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