• UMBC Division of Student Affairs -- Office Assistant -- ID# 9249688
• UMBC The Retriever Weekly -- Advertising Manager -- ID# 9249934
• UMBC The Retriever Weekly -- Circulation Assistant -- ID# 9250072

• WTOP AM/FM -- Freelance News Assistant -- ID# 9247646
• Bright Spot, Inc. -- High School Mathematics Tutoring -- ID# 9245891
• YMCA of Central Maryland -- Preschool Substitute Teacher (718-221) -- ID# 9250133
• Progress Unlimited -- Awake Overnight - Direct Support Staff -- ID# 9249182

Established in 1918, today WSSC is the 8th largest water and wastewater utility in the nation, with a network of more than 5,500 miles of fresh water pipeline and nearly 5,400 miles of sewer pipeline.  Serving nearly 1.8 million residents in Prince George’s and Montgomery counties, our drinking water has always met or exceeded federal standards. 

College engineering majors listen up! Entries will soon be accepted for the annual Washington Suburban Sanitary Commission (WSSC) Joyce Starks Engineering Scholarship essay contest. To be eligible for the $1000 scholarship, students should have a permanent home address in the WSSC service district that includes Prince George’s and Montgomery counties. Eligible students must be enrolled in a degree program that leads to a Bachelor of Science in Engineering or an advanced degree in engineering. Past winners are also eligible to compete.

Applicants should send a copy of their official transcript along with a cover letter, proof of permanent residency, two references and a 400 to1000 - word essay that answers the following question:

"What, in your opinion, is the biggest challenge/threat for the water/wastewater industry in the United States, and why?"

The reference letters must be submitted separately or in a sealed envelope if sent with the application materials. The scholarship winner may also be offered a paid internship at WSSC in the summer of 2013. The scholarship will be awarded at the August Commission meeting. 

Send applications to Charlett Bundy, Esq., WSSC Corporate Secretary, 14501 Sweitzer Lane, Laurel, MD 20707. Applications must be postmarked by June 30, 2012. 

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

Q:  Tell me a little bit about yourself: Major? Hometown? Favorite animals? Random facts?

A: I am an Asian Studies major and a Korean minor, I may change to modern languages though. I was born in Baltimore but raised in Trinidad. I’m a new transfer from Penn State, PSU!  I like giraffes, mustaches, and hotdogs!

Q:     How did you learn about the Diversity Education Internship (DEI)? Did you know right away that you wanted to do it?

A: A friend of mine was working front desk in the Mosaic and she told me about the application and I jumped right on it, what better way to get to know a diverse group of people faster than working in the Mosaic Center?

Q: Have you volunteered in any other diversity positions before you started? How did you learn skills you needed to know for this internship?

A: I had many leadership roles at PSU before attending UMBC; I was President of the Black Student Union and VP of Rainbow Paws, our LGBTQA org, and a student mentor for high school students through a program called Talent Search. Also, the summer before my transfer, I was training to work as an Ethnic Outreach Coordinator in our LGBT office on campus at PSU.

Q: How many hours each week do you work in the OSL Mosaic Center? What do you do during that time?

A: We are required to devote 5 hours of time a week but it always ends being more because the office is so much fun. We spend a lot of time joking around but we take care of business too. I am on the marketing and outreach team with Andrea and we try our best to spread the word about the office and internship. We also facilitate discussions held here and those are always an enriching experience.

Q: What is the most difficult thing you have encountered so far into the internship? What is the most interesting thing you have encountered?

A: Personally, I feel the most difficult thing I have encountered is the use of sensory language. I have a pretty big mouth and always say what is on my mind so it can be difficult to just sit back and listen. I have to say that that is also the most interesting thing I have encountered because when I just listen I learn so much more about a person and the things around me I couldn’t identify myself.

Q: What would you say to other students inquiring about becoming the next generation of DEIs?

A: I would say if you know want to get to know, work, and meet great people then try to become an intern. Not just anyone can come in here and represent the office; you have to have good a work ethic, personality, and most of all, communication skills. You have to know how to communicate because understanding a diverse group of people requires an affinity comprehension.

Q: What are your plans/goals for after UMBC?

A: Graduate school of course because a bachelor’s degree will not take you as far as it used to. I would love to get my PhD in communication because I love conversing and the art of languages. I plan to work in the University system, either as a professor or in Student Life.