Department of Computer Science and Electrical Engineering

Genetic information for chronic disease prediction

Michael A. Grasso, MD, PhD
University of Maryland School of Medicine

1:00pm Friday 23 September 2011, 227 ITE

Type 2 diabetes and coronary artery disease are commonly occurring polygenic-multifactorial diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. However, this resulted in prediction algorithms that are linked to symptomatic states, which have limited accuracy in asymptomatic individuals. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic-multifactorial diseases, and summarize ongoing efforts use this information for disease prediction.

Michael Grasso is an Assistant Professor of Internal Medicine and Emergency Medicine at the University of Maryland School of Medicine, and an Assistant Research Professor of Computer Science at the University of Maryland Baltimore County. He earned a medical degree from the George Washington University and a PhD in Computer Science from the University of Maryland. He is a member of the Upsilon Pi Epsilon Honor Society in the Computing Sciences, the Kane-King-Dodec Medical Honor Society, and the William Beaumont Medical Research Honor Society. He completed a residency at the University of Maryland School of Medicine, and currently works in the Department of Emergency Medicine at the University of Maryland Medical Center. He has been awarded more than $1,200,000 in grant funding from the National Institutes of Health, the National Bureau of Standards and Technology, and the Department of Defense, and has authored more than 35 scholarly papers and abstracts. His research interests include clinical decision support systems, clinical data mining, clinical image processing, personalized medicine, software engineering, database engineering, and human factors. He is also a semi-professional trumpet player and is interested in the specific medical needs of performing artists, especially instrumental musicians.

Host: Yelena Yesha

Ms. Camilla Hyman recently joined the Computer Science and Electrical Engineering Staff as the Business Services Specialist for the department. Ms. Hyman has replaced Ms. Donna Meyers, who retired at the end of Spring 2011.

This summer, Camilla Hyman joined the Computer Science and Electrical Engineering Department as Business Services Specialist–a role that had been left vacant by Ms. Donna Meyers, who retired at the end of Spring 2011. Ms. Hyman, who has lived in Maryland her entire life, grew up just down the road from UMBC in Catonsville, MD and now lives in Baltimore City. Apart from being an expert at all things payroll, Ms. Hyman has served as a Girl Scout leader for the past seventeen years.

Before coming to UMBC, Ms. Hyman spent nine years working for the Goddard Earth Sciences and Technology (GEST) and Joint Center for Earth Sciences (JCET) departments at UMBC. Prior to that, she worked for the Division of Behavioral and Developmental Pediatrics and Adolescent Medicine departments at the University of Maryland, Baltimore (UMB). With less than a month of CSEE office life under her belt, Ms. Hyman already says that she finds the position enjoyable. The best part about her job, she says, is learning about different cultures from the Graduate Students that she interacts with every day. 

EE Graduate Seminar

Analysis of Brain Network Connectivity
in fMRI Data using Spatial Dependence

Sai Ma
EE PhD Candidate, CSEE Dept, UMBC

11:30-12:45 Friday 9 September 2011, ITE 231

Due to low invasiveness and high spatial resolution, functional magnetic resonance imaging (fMRI) has become popular in neuroimaging field to determine where activity occurs in brain as a result of performing cognitive tasks or merely being at rest.  One of the most active areas in current fMRI research involves exploring functional connectivity, i.e., statistical interactions, among distributed neural units. Understanding connectivity elucidates how functional systems process information in brain. More interestingly, disorganized connectivity has shown to be related to various kinds of mental disorder.

Data-driven methods, especially independent component analysis (ICA), have been successfully applied to fMRI data analysis and provided an opportunity to study brain functional connectivity on a network, hence multivariate scale. However, independence is a strong assumption which is not necessarily nor typically satisfied in real applications. For this reason, dependent component analysis (DCA) has emerged to generalize ICA by grouping components into independent subsets while within subset dependence is allowed.

Based on ICA and motivated by DCA, we aim to develop effective and efficient analysis schemes to extract, characterize, and quantify network connectivity pattern in fMRI data. We define functional network connectivity as spatial dependence among ICA-derived components, instead of second-order temporal correlation between time courses, to capture high-order statistics. According to this definition, we present our work on the study of network connectivity by several data-driven methods, including ICA, DCA, hierarchical clustering, hypothesis testing, and graph theoretical analysis.

seminar Host: Prof. Joel M. Morris

Ph.D. Dissertation Proposal

Citizen Science on the Social and Semantic Web

Joel Sachs

9:00-11:00am Friday 9 September 2011

Room 325b, ITE Building, UMBC

A question faced by semantic web developers is how much explicit semantics to include in their ontologies. A typical answer is that it depends on the use case, since different use cases demand different thicknesses for the semantic layer. This suggest several questions, including: What types of patterns in the rdf graph make a semantic layer "thick" or "thin"? What does it mean for an ontology to support a use case? and Can we create ontologies that support multiple use cases, in situations where those use cases have conflicting ontology-design requirements?

I explore these questions in the domains of biodiversity informatics and citizen science, and propose to evaluate the extent to which a variety of social and semantic computing use cases can be supported within a common ontological framework. Broadly speaking, these use cases involve social computing mechanisms for publishing ecological observations on the semantic web, with the goal of integrating them with other sources of biodiversity and biocomplextity data (range maps, food webs, evolutionary and taxanomic trees; conservation and invasiveness status, etc.). My hypothesis is that relatively flat and minimally constrained representations are not only sufficient, but often necessary to enable integration with other biodiversity resources on the Semantic Web.

I also explore the related issue of establishing working relationships between expert-engineered ontologies and tag-based folksonomies. I seek to demonstrate that, in many cases, the types of ontologies that are well-suited for biodiversity data integration are also well-suited to tag-driven evolution.

Committee

• Tim Finin (chair)
• Anupam Joshi
• Tim Oates
• Cynthia Parr
• Yelena Yesha
• Laura Zavala

Professor Marie desJardins receied a three year grant from NSF's Robust Intelligence program to develop techniques that will permit a computer or robot to learn from examples to carry out multipart tasks specified in natural language on behalf of a user. The project, Teaching Computers to Follow Verbal Instructions, is part of a collaborative effort with Rutgers University.

The goal of the work is develop technology for an improved ability for human users to interact with intelligent agents, the incorporation of novel AI research insights and activities into education and outreach activities, and the development of resources for the AI educator community. In addition to permitting intelligent agents to be developed and trained in the future for a broad range of complex application domains, the interactive agents that we will develop will be used for outreach and student learning.

Microsoft will be on campus to meet with undergraduate and graduate students interested in internship and full-time positions in the Seattle area. Interested students should come to the the Skylight Room in the Commons between 6:30 and 7:30pm on Tuesday September 6.

There are opportunities for Computer Science, Computer Engineering, Electrical Engineering and Information Systems majors and more. Food will be available and also chances to win cool prizes.

If you plan to attend, please RSVP via the Events tab in your UMBCworks account (access myUMBC under the Jobs and Internships topic in myUMBC).

UMBC President Freeman Hrabowski was recently interviewed by The Daily Record on UMBC's educational and research programs in cybersecurity and their importance to the region and nation.

"We anticipate significant growth in this area over the next five years as the nation continues to stand up our cybersecurity resources. In addition, cybersecurity has implications for a broad range of sectors, including healthcare, energy and financial services. These industries have a strong footing in the Maryland economy, so the job outlook is strong, as is the need for innovative technologies to address new and emerging problems. Our ability to prepare a workforce to address cybersecurity challenges makes Maryland a real leader in this area."

The interview is part of a special supplement on cybersecurity and higher education published in August.

Google's Crisis Response team has a Hurricane Irene tracker that overlays Google maps. The application shows the hurricane path along with several additional, customizable layers of data: weather radar, cloud imagery, storm surge probabilities. evacuation routes and shelter sites.

Opportunities in Computational Materials Science

Juana Moreno and Randall Hall

Center for Computation and Technology
Louisiana State University

1:00pm Friday 9 September 2011, ITE 227

The White House Materials Genome Initiative intends to double the speed with which we discover, develop, and manufacture new materials. In order for this initiative to be successful an unprecedented collaboration between computer scientists, applied mathematicians, computational scientists, and engineers with expertise in each of the aspects of the simulation-guided design of modern materials must be established. We must also take advantage of the enormous national investments in the next generation of hyperparallel, heterogeneous, multicore supercomputers to develop experimentally verified algorithms. In this talk I will describe new collaborative efforts in Louisiana towards developing a State-wise team of scientist to attack the challenges in the design of new materials, and the current opportunities at the undergraduate and graduate level.

Dr. Juana Moreno is an Assistant Professor in the Department of Physics and Astronomy at LSU. She received her Ph.D. in condensed matter physics from Rutgers University and was faculty at the University of North Dakota before joining CCT. Her research focuses on modeling, using a variety of computational tools, the transport and magnetic properties of correlated electron systems, including diluted magnetic semiconductors, heavy fermion compounds and low-dimensional systems.

Dr. Randall Hall received his B.S. in Chemistry from UC Berkeley and his PhD in Chemistry with Bruce Berne from Columbia University. He was a postdoctoral associate with Peter Wolynes at the University of Illinois, Urbana-Champaign. He joined the faculty at LSU in 1986. He is currently the Webster Parish Chapter Alumni Professor at LSU. He is a co-PI of the Louisiana Alliance for Simulation-Guided Materials Appliations (LA-SiGMA).

Host: Yelena Yesha

The CSEE department will hold an orientation session for new graduate students in its Computer Engineering, Computer Science and Electrical Engineering programs at 9:00am Thursday August 25 in Lecture Hall 8 (ITE 102). Here is the schedule.

• 09:00-09:30am Registration
• 09:30-09:45am Welcome, CSEE Department Chair Dr. Gary Carter
• 09:45-10:15am Success Strategies, Dr. Tim Finin
• 10:15-10:45am CSEE Computer Accounts, CSEE System Administrator Geoffrey Weiss
• 10:45-11:30am Program specific presentations and discussions
  • Computer Science Program, CS Graduate Program Director Dr. Anupam Joshi (remain in Lecture Hall 8)
  • Electrical Engineering Program, EE Graduate Program Director Dr. Gary Carter (report to ITE 325B conference room)
  • Computer Engineering Program, Dr. Chintan Patel (report to ITE 346 conference room)
• 11:30-12:30pm Pizza lunch (ITE Building, 3rd Floor, outside 325 suite)
• 12:30-1:30pm TA and RA Orientation, Dr. Anupam Joshi, (ITE 325B conference room)