Description

Career Peer Advisors assist the Career Services Center in extending career services and information to the UMBC student body.  Students must be able to commit at least one academic year to the following duties and responsibilities: take walk-in appointments, review resumes and cover letters; assist with part-time and full-time job searches including basic interviewing; facilitate workshops/seminars; help market CSC services and programs to UMBC student body; design and present group information meetings upon request to student organizations, residence halls, and other groups; provide general office reception duties; conduct outreach to student organizations and one of three colleges (Engineering and Information Technology, Arts, Humanities and Social Sciences, Natural and Mathematical Sciences); work closely with  CSC staff on special projects as needed.  Training will be provided. Hours:  10-12 per week.

Qualifications

Continuing undergraduate or graduate student with at least a 2.75 GPA; strong interest in helping others and working with students, staff, employers, and faculty; in good academic standing; excellent communication and interpersonal skills; experience with public speaking preferred; ability to use tact and diplomacy in working with others both face to face and on the phone; previous or current involvement in campus organizations or activities; computer literacy and comfort with PowerPoint presentation technology; detail oriented, dependable and reliable; initiative and enthusiasm. All majors invited to apply. Excellent opportunity for undergraduate Social Work, Sociology and Psychology majors considering application to graduate school in the health and counseling professions.

To Apply

Log into your UMBCworks account (http://careers.umbc.edu/students/umbcworks.pdf) and enter job# 9245031 in the keyword box. 

Application deadline is May 9, 2011.

CSEE Ph.D. student Yasaman Haghpanah achieved a Doctoral Consortium hat trick by being invited to participate in upcoming doctoral consortium events at the top three conferences in her research area: IJCAI, AAMAS, and AAAI. Doctoral Consortia have become common in computer science research communities and provide an opportunity for a group of Ph.D. students to discuss and explore their research interests and career objectives with a panel of established, senior researchers in their research area.  Students must apply to participate in a doctoral consortium and the selection process is usually quite competitive. Her dissertation research is developing and evaluating a trust model for supply chain management systems using multi-agent systems techniques. Yasaman is a member of the Maple Laboratory, directed by Professor Marie desJardins.

Yasaman also had a paper accepted to the 2011 Workshop on Agent Mediated Electronic Commerce which is collocated with AAMAS in Taipei. On top of all that, as part of the AAMAS Doctoral Consortium, she will also be spending two months in Rotterdam on an extended stay at Wolf Ketter's Learning Agents Research Group at the Erasmus Research Institute of Management, Erasmus Universiteit Rotterdam.

MS defense

Detection of Unsafe Action in Laparoscopic Cholecystectomy Video

Ashwini Lahane

10:00am Thursday, 28 April 2011, ITE 346

Wellness and healthcare are central to the lives of all people. Information technology has already contributed in significant ways towards enhancement of healthcare delivery and to improving the quality of life. And it will continue to do so with the development of “smarter” technologies and environments. Recent years have seen context awareness as one of the most important aspects in the emerging pervasive computing paradigm. We focus our work on situation awareness; a more holistic variant of context awareness where situations are regarded as logically aggregated contexts. We demonstrate an application of situation aware computing in healthcare. We primarily focus on laparoscopic cholecystectomy, a complex yet commonly performed surgical procedure. The outcome of the surgery is influenced greatly by the training, skill, and judgment of the surgeon. Many surgical simulators have been developed to meet the training and practice needs of the surgeons. However few systems provide feedback during the actual surgery. We present a method to detect a situation, that shows possibility of injury to an artery by analyzing the laparoscopic cholecystectomy surgical video. The system can be used to provide feedback to the operating surgeon in case of a possible risk. We have also built a prototype to demonstrate the use of our system in telemedicine, in the form of a web service.

Thesis Committee:

• Dr. Yelena Yesha (chair)
• Dr. Anupam Joshi
• Dr. Milton Halem
• Dr. Michael Grasso

EE Graduate Seminar

Complex-valued Adaptive Signal Processing:
Applications in Medical Imaging

Prof. Tulay Adali
Machine Learning for Signal Processing Laboratory
CSEE Dept/UMBC

1-2pm Friday, 29 April 2011, ITE 237

Complex-valued signals arise frequently in applications as diverse as communications, radar, geophysics, optics, and biomedicine, as most practical modulation formats are of complex type and applications such as radar and magnetic resonance imaging lead to data that are inherently complex valued. The complex domain, however, presents unique challenges for signal processing, in particular for adaptive nonlinear processing, and as a result, until recently, most algorithms derived for the complex domain have taken engineering shortcuts limiting their usefulness. The most common one among those has been assuming the circularity of the signal, thus ignoring the information conveyed by the phase. Similarly when taking gradients in the complex domain, a "split" approach that performs optimization separately with respect to the real and imaginary variables has been the dominant practice.

There have been important advances in the area within the last decade that clearly demonstrate that noncircularity is an intrinsic characteristic of many signals of practical interest, and when taken into account, the methods developed for their processing may provide significant performance gains. Similarly, it has been shown that using Wirtinger calculus, all calculations can be carried out in a manner similar to real-valued calculus while keeping all the computations in the complex domain.

In this talk, after a brief introduction to optimization using Wirtinger calculus and statistics in the complex domain, and then I will give examples from some of the recent work conducted at the MLSP-Lab.

Professor Gymama Slaughter joined the department as an Assistant Professor in 2010 and established the Bioelectronics Laboratory as a group doing research on Bioelectronics and optimization methods for physical circuit design, low-voltage and biologically inspired computing, sensor-processor integration, and wireless networking and communications. Its current research projects focus on developing sense-and-respond systems for blood metabolites and vital signs as well as volatile organic compounds/gas detection in trauma patients and crowded areas.

Dr. Slaughter has a broad background that makes her uniquely qualified to work in Bioelectronics. She received three degrees from Virginia Commonwealth University: a BS in Chemistry, a MS in Chemical Engineering and a Ph.D in Computer Engineering. Before joining UMBC in August 2010, she was Director of the Center for Biosystems and Engineering and professor of Computer Engineering at Virginia State University.

Visit the new BEL@UMBC Web site to find out more about this new and exciting research group at UMBC.

MS Defense

Exploiting Architectural Techniques for Boosting
Base Station Anonymity in Wireless Sensor Networks

Zhong Ren

2:00pm Thursday, 28 April 2011, ITE 346

Wireless Sensor Networks (WSNs) can be deployed to serve mission-critical applications in hostile environments such as battlefield and territorial borders. In these setups, the WSN may be subject to attacks in order to disrupt the network operation. The most effective way for an adversary to do so is by targeting the Base-Station (BS), where the sensor data are collected in the field. By identifying and locating the BS, the adversary can launch attacks to damage or disrupt the operation of the BS. Therefore, maintaining the BS anonymity is of utmost importance in WSNs.

In this thesis we propose three novel approaches to boost the anonymity of the BS nodes to protect them from potential threats. We first explore the deployment of more BS nodes. We compare the BS anonymity of one versus multiple stationary BS under different network topologies. Our results show that having more base-stations can boost both the average and max anonymity of BS nodes. We further provide guidelines on a cost versus anonymity trade-off to determine the most suitable BS count for a network. Second we exploit the mobility of base-stations and explore the effect of relocating some of the existing BS nodes to the lowest anonymity regions. Our results show that having one mobile BS can dramatically boost the anonymity of the network and moving multiple BS does not provide much value. Finally, we propose to pursue dynamic sensor to cluster re-association to confuse the adversary. This can be employed when base-stations cannot safely move.

Committee members:

• Mohamed Younis (Chair)
• Yun Peng
• Charles Nicholas