The Grace Hopper Celebration of Women in Computing (GHC) is the world’s largest gathering of women in computing. The 2012 Grace Hopper Celebration will take place 3-6 October 2012 at the Baltimore Convention Center. This year’s theme “Are We There Yet?” recognizes that technology and the culture of technology are continuously evolving but there are also concrete goals we are striving to achieve. Since UMBC is a Gold Academic Sponsor, UMBC students will receive a 20% registration discount.

At the conference, leading researchers will present their current work, while special sessions focus on the role of women in today’s technology fields, including computer science, information technology, research and engineering. The technical conference features well known keynote speakers and invited technical speakers, panels, workshops, new investigator technical papers, PhD forums, technical posters, birds of a feather sessions, the ACM Student Research Competition and an Awards Celebration.

If you would like to submit a paper or poster abstract on your work, the deadline is this coming Friday, March 16th. See the 2012 GHC call for participation for details.

Dr. Marie desJardins had the opportunity to attend two invitation-only professional development events in November 2011.

The Senior Women's Summit at the Grace Hopper Celebration of Women in Computing in Portland, Oregon, brought together senior women who are leaders in their fields in academia, industry, and research labs. The event featured a panel on career advancement, working sessions on leadership and developing a "brand" as a senior scientist, and networking opportunities for the women to share their experiences and advice with each other. Dr. desJardins reports, "I was inspired by the amazing senior women at this event, and by their accomplishments in the field. It was particularly interesting to realize that some of the women who are more senior than I am—department chairs, deans, vice presidents—were wrestling with many of the same questions I've been asking myself, about what career choices and leadership opportunities would be most satisfying to pursue, as I enter the second half of my professional career."

The Frontiers of Engineering Education (FOEE) Symposium, organized and sponsored by the National Academy of Engineering, provided an opportunity for early- and mid-career faculty to share their experiences and ideas about innovative strategies for improving engineering education. In the symposium's poster session, Dr. desJardins gave a presentation on the honors seminar that she teaches at UMBC, called "Computation, Complexity, and Emergence." The course brings together students from a wide range of backgrounds to explore complex systems and understand the importance of complexity in understanding processes and behaviors in many different application fields. Dr. desJardins's presentation emphasized the importance of teaching non-engineers about engineering and computational topics, the value of interdisciplinary learning environments, and the importance of emphasizing student-centered learning methods. The FOEE Symposium also included panels and presentations on project-based learning, assessment of learning outcomes, active learning, and design-based learning. Meeting other faculty from across the country who are teaching and innovating at a wide range of academic institutions, was also the source of new friendships as well as exciting new ideas for engaging students and increasing the depth of their learning experiences inside and outside of the classroom.

One of the most valuable parts of the FOEE symposium, according to Dr. desJardins, was the small-group mentoring sessions with senior leaders from industry and academia. She had the opportunity to have breakfast with Larry Shuman (Senior Associate Dean for Academic Affairs at the University of Pittsburgh) and lunch with Stephen Director (Provost and Senior Vice President for Academic Affairs at Northeastern University), and was inspired and fascinated by their stories of implementing major curricular changes at their respective universities.

Photo Courtesy www.gracehopper.org

EE Graduate Seminar

Energy Efficient and High Performance Architectures
for DSP and Communication Applications

Tinoosh Mohsenin, PhD
Assistant Professor of Computer Engineering
CSEE Dept/UMBC

11:30am-12:45pm, 9 March 2012, ITE 231

Many emerging and future communication applications require a significant amount of high throughput data processing and operate with decreasing power budgets. This need for greater energy efficiency and improved performance of electronic devices demands co-optimization of algorithms, architectures, and implementations. This talk presents several design projects that illustrate the cross-domain optimization.

The design of System-on-Chip (SoC) blocks becomes increasingly sophisticated with emergent communication standards that have large real-time computational requirements. Two such algorithms, Low Density Parity Check (LDPC) decoding and Compressive Sensing (CS), have received significant attention. LDPC decoding is an error correction technique which has shown superior error correction performance and has been adopted by several recent communication standards. Compressive sensing is a revolutionary technique which reduces the amount of data collected during acquisition and allows sparse signals and images to be recovered from very few samples compared to the traditional Nyquist sampling. While both LDPC decoding and compressive sampling have several advantages, they require high computational intensive algorithms which typically suffer from high power consumption and low clock rates. This talk presents novel algorithms and architectures to address these challenges.

As future communication systems demand increasing flexibility and performance within a limited power budget, multi-core and many-core chip architectures have become a promising solution. The design and implementation of a many-core platform capable of performing DSP applications is presented. The low power and low area core processors are connected through a hierarchical network structure. The network protocol includes contention resolution for high data traffic between cores. The result is a platform with higher performance and lower power consumption than a traditional DSP with the ease of programmability lacking in an ASIC. Early post place and route results from a standard-cell design gives processor areas of 0.078 mm2 each using TSMCs 65 nm.

Dr. Mohsenin received the B.S. degree in electrical engineering from the Sharif University of Technology, Iran and the M.S. and PhD degrees in electrical and computer engineering from Rice University and University of California Davis in 2004 and 2010, respectively. In 2011, she joined the Department of Computer Science and Electrical Engineering at the University of Maryland Baltimore County where she is currently an Assistant Professor. Dr. Mohsenin's research interests lie in the areas of high performance and energy-efficiency in programmable and special purpose processors. She is the director of the Energy Efficient High Performance Computing (EEPC) Lab, where she leads projects in architecture, hardware, software tools, and applications for VLSI computation with an emphasis on DSP workloads. Dr. Mohsenin has been consultant to early stage technology companies and currently serves as a member of the Technical Program Committees of the IEEE Biomedical Circuits & Systems Conference (BioCAS), the Life Science Systems and Applications Workshop (LiSSA), and IEEE Women in Circuits and Systems (WiCAS).

Host: Prof. Joel M. Morris

A Sophomore Computer Science major, Dan Maselko has been a tutor in the Computer Science Help Center since last fall.

Dan Maselko got hooked on computer science in high school. “When I took my first computer programming course in tenth grade,” he says, “I realized how easy and fun it was for me to get computers to solve problems.” Since then, Dan, a Sophomore, has been working towards his Computer Science degree while helping those who struggle with the subject.

Last Fall, Dan applied to be a tutor in the Computer Science Help Center. “The best thing about tutoring is getting the chance to help other students learn,” he says. “Every time someone walks out of the door of the Help Center with a better understanding of the material they had questions about, I just feel good knowing I could help them learn something.” Though Dan mainly helps students in CMSC 104, 201, and 202, the center provides help for students in most lower-level Computer Science courses including CMSC 100, 203, 313, 331, and 341, he explains.

The Computer Science Help Center—located in ITE 201-E—offers tutoring on a walk in basis. “Anyone enrolled in a Computer Science course at UMBC can be tutored by the Help Center,” says Dan, “and it’s completely free.” Dan compares the challenges of tutoring to those faced by computer scientists.

“The good challenge is trying to figure out how to make the computer science topics make sense to different people with different ways of thinking,” explains Dan. “Trying to understand so many diverse strategies is a lot like solving a problem in computer science.”

Dan has plans to continue tutoring until he pursues a Master’s degree in Computer Science. Once in graduate school, his teaching aspirations will not cease: “I do hope to eventually become a TA.” Though Dan enjoys helping others, he’s not set on a career in teaching, though he’s still considering it. “I…want to work at a job that’s exciting and requires collaboration,” he says. “Right now the thing that excites me most is cyber security.”

Ph.D. Dissertation Defense

Mining Commonsense Knowledge from the Web:
Towards Inducing Script-like Structures From Large-scale Text Sources

Niels Kasch

10:00am Friday, March 9th, 2012, ITE 325B

Knowing the sequences of events in situations such as eating at a restaurant is an example of commonsense knowledge needed for a broad range of cognitive tasks (e.g., language understanding). This thesis outlines an approach to mine information about sequential, every day situations in a topic-driven fashion to produce declarative, script-like representations (c.f., Schank's scripts). Given a topic such as eating at a restaurant, we produce graphs of temporally ordered events involved with the activity referenced by the topic. Our work utilizes large-scale data sources (e.g., the Web) to avoid data sparseness issues of narrow corpora.

We describe steps that address the scale and noisiness of the Web to make it accessible for script extraction. Boilerplate elements (e.g., navigation bars and advertising) on web pages skew distributional statistics of words and obstruct information retrieval tasks. To make the web usable as a corpus, we introduce a machine learning technique to separate boilerplate elements from content in arbitrary web pages.

A key element for commonsense knowledge extraction is the generation of a topic-specific corpus that facilitates script extraction in a topic-driven manner. We introduce Concept Modeling for Scripts as an efficient method to induce concepts containing script elements (e.g., events, people, and objects) from topic-specific corpora. Our experiments and user studies conducted on the 2011 ICWSM Spinn3r dataset show that our method outperforms state of the art topic-modeling approaches such as Latent Dirichlet Allocation (LDA) on this task when applied to unbalanced (topic-specific) corpora.

Concept Modeling serves as a starting point for automated methods to discover events relevant to a script. We demonstrate event detection methods in topic-specific corpora based on (1) learned dependency paths indicative of individual event structures, (2) semantic cohesiveness of event pairs, and (3) surface structures indicative of golden sentences containing sequential information. Events extracted for a given topic can be arranged in a graph. The detection methods exploit graph analysis methods to identify strongly connected components to prune the event set such that related and central events are predominant in the structure. User studies demonstrate that (1) the Web is suitable for mining script-like knowledge and (2) the resulting graph structures portray events strongly related to a given topic.

Script-like structures, by definition, impose temporal ordering on the events contained within the structure. This work also presents a novel method to induce ordering information from topic-specific corpora based on a counting framework to judge the presence and strength of a temporal happens-before relation. The framework is extensible to several counting methods, where a counting method provides co-occurrence and ordering statistics. We present, among others, a novel naive counting methods that uses a simple sentence position assumption for temporal order. Comparisons to existing temporal resources show that our naive method, in conjunction with connected components analysis, induces temporal relationship with similar accuracy than more sophisticated methods, yet with a smaller computational footprint.

Committee

• Dr. Tim Oates (chair)
• Dr. Ronnie W. Smith
• Dr. Matt Schmill
• Dr. Tim Finin
• Dr. Charles Nicholas

This semester, the students in Susan Mitchell’s Software Design and Development course were hand-picked. After applying and being interviewed, ten students were chosen based on their “go-getter” attitude.

Why the selectivity? Susan ’s CMSC 345 course this semester is a trial course that’s being taught in collaboration with Next Century Corporation, a Maryland-based technology company. Though Mitchell has been teaching CMSC 345 for ten years, this is a first.

Designed around the completion of one software-design project, the course provides students with a “customer” (normally a faculty member) who gives them specific guidelines for the “product” they need to complete. In years prior, students were given the task of developing a program that plans a student’s UMBC course career. Mitchell explains that the product for this semester will be especially real-world focused.

In fact, essentially everything about the course is meant to simulate working in the software industry. A writing intensive course, students are asked to write formal documents, and at the end of the semester, they must give a formal presentation.
Mitchell explains that the course isn’t so much about coding as it is about understanding the “software development lifecycle.” It’s the process that’s important, she explains, from conception to carry through. Understanding what the customer wants and then turning out a product that fits those guidelines is the goal.

Chris Stepnitz, a software engineer at Next Century, is the “customer” of this semester’s pilot course. Stepnitz, who graduated from UMBC in 2006 with a degree in Computer Science, took the very same course with Mitchell years ago. “We wrote an accounting system,” remembers Stepnitz, who admits she was considering changing majors before taking the course. She credits it with opening her eyes to the reality of a career in software development and the rewarding experience of programming with a team.

So, when Stepnitz heard that Next Century, who has been reaching out to the community through local colleges, was about to reach out to her alma matter, she jumped at the chance to participate. “I’m very excited,” says Stepnitz. “For the students, I really want to make sure that they both enjoy [the class] and get the taste of what it’s like to really be in the development world.”

The arrangement is meant to be mutually beneficial. Students in the course learn how to succeed in an industry setting, while Next Century builds bonds with universities that may provide them with future staff members (In fact, roughly 20% of their staff are UMBC alumni). If all goes well, Mitchell hopes to collaborate again and maybe even branch out to other local businesses.

Correlation Aware Optimizations for Analytic Databases

Hideaki Kimura, Brown University

1:00pm Friday 9 March 2012, ITE 325b, UMBC

Recent years have seen that the analysis of large data-sets is crucially important in a wide range of business, governmental, and scientific applications. For example, research projects in astronomy need to analyze petabytes of image data taken from telescopes. Providing a fast and scalable analytical data management system for such users has become increasingly important.

The major bottlenecks for analytics on such big data are disk- and network-I/O. Because the data is too large to fit in RAM, each query causes substantial disk I/O. Traditional database systems provide indexes to speed up disk reads, but many analytic queries do not benefit from indexes because data is scattered over a large number of disk blocks and disk seeks are prohibitively expensive. Furthermore, such huge data sets need to be partitioned and distributed over hundreds or many thousands of nodes. When a query requires more than one data at once, such as a query involving a JOIN operation, the data management system must transmit a large amount of data over the network. For example, the Shuffle phase in Map-Reduce systems copies file blocks over the network and causes a significant bottleneck in many cases.

Our approach to tackling these challenges in big data analytics is to exploit correlations. I will describe our correlation-aware indexing, replication, and data placement which make big data analytics faster and more scalable.

Finally, if time allows, I will also introduce another on-going project to develop a scalable transactional processing system on modern hardware in collaboration with Hewlett-Packard Laboratories.

Hideaki Kimura is a doctoral candidate in the Computer Science Department at Brown University. His main research interests are in data management systems. His dissertation research with Prof. Stan Zdonik is on correlation-based optimizations for large analytic databases. He also worked on transaction processing systems exploiting modern hardware at HP Labs.

Host: Anupam Joshi
See http://csee.umbc.edu/talks for more information

Interactive visual computing for knowledge discovery
in science, engineering and training

Dr. Jian Chen
University of Southern Mississippi

1:00pm Wednesday 7 March 2012, ITE 325b UMBC

Advances in simulations and lab experiments are producing huge datasets at unprecedented rates, and deriving meanings from these data will have far-reaching impacts on our lives in many areas of science, engineering, and medicine. Visualization and interactive computing provide great tools for exploiting these data in scientific discovery and engineering innovations. A limiting factor in the scientific use of visualization tools is the lack of guiding principles to identify and assess visualization methods that are helpful in scientific tasks. In this talk, I present research designed to advance knowledge discovery through the design and evaluation of interactive visualizations. Experiments on image illumination and density are described that successfully address this limitation in brain imaging for medical diagnoses. I also present the theoretical foundations that have led to the various choices in visualization design. In the second part of the talk, I argue that most existing tools designed for scientific discovery fail to address the dynamic nature of the discovery workflow. I present a new visualization tool, VisBubbles, that integrates programming, visualization, and interaction in one environment to create fluid workflows in which new hypotheses can be tested efficiently. VisBubbles augments interactive computing and analysis of time-varying motion data of bat flights by enabling dynamic displays, thus facilitating scientists' quest for new knowledge. I present the design methods we have followed in our long-term collaboration with biologists and engineering scientists on motion analysis. Finally, I present future work I envision in interactive visualization that will be critical in developing future visualization tools for science, engineering, and training.

Jian Chen is an assistant professor in the School of Computing at the University of Southern Mississippi. She is the founder and director of Interactive Visual Computing Lab. Her research is in the broad area of interaction and visualization, with current focuses on the emerging field of scientific visualization theory and workflow analysis. She has published numerous articles in top journals and international conferences. Her panel on combining human-centered computing and scientific visualization received honorable mention at the 2007 IEEE Visualization Conference. She was a postdoc at Brown University with Drs. David H. Laidlaw (CS) and Sharon Swartz (BioMed) from 2006 to 2009. She has a Ph.D. degree in Computer Science from Virginia Tech and Master’s degrees in both Computer Science and Mechanical Engineering. Her research has been funded by DHS and NSF.

Host: Penny Rheingans

See here for more information

EE Graduate Seminar

Spectrum Wars: LightSquared vs. GPS

Professor Chuck LaBerge
Professor of the Practice, CSEE Dept/UMBC

11:30am-12:45pm Friday, 2 March 2012, ITE 231

The radio-frequency spectrum is a limited resource. Within the US, commercial use of the spectrum is administered by the Federal Communications Commission (FCC), while government use of the spectrum is administered by the National Telecommunications and Information Administration. Currently, the regulatory community is locked in a battle about spectrum utilization in the vicinity of 1.5 GHz. This struggle pits millions of users of GPS technology for position and time information against technical innovators desiring to bring 4G wireless communications to millions of users in underserved populations. So who wins the spectrum wars?

The talk will outline the technologies involved, and provide a time-line of the regulatory actions to date. There are some innovative things going on here, and some simple analysis will show why there are points of contention. A final resolution cannot be provided at this time, because the issue is currently an open discussion in FCC. And, as might expected, there are financial and political ramifications as well.

This talk will provide an interesting insight into how the 'real world' works.

Dr. LaBerge is Professor of the Practice of Electrical and Computer Engineering in the CSEE at UMBC, where he teaches a wide variety of courses ranging from Introductory Circuits to Error Correcting Codes. From 1975-2008, he was employed by Bendix, which became AlliedSignal, which became Honeywell through a series of corporate mergers. He retired in July 2008 as the Senior Fellow for Communications, Navigation, and Surveillance in Honeywell's Aerospace Research and Technology Center.

Dr. LaBerge has worked on precision landing systems and a wide variety of aeronautical radios and applications. He's recognized as an expert in issues involving interference to aeronautical systems. His technical, writing, and editorial contributions have received numerous citations from regulatory bodies, and he was the winner of the Best Paper of Conference at the 2000 IEEE/AIAA Digital Avionics Systems Conference.

Dr. LaBerge is a Senior Member of IEEE, a member of Tau Beta Pi, and an inductee in the Order of the Engineer. He received his BES-EE and MSE-EE, degrees, both with Honors, from The Johns Hopkins University and the PhD. in Electrical Engineering from UMBC. His three kids are older than his students. He's been married to his patient wife for almost 38 years.

Host: Prof. Joel M. Morris

Using Static Analysis to Diagnose
Misconfigured Open Source Systems Software

Ariel Rabkin, UC Berkeley

1:00pm Monday 5 March 2012, ITE 325b UMBC

Ten years ago, few software developers worked on distributed systems. Today, developers often run code on clusters, relying on large open-source software stacks to manage resources. These systems are challenging to configure and debug. Fortunately, developments in program analysis have given us new tools for managing the complexity of modern software. This talk will show how static analysis can help users configure their systems. I present a technique that builds an explicit table mapping a program's possible error messages to the options that might cause them. As a result, users can get immediate feedback on how to resolve configuration errors.

Ari Rabkin is a PhD student in Computer Science at UC Berkeley working in the AMP lab. His current research interest is the software engineering and administration challenges of big-data systems. He is particularly interested in applying program analysis techniques to tasks like log analysis and configuration debugging. His broader interests focus on systems and security, including improving system usability by making systems easier to understand, the connections between computer science research and technology policy, developing program analysis techniques that work acceptably well on large, complex, messy software systems.

Host: Anupam Joshi
See http://csee.umbc.edu/talks for more information