Tag Archive: Research Highlight

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CRA Board Member Highlight: Rachel Pottinger


Increasingly, jobs rely on the ability to use computers to interpret, understand, and trust data. For example, my students and I have worked with ornithologists who cannot understand the representations of their bird sightings, civil engineers who cannot easily use their own building data, finance experts who cannot trace money between companies and their subsidiaries, and an XML document company whose clients cannot understand data that appears outside of their reports. In each case, the data users have been hampered because their data is exceedingly difficult to understand and trust, even though the users are experts in their fields. One reason for this difficulty is that the organization of the data is often designed for computers, not for people (i.e., for storage, not accessibility). Another reason is that data often come from different sources, leaving users with the challenge of integrating data that they neither understand nor trust.

RyderRyder

CRA Board Member Highlight: Barbara G. Ryder


My computer science research career started during my college internship at Bell Laboratories in Murray Hill, New Jersey, during the early 1970s in the center that later produced UNIX and the portable C compiler. This experience taught me that computing was broader than the introduction to scientific programming in my undergraduate studies in applied math. (There was no computer science undergraduate major at the time.) For most of my career, I was interested in deriving descriptions of program execution behaviors from code in order, for example, to optimize program time and/or memory performance, to validate desirable properties such as correctness or data security, or to refactor code for ease of maintenance.

Increasing diversity in computing has been my passion throughout my career, mostly through my informal mentoring of female CS students at Rutgers and Virginia Tech, participating in CRA-W mentoring workshops, and leading efforts in CS at Virginia Tech College of Engineering to join with NCWIT to increase the gender diversity of our CS students.

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.