Department of Computer Science and Electrical Engineering

Raytheon, a defense contractor and electronics company specializing in defense, homeland security, and mission systems integration and support services, is looking for a Software Engineering Intern to work on a NASA program involving the maintenance and evolution of the EOSDIS ECS System. Currently operational at three NASA Data Centers, the ECS system ingests, distributes, and stores on-line earth science data.

Proficiency in JAVA in a Linux or UNIX development environment is required, along with good communication skills and the ability to work in a structured team environment with other software engineers. Experience with shell scripting, Perl, C++, and some experience with database applications is desired, but not required.

The paid position is only open to rising Seniors majoring in Computer Science, Computer Engineering, or Mathematics who have a G.P.A. of 3.0 or higher. The intern will need to obtain a government security clearance.

For more information, click here.

To apply for the internship, click here.

TechGuard Security, a very local (so local, in fact, that it's on campus) company dedicated to addressing National Cyber Defense initiatives and U.S. Critical Infrastructure Security is seeking a Web Developer Intern and Cyber Security-Malware Intern for the summer or fall. Both positions are paid.

The Web Developer Intern will be part of a project team that will design, develop, and test dynamic web pages for cyber security related web applications. Knowledge of HTML, Flex, JavaScript, JQuery, and Java is expected. The position will provide the intern with experience with AJAX, JSON, Google GSON, and XML, while exposing him/her to cyber security fundamentals like TCP/IP networking, firewalls, and intrusion detection systems.

The Cyber Security-Malware Intern will research, investigate, analyze, validate, and determine the effects of discovered malware. Some knowledge in computer programming, Information Security, and Network Security is expected.

Visit UMBCworks to apply for the positions. For more information, click here.

It will be a busy summer for Computer Science and Electrical Engineering professor Hillol Kargupta, who has been invited to speak at three international conferences on his research in data mining.

The first, from June 4-6, is the 3^rd International Conference on Sensor Systems and Software to be held in Lisbon, Portugal. Dubbed S-CUBE 2012 for short, the conference aspires to be a venue to “address the research challenges facing system development and software support for wireless sensor network-based systems that have the potential to impact society in many ways,” says the website.

As the keynote speaker, Dr. Kargupta will discuss the possibilities of wirelessly harnessing data from vehicles. Features of the talk include an overview of the market, emerging product-types, core technical challenges, and a description of how advanced data analysis has helped create new and innovative, commercially successful products.The talk reflects the work he’s been doing at Agnik, a Columbia-based data analytics company for distributed, mobile, and embedded environments that Dr. Kargupta co-founded.

From August 1-3, Dr. Kargupta will speak at the 36^th Annual Conference of the German Classification Society in Hildesheim, Germany. This year, Dr. Kargupta joins nine other confirmed speakers from around the world, who will speak on topics ranging from Data Analysis to Machine Learning to Knowledge Discovery. His talk will explore distributed data stream mining from sensor networks and discuss algorithms and data mining applications in embedded machine-to-machine wireless networks.

Dr. Kargupta closes his international tour with a stop at the Sixth International Workshop on Knowledge Discovery from Sensor Data (Sensor-KDD ’12) in Beijing, China. One of four invited speakers, Dr. Kargupta joins Dr. Ashok N. Srivastava of the NASA Ames Research Center, Dr. Ian Davidson, a professor of Computer Science at UC: Davis, and Dr. Dr. Ralf Birken, a professor of Civil and Environmental Engineering at Northeastern University.

Need a little help with next year's tuition? If you're majoring in Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or Systems Engineering, consider applying for a Northrop Grumman Foundation/ UNCF Scholarship of up to $7,500.

The need-based scholarship is open to students with a minimum GPA of 3.0 who are U.S. citizens. Applicants must submit an essay, two letters of recommendation, and an online application.

To apply for the scholarship, click here.

Application Deadline: May 30, 2012

Masters Thesis Defense

Mobile Relays Based Federation of Multiple Wireless
Sensor Network Segments with Reduced-Latency

Jerome Stanislaus

10:00am Tuesday, 15 May 2012, ITE 325b, UMBC

Wireless sensor networks are used to continuously monitor certain area of interest and send data to a base station for processing. In many applications, WSN serve in inhospitable environments where multiple nodes may simultaneously fail causing the network to be divided into disjoint segments. Restoring connectivity in this case would be necessary for the WSN to become fully functional again. A similar scenario is when multiple standalone WSNs may need to be federated to collectively handle an important event that requires data sharing among these networks. A viable approach for establishing connectivity among these network segments is by employing mobile data collectors (MDCs). Few MDCs can be used to create intermittent links among the segments by touring and carrying data. Obviously, the travel path of the MDCs will affect the date delivery latency. We present two algorithms for finding optimized travel routes for the MDCs so that the average and maximum delay for delivering the inter-segment traffic is minimized. The algorithms deal with two variants of the federation problem that differ in the available MDC count. The first algorithm handles the case when the number of available MDCs is more than the number of segments, while the second tackles the problemwhen the MDC count is significantly less. The performance of the algorithm is validated through simulation.

Committee: Dr. Mohamed Younis (chair), Dr. Charles Nicholas, Dr. Gymama Slaughter

Congratulations to CSEE lecturer Susan Mitchell who, on April 6, 2012, successfully defended her Ph.D. dissertation entitled “Software Process Improvement through the Removal of Project-level Knowledge Flow Obstacles: The Perceptions of Software Engineers.”

Eight years ago, Dr. Mitchell began working toward her Ph.D. in Software Engineering through UMBC’s Information Systems Department. Working as a lecturer in the Computer Science and Electrical Engineering Department while pursuing her degree part-time, Dr. Mitchell’s triumph is an inspiration to all those working stiffs who someday dream of doing the same.

Dr. Mitchell's incentive to go back to school was closely tied to her work as a lecturer. “I teach CMSC 345, Software Design and Development, and I wanted to further my knowledge in the software engineering field,” she says. Designed around the completion of a software-design project, the course mimics a job in the software industry.

Her dissertation—“Software Process Improvement through the Removal of Project-level Knowledge Flow Obstacles: The Perceptions of Software Engineers”—is a case study of a software development team at a major U.S. Department of Defense contracting organization. “Through qualitative methods, such as interviews and focus groups, I was able to locate obstacles to the flow of knowledge within the team that, as perceived by the software engineers, if mitigated or removed, would increase individual efficiency and end-product quality.”

Dr. Mitchell describes software development as a "very human-centric, knowledge intensive endeavor.” “I believe that the major strides in software process improvement (i.e. efficiency and end-product improvements) will not come from process automation or standardization or from the introduction of new development tools, but from changes in the ways that software engineers and managers approach development,” she explains.

Though her title may have changed, Dr. Mitchell's plans are to remain at UMBC as a lecturer. She does hope, however, to continue her research in the area of software process improvement. 

Congratulations to Shamit Patel (CS, MS '12, BS '10) on securing the highly competitive National Defense Science and Engineering Graduate Fellowship (NDSEG).

After graduating at the end of the semester with an M.S. in Computer Science, Shamit plans on pursuing his Ph.D. in Neurosciences–specializing in Computational Neuroscience–at the University of California, San Diego this Fall. The NDSEG fellowship will cover Shamit's education expenses for three years and offer a monthly stipend.

"I applied for an NDSEG Fellowship so that I could have the freedom to pursue the exact research that I am interested in," explains Shamit.

As a Master's student working with Professor Tim Oates, Shamit developed an implementation of Jeff Hawkins and Dileep George's Hierarchical Temporal Memory (HTM) pattern recognition system based on an existing theory of the learning rule for dendritic integration: spike-timing-dependent synaptic plasticity (STDP). "I found that the STDP HTM system achieved far better generalization ability than the baseline HTM system."

Shamit's doctoral research lies within the same vein. "My goal is to develop a working theory of the learning rule for dendritic integration by performing appropriate neurophysiological experimentation, and to then implement a pattern recognition system based on that learning algorithm so that the algorithm can be evaluated for its generalization ability."

Photo Courtesy midlife-opportunity.com

The end of the semester is upon us, and for many that means the job search has begun. Below you’ll find a list of local job opportunities for computer savvy graduates. Hopefully you’ll find something that sparks your interest. If not, don’t forget to check back regularly for updates.

Key Tech
What they do: Develops high-tech products with a focus on medical, industrial, and consumer devices.
Positions: Firmware/ Software Designer, Circuit Board Designer
Location: Baltimore, MD
Apply

CyberPoint
What they do: provides cybersecurity products and services.
Positions: Senior Systems Engineer, Senior Software Developer, Software Developer, Reverse Engineer
Location: Inner Harbor, Baltimore
Apply

Agnik
What they do: a data analytics company for distributed, mobile, and embedded environments.
Position: Software Developer I/II – Intern
Location: Columbia, MD
Apply

Agora, Inc.
What they do: A holding company for various publishers of financial, health, travel and special interest books, and newsletters.
Position: Software Engineers
Location: Mt. Vernon, Baltimore
Apply

*Jobs posted May 15.

Parking Panda
What they do: A rapidly expanding startup that thought up a creative solution for scarce parking in Baltimore and D.C.: A web-based app that lets you rent out your personal parking pad.
Position: Front End Engineer
Location: Federal Hill, Baltimore
Apply

The Hilltop Institute
What they do: Located in UMBC’s Sondheim building, The Hilltop Institute is a health research organization that conducts research, analysis, and evaluations on behalf of government agencies, foundations, and nonprofit organizations at the national, state, and local levels.
Position: Web Developer/ Programmer
Location: UMBC
Apply

OptiMetrics, Inc.
What they do: A company that provides research and engineering services to government and industry, specifically applying science and technology to protect soldiers on the battlefield.
Positions: Mid-Level Software Engineers, Software Engineer
Location: Abingdon, MD
Apply

Information Management Services, Inc.
What they do: A biomedical computing firm.
Position: Software Developer
Location: Silver Spring, MD
Apply

Praxis Engineering
What they do: A consulting, products, and solutions firm dedicated to the practical application of software and system engineering technologies to solve complex problems.
Positions: Software Engineer, Reverse Software Engineer, Application Developer, and more
Location: Aberdeen, MD, Annapolis Junction, MD
Apply

*Jobs posted May 7.

Have a job opening you'd like to have posted here? Contact Anissa.

MS Thesis Defense

Numerical Integration Techniques for Volume Rendering

Preeti Bindu

10:00am Monday, 7 May 2012, ITE 352, UMBC

Medical image visualization often relies on 3D volume rendering. To enable interaction with 3D rendering of medical scans, improvements in the performance of Volume Rendering Algorithms need significant attention. Real-time visualization of 3D image data set is one of the key tasks of Augmented Reality Systems required by many medical imaging applications. Over past five years the development of the Graphics Processing Unit (GPU) has proved beneficial when it comes to Real Time Volume Rendering. We propose a GPU based volume rendering system for medical images using adaptive integration to improve performance. Our system is able to read and render DICOM images, implementing adaptive integration techniques that increase frame rate for volume rendering with the same quality of output images.

Committee: Dr. Marc Olano (advisor), Dr. Penny Rheingans and Dr. Samir Chettri

Congratulations to the three winners of the poster competition at the Computer Science and Electrical Engineering Department's annual Research Review, which took place in the UMBC Technology Center's business incubator and accelerator building last Friday. Winners were chosen by UMBC faculty who scored their top five choices with [-9, +9] range voting.

1st place (26 points): 
Varish Mulwad (CS, Ph.D.) "A Probabilistic Model for Generating Linked Data from Tables"
Advisor: Tim Finin

Vast amount of information is encoded in tables found in documents, on the Web, and in spreadsheets or databases. Integrating or searching over this information benefits from understanding its intended meaning and making it explicit in a semantic representation language like RDF. Most current approaches to generating Semantic Web representations from tables requires human input to create schemas and often results in graphs that do not follow best practices for linked data. Evidence for a table's meaning can be found in its column headers, cell values, implicit relations between columns, caption and surrounding text but also requires general and domain-specific background knowledge. Approaches that work well for one domain, may not necessarily work well for others. We describe a domain independent framework for interpreting the intended meaning of tables and representing it as Linked Data. At the core of the framework are techniques grounded in graphical models and probabilistic reasoning to infer meaning associated with a table. Using background knowledge from resources in the Linked Open Data cloud, we jointly infer the semantics of column headers, table cell values (e.g., strings and numbers) and relations between columns and represent the inferred meaning as graph of RDF triples. A table's meaning is thus captured by mapping columns to classes in an appropriate ontology, linking cell values to literal constants, implied measurements, or entities in the linked data cloud (existing or new) and discovering or and identifying relations between columns.

2nd place (18 points): 
Richard Van Tassel  (CS, M.S.)  "Visual Obstruction Resistance for Emotion Detection"
Advisor: Marie desJardins

There is an increasing interest in developing systems that can determine a user's emotion by analyzing a video feed of the user's face. However, it cannot always be assumed that the user's face will be completely unobstructed by facial hair or apparel. If the system is a recreational or consumer good, it could be considered too restrictive to require a perfect view of the face at all times. Obstructions can prevent the system from identifying all of the facial expression components, called action units, present in the input face. It is therefore important that such emotion detection systems are capable of coping with partially obstructed faces. I propose a technique for reducing the effect of face obstructions. The technique will learn association rules between sets of action units from a set of unobstructed faces. Then, for a given input obstructed face, the technique will infer what action units are likely to be obstructed based on the visible ones, and will use this hypothetical set of action units to infer the emotion. This technique is tested on real face data, with simulated face obstructions. It will provide a statistically significant improvement in emotion detection accuracy over the same process without the technique applied.

3rd place (16 points): 
Patricia Ordonez (CS, Ph.D) (pictured) "Multivariate Time Series Analysis of Physiological and Clinical Data"
Advisor: Marie desJardins, Tim Oates

The complexity and volume of collected medical data is greater now than at any point in the history of medicine. Providers are expected to examine large volumes of data and identify correlations between parameters based on their own clinical experience to detect significant medical events. The information overload that providers face may hinder the diagnostic process. Existing visualizations to assist the provider in analyzing information consist mainly of tables or plots of values for a particular parameter over time. Multivariate Time Series Amalgams (MTSAs) provide an integrated, multivariate approach to represent clinical and physiological data. The hybrid representation automates the personalization of baselines and threshold values based on a patient’s medical history, while also incorporating traditional baselines and thresholds. MTSA visualizations capture the rate of change of provider-selected parameters and the relationships among them.

The second half of my research consists of developing automated techniques for discovering correlations among parameters over time to assist providers in making a diagnosis. The underlying premise of my research is that the complexity of a highly integrated system such as a human being is better captured by examining patterns as multivariate temporal abstractions as opposed to conjunctions of univariate ones — the more common approach for multivariate time series analysis and in medicine. The objective of such an approach is to assist in the identification of latent patterns within the data associated with specific medical conditions or significant medical events. Thus, in addition to the MTSA visualizations, I will present two novel multivariate time series representations, Stacked Bags-of-Patterns and Multivariate Bag-of-Patterns, which have been effective at classifying medical data. These representations are more compact than the raw multivariate time series and would facilitate the retrieval of patients from large medical databases based on physiological similarity and ideally on the presence of similar medically significant events or medical conditions. These techniques been compared to two other multivariate versions of univariate time series representations, Piecewise Dynamic Time Warping and Ensemble Voting using Bag-of-Patterns. Results demonstrate the potential of using these representations for multivariate time series analysis.