors and the effects those behaviors have on our health and the environment around us. My research focuses on the role of technology in bridging this disconnect—in particular, how technology can be used to effectively sense and visualize information about our own behaviors to promote awareness and enable positive behavior change. In this talk, I will provide an overview of my dissertation work on sensing and feedback systems for environmental behaviors, focusing on home resource consumption and personal transportation. These two domains account for a large percentage of an individual’s environmental footprint.

My work covers the entire spectrum of information flow: from sensing physical events, to intelligently interpreting and classifying this data, to building novel feedback interfaces that inform and motivate behavior. I will discuss the design and evaluation of UbiGreen, a mobile phone-based system that semi-automatically tracks personal transit behaviors such as bicycling or riding in a car, and feeds back this information continuously on the background of the mobile phone. I will also talk about HydroSense, which is the first water disaggregation system to automatically track water usage activities down to the fixture-level (e.g., upstairs shower vs. kitchen sink) from a single-point. Finally, I will discuss my current research on Reflect, a real-time ambient water usage feedback display for the home. Throughout the talk, I will interweave a design space of feedback technology that incorporates findings from behavioral and environmental psychology and human-computer interaction.