Tag Archive: Research Highlight

TeevanTeevan

CRA Board Member Highlight: Jaime Teevan


Research shows that it takes 25 minutes to reach full productivity after an interruption, yet we are interrupted every 3 minutes. And even without external interruptions, our focus is fragmented. We look at any given desktop window for an average of only 40 seconds, constantly self-interrupting to check email or Facebook. We also try to complete multiple tasks at once, even though we all know that multitasking typically fails. Our tendency to be easily distracted kept our hunter-and-gatherer ancestors alive when they needed to attend to potential predators, but now, in the safety of our offices, it is amazing we manage to get anything done. Chances are you won’t even read this entire article in one go.

Vivek SarkarVivek Sarkar

My Parallel Careers in Industry and Academia


As a researcher, I am fascinated by the challenge of advancing the high-level foundations of computer software (programming models, compilers, and runtimes) to productively exploit the latest advances in computing systems. While there has been a long tradition of research in this area since the dawn of computing, the rapid evolution of hardware has continuously fueled a need for new software technologies as old approaches quickly become obsolete. Current explorations of new hardware directions that go beyond Moore’s law have further amplified the motivation for this research direction.

Carla BrodleyCarla Brodley

CRA Board Member Highlight: Carla Brodley


For the past 30 years I have had two passions – machine learning (ML) that makes a difference in the real world and increasing diversity in computer science (CS).  For the first 26 years, I focused on my first passion and developed new approaches to ML though applications to remote sensing, neuroscience, digital libraries, astrophysics, content-based image retrieval of medical images, computational biology, chemistry, evidence-based medicine, detecting lesions in the MRIs of epilepsy patients, and predicting disease progression for MS patients. For the last four years, my focus has been on my second passion: increasing diversity in CS.

Julia-HirschbergJulia-Hirschberg

Research Highlight: CRA Board Member Julia Hirschberg


My research sits at the intersection of Natural Language Processing (NLP) and speech processing.  I have focused on identifying the role of prosodic information in speech and using this knowledge to produce more realistic Text-to-Speech Synthesis (TTS) systems; to detect many types of speaker state, including the classic emotions, such as anger, disgust, fear, happiness, sadness, and surprise; and derived emotions, such as confidence and uncertainty, deception, trust, and charisma. I’ve also studied human-machine and human-human behavior in Spoken Dialogue Systems (SDS) and Human-Computer Interaction (HCI).

Research Highlight: CRA Board Member Josep Torrellas


As Stanford professor John Hennessy once said, “[P]arallelism and ease of use of truly parallel computers … [is] a problem that’s as hard as any that computer science has faced.” As my Ph.D. advisor, Hennessy instilled in me a desire to conquer this problem, and I have been working at it for the last 30 years. Specifically, my research focuses on parallel computer architecture, with an emphasis on shared-memory organizations and their software layers.

Andrew-SearsAndrew-Sears

Meeting the Needs of Individuals with Disabilities- Accessible Computing


My research focuses on empowering individuals through computing technologies that more effectively match their knowledge, experience, abilities, and goals. The majority of my recent research has focused on accessibility-related issues. Working with my students, our research employs a broad definition of accessibility, seeking to empower individuals with disabilities as well as individuals who may experience challenges due to the environment in which they are using computing technologies.

Mary_HallMary_Hall

New Approaches to Producing High-Performance Code, Thanks to Compiler Technology


What does it take to produce application code that performs as close as possible to a parallel architecture’s compute or memory peak performance? This question is one that programmers of high-performance architectures contemplate regularly since using such systems efficiently can solve problems faster, or solve larger or more complex problems. 

This question fundamentally changes the approach to programming. 

Programming is no longer simply about the correct specification of an algorithm, but expands to understanding and exploiting features of the target architecture in all aspects of an application: algorithm choice, data structures and data layout, where to exploit parallelism, how to make the best use of the memory hierarchy, and how to avoid costly communication and synchronization between cooperating computations. Building applications while addressing performance and scalability concerns is difficult and frequently leads to low-level software that exposes architectural details.

Photo of Susan DavidsonPhoto of Susan Davidson

CRA Board Member Highlight: IEEE Honors Susan Davidson With TCDE Impact Award


This year, CRA Board Chair Susan Davidson received the IEEE TCDE Impact Award for “expanding the reach of data engineering within scientific disciplines.” In this interview, Davidson reveals how her interest in bioinformatics came about and how her career led to this award. Two of her favorite problems have been data integration and data provenance.

H.V. JagadishH.V. Jagadish

CRA Board Member Highlight: H. V. Jagadish


I study how data and people interact. For more than a decade, I have been studying how to help humans access and manage information. While there is a lot of good work on human-computer interaction and on data visualization, much less work exists on “human-data interaction.” Why can anyone use Google to get information of interest while it is so difficult to get useful information from a structured database? The difference lies in the specificity of the request. A web search engine receives your request and tries to guess your intention. You know that it has a limited understanding of your need, and are happy to have it get you into “the zone,” from where you can explore for yourself. On the other hand, a traditional database query engine can give you complete answers to complex questions but requires that you precisely specify your query. If you make a small mistake, you are out of luck. Wouldn’t it be helpful to devise database query mechanisms that you can actually use and get reasonable results from even if you don’t ask it totally correctly? Complementarily, can the system help you ask a better question in the first place? Similar concerns also apply to the creation of a database, and helping users manage their data.

Research Highlight: CRA Board Member Margaret Martonosi


What do multiprocessors, zebras, and qubits have in common? The field of computer architecture sits at the hardware-software interface, and computer architects play the role of mediating between technology trends emanating “from below” and application trends influencing the field “from above.” Over the 30 years since I began graduate school, my computer architecture research has explored many topics, but the ongoing theme has been attention to how technology and application trends and constraints influence hardware and system design, particularly at the hardware-software interface.