Department of Computer Science and Electrical Engineering

Making Sense

For his master's thesis, Computer Engineering student Kirit Chatterjee worked with scientists from UMBC's Center for Advanced Sensor Technology (CAST) on an innovative temperature sensor for premature babies.

In hospitals, doctors use a thermistor probe to monitor the temperature of a premature baby. But, the glue used to attach it is harmful for the baby, whose skin is as fragile as tissue paper.

“When the probe is removed, there is a high risk of “epidermal stripping” occurring-i.e. the skin of the baby can tear, leaving it open to infection,” explains Kirit Chatterjee, a Computer Engineering graduate student. For his master’s thesis, Kirit helped develop a new temperature sensing device that avoids this problem.

It wasn’t easy. During research, other obvious options had been shot down one by one: Bluetooth sensors had batteries that leaked toxic chemicals. Wireless sensing devices emitted energy that was harmful for the baby.

The solution, supported by an NIH grant, and later commissioned by General Electric (GE), was the result of the combined brain-power of a group of UMBC scientists led by Dr. Govind Rao, Director of UMBC’s Center for Advanced Sensor Technology (CAST). Dr. Yordan Kostov (CAST), Dr. Hung Lam (CAST), and Dr. Ryan Robucci (CSEE)–Kirit’s advisor for the project–were the team’s key players.

Together they created a patch containing a unique fluorescent orange dye. “The intensity of the orange emission depends on the temperature,” explains Dr. Kostov, the senior scientist on the temperature project who also worked closely with Kirit. When the baby’s temperature rises, he explains, the orange patch becomes brighter.

Recording and translating the patch’s fluorescence into a temperature reading that a doctor could understand was Kirit's job. “My part,” explains Kirit, “was to take care of the Engineering side—namely, to build the sensing apparatus.”

Choosing the right camera to monitor the dye was another challenge. The project was bound to a strict budget since the new sensor system was slated for mass production by GE. Therefore, expensive scientific cameras were out of the question.

Instead, Kirit reverse engineered and manipulated a much more affordable camera to serve his purposes. He used a two megapixel camera–the same camera found inside an iPhone 3–to monitor the dye in the patch.

“The dye is just the target for the Computer Engineer,” he says. “To the engineer, it’s just photons being emitted which translate to analog voltage signals inside the camera which then translate to digital bits inside the FPGA and then are analyzed.”

Next, Kirit used an FPGA in order to tap into the camera and retrieve its data, and MATLAB to translate the data into a traditional temperature reading.

The result is a temperature sensing device that is affordable, accurate, and, most importantly, safe for the baby. Dr. Kostov explains that when the GE contract comes to an end this September, the patch system will undergo clinical trials and toxicology tests. If all goes well, the new system should be found in premature baby incubators across the world in as little as two years.

Congratulations to our December Ph.D. graduates! Read on to hear about their Ph.D. dissertation research and their plans for the future. 

	Dr. Karuna Joshi Computer Science Semantically Rich, Policy Based Framework to Automate Lifecycle of Cloud Based Services Mentors: Yelena Yesha and Tim Finin Thesis Topic: Dr. Joshi developed a new framework to automate the acquisition, composition, and consumption/monitoring of virtualized services delivered on the cloud. The lifecycle consists of five phases of requirements, discovery, negotiation, composition, and consumption. She has developed ontologies to represent the concepts and relationships for each phase using Semantic Web languages. She has also developed a protocol to automate the negotiation process when acquiring virtualized services. "I chose to concentrate on Cloud Services automation for my Ph.D. thesis since I was able to draw upon my extensive experience as an IT Project Manager to determine open issues that need to be addressed for broader adoption of cloud computing." Future plans: Dr. Joshi has received funding from NIST to continue her research on Cloud Computing and Big Data management. As part of this funding, she will be working as a research faculty member in the CSEE Department. In the spring, Dr. Joshi will teach a course on Software Design and Development.
	Dr. Phuong Nguyen Computer Science Data Intensive Scientific Compute Model For Multicore Clusters Mentors: Milton Halem and Yelena Yesha Thesis Topic: Dr. Phuong developed a scalable workflow system on top Apache Hadoop for orchestrating data intensive scientific workflows. New scheduling algorithms have been developed in the workflow system to manage and reduce latency of the workflow executions. The evaluations of the workflow system on the climate data processing and analysis application (several TB dataset) showed that it is feasible and improved. The scientific results of the application provide new global climate change indicators for the decade of 2002-2012. "The Ph.D. topic came from the motivations related to our NASA and NOAA projects which need to process and analyze very large datasets to study climate change. My research contributions provide new tools for accelerating scientific discoveries from very large datasets and the scientific results." Future plans: Work on research and development related to building large distributed systems or applications.
	Dr. David Chapman Computer Science A Decadal Gridded Hyperspectral Infrared Record for Climate Mentors: Milton Halem Yelena Yesha, Shujia Zhou, John Dorband, Joel Susskind (NASA) Thesis Topic: Dr. Chapman helped improve our understanding of Global Climate Change by creating a Climate Data Record (CDR) of Outgoing Longwave Radiation (OLR) from 55 terabytes of NASA satellite weather observations from the Atmospheric Infrared Sounder (AIRS). He developed a parallel data-intensive scientific workflow infrastructure making use of Large Array Storage (LAS) in order to show the complete derivation these climate trending results. "Global Climate Change and Global Warming are very important and controversial issues, and we need to measure if they have actually happened. AIRS is the first of its kind because it measures hyperspectral radiation. The trick is to take a Big Dataset, and squeeze it into something meaningful. This takes a lot of hardware, and typically a large software team to develop the processing system. I showed how the Large Array Storage (LAS) paradigm can simplify these calculations along with their derivation." Future plans: Dr. Chapman has applied for a post doc in Climate Modeling at Columbia University. It would allow him to do interdisciplinary work to develop Big Data Analytics infrastructure alongside the statistical validation of climate models.
	Dr. Niyati Chhaya Computer Science Joint Inference for Extracting Soft Biometric Text Descriptors from Patient Triage Images Mentors: Tim Oates Thesis Topic: Dr. Chhaya's research was a combination of Soft biometrics, Probalistic Graphical Models, and Natural Language Processing techniques. The aim was to extract soft biometric text labels (using computer vision techniques) from images of mass disaster victims. The main contributions of the work include soft biometric feature extractors, a probalistic graphical model that exploits related appearance-related features, and a novel study of natural human descriptors using NLP techniques that help understand 1) how people describe other people and 2) order and structure of free text human descriptions. "Socially, this work aims at addressing the issue of providing victim information to the public in a post disaster situation. It forms an important contribution to anonymize available image data using text labels to facilitate efficient search. Technically, this is the first work of its kind that aims at using Probabilistic Graphical Models to relate Soft biometric features, and in turn improve the overall accuracy of text label extraction. Also, the NLP study is a significant contribution along with the datasets gathered for this research. The key contribution is the use of techniques from computer vision, machine learning, and NLP to build a robust system that extracts soft biometric features." Future Plans: Dr. Chhaya has moved back to India and will work as a Computer Scientist with Adobe Research Labs starting in January.
	Dr. Yasaman Haghpanah Jahromi Computer Science A Trust and Reputation Mechanism Through Behavioral Modeling of Reviewers Mentors: Marie desJardins Thesis Topic: Dr. Haghpanah introduced a novel mechanism to represent trust and reputation using behavioral modeling of online reviewers. Her approach helps decision makers utilize reputation information more effectively. "Evidence shows that people are now relying more and more on other people's posted opinions for making decisions about which product to buy, which movie to watch, etc. So, I modeled the raters' or in general information providers' behavior and showed how we can improve our decisions by knowing the behavior of the online raters." Future Plans: Dr. Haghpanah is currently interviewing for postdoctoral positions at universities and research labs to extend and broaden her knowledge.
	Dr. Ganesh Saiprasad Electrical Engineering Automatic Detection of Adrenal Gland Abnormality Using The Random Forest Classification Framework combined with Histogram Analysis Mentors: Chein-I Chang Thesis Topic: Dr. Saiprasad proposed a new, more accurate way to detect adrenal abnormalities: rather than using the popular Region of Interest (ROI) method, Dr. Saiprasad suggests segmenting the adrenal gland automatically using the random forest classification framework and then performing histogram analysis. "Working with radiologists and surgeons at the University of Maryland Medical Center on my Master's research helped me pick a topic for my Ph.D. research. Adrenal gland abnormality detection is a very challenging problem and we have some preliminary results now to show that it can be done automatically. This is a very important step forward in using such systems as decision support tools and also the same methodology can be used for other smaller organs to detect abnormalities which are challenging to detect on CT." Future Plans: Postdoc at the National Institute of Standards and Technology (NIST)
	Dr. Kevin Fisher Computer Engineering Real-Time Progressive Band Processing for Linear Spectral Unmixing and Endmember Extraction Mentors: Chein-I Chang Milton Halem (NASA) Thesis Topic: Dr. Fisher developed three algorithms that work on hyperspectral images–pictures (often taken by satellites or airborne cameras) where each pixel is a spectograph of the materials in that part of the image. His algorithms work to reduce the amount of irrelevant data in the image, detect samples of pure materials in the image, and then estimate the abundance of those materials in each pixel in the image. "In 2006, I finished a Master's thesis with Prof. Alan Sherman on electronic voting systems. It was an engaging project in a hot topic in computing, but it was not related to the work I was doing as an intern at NASA Goddard Space Flight Center. I sat down with my supervisor and some NASA technologists, and looked for common areas of interest between UMBC and NASA. Hyperspectral image processing was on the short list and that's when I contacted Prof. Chein-I Chang about potential research projects." Future Plans: Dr. Fisher will continue working at NASA as a software systems engineer working on the ground antenna system for the Geostationary Operational Environmental Satellite, R-Series (GOES-R) spacecraft, a new line of weather satellites due to launch in 2015.
	Dr. Joel Sachs Computer Science Supporting Citizen Science and Biodiversity Informatics on the Semantic Web Mentors: Tim Finin Thesis Topic: Dr. Sachs introduces an approach to constructing ontologies by layer, designed to make it easier for both data publishers and application developers to tailor-fit semantics to use cases.

NASA Goddard Space Flight Center, in Greenbelt, MD (20 minutes south of UMBC), offers a wide array of valuable, paid internships for Undergraduates in the summer.  Please see the attached flyers. 

IMPORTANT NOTE: while the end date for applications is in March, Goddard is doing a FIRST CUT by Jan 30, so the good jobs will all be taken then.  PLEASE APPLY BY JAN 30!!

FLYERS:

Internships at Goddard

One Stop Shopping Initiative (OSSI) Information

This week the UMBC chess program will field a team in the 2012 Pan-American Intercollegiate Team Chess Championship which will take place December 27-30 in Princeton, NJ.

The UMBC team is shown here along with GM Sam Palatnik (Chess Program Associate Director), Alan Sherman (Chess Program Director and Professor of Computer Science and Electrical Engineering) and  NM Igor Epshteyn (Chess Program Coach). The current team lineup includes Giorgi Margvelashvili (Captain), Niclas Huschenbeth, Sasha Kaplan, Nazi Paikidze and alternates Sabina Foisor and Adithya Balasubramanian.

The Pan-Am tournament has been held annually since 1946 and determines the top university chess team in the Americas. UMBC's chess team has competed in the tounament since 1990 and won or tied for first place nine times, a record unmatched by any other college chess team. The top four U.S. schools in the Pan-Am will advance to the President’s Cup, the Final Four of College Chess which will take place in early April in Herndon, Virginia. The Final Four which was started in 2001 determines the top U.S. college team. UMBC's chess team has won the Final Four a record six times.

Live commentary featuring GM Ronen Har-Zvi will be broadcast on the Web at livestream and results and pairings will be posted regularly on the tournament website.

The Heidelberg Laureate Forum is an extraordinary opportunity for a group of students and young researchers to interact with some of the greatest minds of Mathematics and Computer Science for a week of scientific exchange and inspiration.

It will bring together winners of the Abel Prize, the ACM Turing Award, and the Fields Medal with young scientists from Computer Science and Mathematics. The first forum will be held over a week in September 2013 in Heidelberg and will consist of presentations, workshops, panel discussions and social events, all of them involving both the laureates and the young scientists. Some travel support is available.

The Forum will invite undergraduate students, PhD candidates, and young researchers at the postdoctoral level. Apply online by submitting a statement of purpose, CV, and the names of 1-3 people who can write recommendations. PhD candidates and postdocs should provide more information on their research. The deadline for applications is February 15, 2013 but may close early if the maximum number of applications that can be reviewed is reached.

The Center for Hybrid Multicore Productivity Research is a collaborative research center sponsored by the National Science Foundation with two university partners (UMBC and University of California San Diego), six government, and seven industry members. The Center's research is focused on addressing productivity, performance, and scalability issues in meeting the insatiable computational demands of its members' applications through the continuous evolution of multicore architectures and open source tools.

As part of its annual industrial advisory board meeting next week, the center will hold an afternoon of public tutorials from 1:00pm to 4:00pm on Monday, 17 December 2012 in room 456 of the ITE building at UMBC. The tutorials will be presented by students doing research sponsored by the Center and feature some of the underlying technologies being used and some of their applications. The tutorials are:

• GPGPUs – Tim Blattner and Fahad Zafa
• Cloud Policies – Karuna Joshi
• Human Sensors Networks – Oleg Aulov
• Machine Learning Disaster Warnings – Han Dong
• Graph 500 – Tyler Simon
• HBase – Phuong Nyguen

The tutorial talks are free and open to the public. If you plan to attend, please RSVP by email to Dr. Valerie L. Thomas, .

UMBC Computer Science Alumni Donald Miner (BS ’06, PhD ’10) (left) and Adam Shook (BS ’09, MS expected ’13) (right) have written a book on the popular MapReduce paradigm that has revolutionized the way collections of computers are used to process large amounts of data in parallel. Their book, MapReduce Design Patterns Building Effective Algorithms and Analytics for Hadoop and Other Systems, was published by O’Reilly Media in December.

“Adam and I were teaching Hadoop classes and we saw a gap: students would pick up on how hadoop worked mechanically, but struggled to understand how to solve problems with it,” explains Donald, who now works as a Solutions Architect at EMC Greenplum. “This book is intended for people who have a basic understanding of Hadoop, but want to start solving their problems effectively.”

Adam and Donald met in fall 2008 during an Artificial Intelligence class at UMBC. Donald, a Ph.D. student working with Dr. Marie desJardins on machine learning and multiagent systems research, was teaching the class. Adam, an undergraduate Computer Science student, was taking the class. Later, the pair ended up working together at ClearEdge IT Solutions.

“We worked well together and our skills and interests complemented each other well, so when I had the opportunity to write this book I knew it would be a much better book doing it with him than doing it alone,” says Donald.

Now Adam works with big data technologies like Hadoop, Accumulo, Pig, and ZooKeeper as a Software Engineer at ClearEdge IT Solutions. He is working towards his Master’s in Computer Science at UMBC under Dr. Tim Finin. His research deals with developing an efficient in-memory distributed database for Semantic Web applications.

“I don’t know how I do it,” says Adam about working full time, being in graduate school, and writing a book. “Caffeine helps.” He plans on finishing up his degree in 2013.

Ph.D. Dissertation Defense

Supporting Citizen Science and
Biodiversity Informatics on the Semantic Web

Joel Sachs

10:00am Friday, 14 December 2012, ITE 325b

It is common for Semantic Web documents to use terms from multiple ontologies, with no expectation that the full semantics of each ontology will be imported by consuming applications. This makes sense, because importing all ontologies referenced by a document causes both practical and logical problems. But it has the drawback of leaving it to the consuming application to determine appropriate semantics for the terms being used. We describe an approach to constructing ontologies by layer, designed to make it easier for both data publishers and application developers to tailor-fit semantics to use cases.

The layers that we develop correspond to patterns in the RDF graph. This contrasts with typical approaches to modular ontology development, where the layers are domain based. The three primary motivations for this approach are i) preserving computational tractability; ii) enabling easy coupling and decoupling with foundational ontologies and iii) maintaining cognitive tractability. This third motivation is still under-studied in semantic web development; we consider it in relation to reducing the ease with which ontology users can publish data that accidentally implies things that they do not mean. This is important always, but becomes especially so in citizen science, where users will naturally bring intuitive semantics to the terms that they encounter.

We describe case studies that involved deploying our approach in the context of citizen science activities, and which provided opportunities to assess its capabilities and limitations. We also describe subsequent work aimed at addressing these limitations, and, by applying newly defined layers over the underlying data, show that we are able to improve the competency of our knowledge base. More generally, we show that appropriately combining triple-pattern-based layers allows us to support a wide variety of use cases with varied (and occasionally conflicting) requirements.

In addition to our approach to semantic layering, contributions include an improved understanding of how to blend social and semantic computing to support citizen science, and a collection of layers for representing biodiversity information in RDF, with a focus on invasive species. Compared with other proposed “semanticizations” of the Darwin Core standard for representing biodiversity occurrence data, these layers involve minimal modification to the Darwin Core vocabulary, and make maximal use of the Darwin Core namespace, thereby simplifying the transition of current practices onto the semantic web.

Committee: Drs. Tim Finin (Chair), Anupam Joshi, Tim Oates, Cynthia Parr, Yelena Yesha, Laura Zavala

On December 12, CSEE professor Hillol Kargupta will receive the 10-year Highest-Impact Paper Award from the IEEE International Data Mining Conference (ICDM) in Brussels, Belgium.

The winning paper—“On the Privacy Preserving Properties of Random Data Perturbation Techniques”—discusses privacy-preserving data mining and it also received the 2003 ICDM Best Paper Award. It is co-authored by former UMBC PhD student Souptik Datta (CS '08) and Dr. Kargupta’s colleagues at Washington State University—Qi Wang and Professor Krishnamoorthy Sivakumar.

Privacy Preserving Data Mining (PPDM) is important in many domains where the data is privacy sensitive and exposing the data to a third party for mining is not an option. Researchers have come up with many PPDM algorithms that attempt to protect data privacy while allowing analysis of the data for detecting patterns. Many of these algorithms make use of randomized techniques. This paper offers a perspective on the structure of random noise using theories of random matrices and their spectral properties in order to analyze their role in preserving data privacy while still keeping data patterns intact for analysis. It points out that spectral properties of random matrices can be exploited to create attacks on many commonly used privacy-preserving data mining algorithms.

Kargupta and his associates point out is that you must be very careful when using random noise to protect data, since it can be easily filtered out. “Random noise is really not that unpredictable,” explains Kargupta, since it has a pattern of its own.

Out of all of the papers on data mining published within the last ten years, this year Dr. Kargupta’s paper was chosen by IEEE as the most impactful paper in its field.

UMBC will once again host the Global Game Jam. The weekend-long game development event will be held this year from January 25-27. UMBC is one of hundreds of host sites around the world. Other local sites include College Park, the Universities at Shady Grove, and George Mason.

“I expect an exciting mix of students, friends, alumni, and game developers for a weekend of creative fun,” says Dr. Olano, director of UMBC’s Game Development Track. Last year he and Visual Arts professor Neal McDonald ran the event out of UMBC’s GAIM Lab where game developers of all levels gathered to conceive and create video games around a common theme.

Last year the theme was Ouroboros, a symbol of perpetual renewal. The theme inspired games like Bit Exhaust, a space-invaders-esque Windows phone game and Snake ‘N Bake (pictured above), a two-player game where a snake must help a cupcake make it to the oven before the tasty confection gets hit by a fireball.

The theme for this year’s competition will be announced at 5 p.m. on January 25^th so that all parts of the game development process—from coming up with a game concept to finishing a playable video game–will have to be carried out during one single adrenaline-filled weekend.

Visit globalgamejam.org to register for the event. Thanks to support from Next Century Corporation, registration for the UMBC site is free and open to anyone 18+.