Demos: Introduction to mobile computing and
systems for smart home automation

12:30-2:00 Monday, 12 May 2014, 3rd floor corridor, ITE Building

The students in Professor Banerjee’s Introduction to Mobile Computing and Systems for Smart Home Automation classes will showcase their cutting edge projects and application that use mobile phones, tablets, cloud services, and smarthome sensors.

Come and enjoy the demonstrations that range from cool smartphone games to smartphone-based educational tools to smartphone-controlled robots to location-based mobile phone services to voice and mind controlled home appliances.

The demonstrations will take place from 12:30 to 2:00pm on Monday, May 12 in the central corridor of the third floor of the ITE building at UMBC.

For more information, contact Dr. Nilanjan Banerjee ()

MS Thesis Defense

Recoloring Web Pages For Color Vision Deficiency Users

Vikas Bansal

11:00am Thursday, May 8, 2014, ITE346, UMBC

Color vision begins with the activation cone cells. When one of the cone cells dysfunction, color vision deficiency (CVD) ensues. Due to CVD, users become unable to differentiate as many colors a normal person can. Lack of this ability results in less rich web experience, incomprehension of basic information and thus frustration. Solutions such as carefully choosing colors while designing or recolor web pages for CVD users exist. We first present the improvement in the time complexity of an existing tool SPRWeb to recolor web pages. After that we present our tool which explores the foreground-background relationship between colors in a web page. Using this relationship we propose an algorithm which preserves naturalness, pair-differentiability and subjectivity. In the last part, we add an additional step in to algorithm to ensure that the contrast in the parsed color pairs meets the required W3C guidelines. In evaluation, we found that our algorithm does significantly better in preserving pair-differentiability and produces lower total cost solutions than SPRWeb. Quantitative experimentation of modified algorithm shows that contrast ratio in each replacement pair is more than 4.5 as required for readability.

Committee: Drs. Lina Zhou (co-chair), Tim Finin (ch-chair), Yelena Yesha, Dongsong Zhang

UMBC Information Systems Security Association Seminar

Framework for Improving Critical
Infrastructure in Cybersecurity

Dr. Ron Ross, NIST

6:00-8:00pm Wednesday, 30 April 20014
Meyerhoff 030 Building Lecture Hall 2

RSVP
Schedule:
6:00-6:30pm Introductions to UMBC ISSA, Networking & Pizza
6:30-7:30pm Cyber Security Lecture From Dr. Ron Ross
7:30-8:00pm Networking

Host: Monique Jeffrey, UMBC ISSA President,

Ron Ross is a Fellow at the National Institute of Standards and Technology (NIST). His current areas of specialization include information security and risk management. Dr. Ross leads the Federal Information Security Management Act (FISMA) Implementation Project, which includes the development of security standards and guidelines for the federal government, contractors, and the United States critical information infrastructure.

A graduate of the United States Military Academy at West Point, Dr. Ross served in a variety of leadership and technical positions during his over twenty-year career in the United States Army. While assigned to the National Security Agency, he received the Scientific Achievement Award for his work on an inter-agency national security project and was awarded the Defense Superior Service Medal upon his departure from the agency. Dr. Ross is a three-time recipient of the Federal 100 award for his leadership and technical contributions to critical information security projects affecting the federal government and is a recipient of the Department of Commerce Gold and Silver Medal Awards.

Dr. Ross has been inducted into the Information Systems Security Association (ISSA) Hall of Fame and given its highest honor of ISSA Distinguished Fellow. Dr. Ross has also received several private sector cyber security awards and recognition including the Vanguard ChairmanÕs Award, the Symantec Cyber 7 Award, InformationWeek’s Government CIO 50 Award, Best of GTRA Award, and the ISACA National Capital Area Conyers Award. During his military career, Dr. Ross served as a White House aide and as a senior technical advisor to the Department of the Army. Dr. Ross is a graduate of the Defense Systems Management College and holds Masters and Ph.D. degrees in Computer Science from the U.S. Naval Postgraduate School specializing in artificial intelligence and robotics.

Center for Hybrid Multicore Productivity Research
Distinguished Computational Science Lecture Series

The White House Climate Data Initiative

Eric Letvin
Director, Disaster and Failure Studies
National Security Council

3:00pm Tuesday, 29 April 2014, ITE 456, UMBC

Delivering on the commitment in the President’s Climate Action Plan, the White House recently launched the Climate Data Initiative — a broad effort to leverage the Federal Government’s extensive, freely- available climate-relevant data resources to advance awareness of and preparedness for climate change impacts. This effort will help give communities across America the information and tools they need to plan for current and future climate impacts. Data from NOAA, NASA, the U.S. Geological Survey, the Department of Defense, and other Federal agencies was recently launched on climate.data.gov. Data and innovation challenges issued by public, private, nonprofit, and other organizations can help catalyze new, data-driven solutions that help communities understand and build resilience to climate change. NOAA and NASA recently announced an innovation challenge calling on researchers and developers to create data-driven simulations to help plan for the future and to educate the public about the vulnerability of their own communities to sea level rise and flood events.

Mr. Eric Letvin PE, Esq, is the Director of Hazard Mitigation and Risk Reduction Policy within the National Security Council in the Executive Office of the President. He coordinates the development and effective delivery of mitigation capabilities identified in the National Preparedness Goal, such as threat and hazard identification, risk and disaster resilience assessment, planning, and long-term vulnerability reduction.

When at NIST, Mr. Letvin is the Disaster and Failure Studies Program Director within NIST’s Engineering Laboratory. Mr. Letvin provides national coordination for conducting field data collection studies. He is also responsible for creating and maintaining a repository related to hazard events (earthquakes, hurricanes, tornadoes, windstorms, community-scale fires in the wildland-urban interface, structural fires, storm surge, flood, tsunami) and human-made hazards (accidental, criminal, or terrorist), the performance of the built environment during hazard events, associated emergency response and evacuation procedures.

Before coming to NIST, Mr. Letvin was Leader of Infrastructure Research and Resiliency in the Homeland Security Group of URS. He has participated in numerous post-disaster studies including the bombing of the Murrah Building in Oklahoma City, and Hurricanes Opal, Ike and Katrina. He has assessed over 200 buildings for risk from terrorist threats and natural disasters.

Mr. Letvin holds a bachelor’s and master’s degree in environmental engineering from Syracuse University and received his Juris Doctor from the University of Maryland. He has taught many courses on risk assessments and protection of infrastructure for FEMA/DHS and made related presentations throughout the world over the last ten years.

The NIST National Cybersecurity Center for Excellence (NCCoE) is seeking full- and part-time paid interns from UMBC graduate students studying cybersecurity at the Universities at Shady Grove (USG). The program is part of NCCoE’s ongoing efforts to build and sustain academic partnerships in the Montgomery County region.

The NCCoE internship will identify and immerse students in practical cybersecurity experiences at the NCCoE in Rockville, MD. NCCoE’s Cybersecurity Graduate Researchers will work in a state-of-the-art facility with expert cybersecurity practitioners from government and academia, along with engineers from some of the largest and most influential IT and cybersecurity companies in the world, including Intel, Microsoft, Symantec, HP, Cisco, Splunk, Palo Alto Networks, and Hytrust.

During their internships, NCCoE’s Graduate Cybersecurity Researchers may assist NCCoE staff and contractors in areas such as:

the design and building of cybersecurity reference designs to demonstrate platform capabilities that address one or more challenges identified by industry.

mentoring undergraduate cybersecurity researchers and helping build teams to work on research projects.

working with NCCoE industry partners and collaborators to identify relevant commercially available technologies that can serve as a component of these reference designs.

supporting the NCCoE lab infrastructure, including the provisioning of hardware, creation and management of both virtual and physical equipment, and the installation and configuration of cybersecurity tools and components.

These NCCoE internships are open to UMBC cybersecurity students enrolled at the USG campus who are US citizens. The deadline for Summer 2014 consideration is Monday, May 5, however internships are available during the 2014-15 academic year as well.

For more information and/or to apply, please contact the USG Career & Internship Services Center at 301-738-6338 or .

Translational Bioinformatics Approaches to Evaluate
and Implement Genomic Medicine Programs

Dr. Casey Overby, Assistant Professor

Program for Personalized and Genomic Medicine
University of Maryland – Baltimore

1:00pm Friday, 25 April 2014, ITE 325b, UMBC

There is a growing evidence base to support the use of many genomic applications in healthcare. There are, however, several barriers to healthcare providers making use of genomic data and information on a routine basis. In this talk, I will describe some of our challenges and successes with implementing genomic medicine programs within the Program for Personalized and Genomic Medicine at UMB, introduce one way to conceptualize translational research and translational bioinformatics in this context, describe a proposed model for evaluating and implementing genomic medicine programs, and describe some of my current and planned research in translational bioinformatics.

Casey L. Overby is an Assistant Professor of Medicine in the Program for Personalized and Genomic Medicine and the Center for Health-related Informatics and Bio-Imaging at the University of Maryland School of Medicine. She received her Masters of Biotechnology from the University of Pennsylvania in 2006, her PhD in Biomedical and Health Informatics and a Graduate Certificate in Public Health Genetics from the University of Washington in 2011. In 2013, she completed her post-doctoral training in the Department of Biomedical Informatics at Columbia University and started her position at University of Maryland, Baltimore.

Host: Marie desJardins,

ACTIVE Center Open House

4:00-5:00pm Monday, 28 April 2014 in ENGR 231

The ACTIVE Center (Engineering 231) is a new classroom that was created by the CSEE Department with support from the Hrabowski Fund for Innovation, BAE Systems, and Northrup Grumman. The ACTIVE Center is designed to facilitate active student learning and laptop-based laboratory activities, and features movable furniture and whiteboards, a smart projector, and flat-panel displays around the room. We are also developing and documenting a “virtual environment” for the classroom, by creating “design patterns” for how computing technology can be used in this type of space to facilitate student learning.

The classroom came online in February 2014, and four pilot courses are currently being offered in the space. On Monday, April 28, we will hold an open house and presentation in the ACTIVE Center to show the campus community how an intentionally designed classroom space can increase student engagement and improve learning outcomes. The open house will include a presentation by Dr. Marie desJardins, a Hrabowski Academic Innovation Fellow and lead PI for the ACTIVE Center project, and a Q&A session with instructors and students who are currently teaching and learning in the ACTIVE Center. We will share best practices for developing and using similar teaching spaces, and will present the current policy for requesting to use the space for future classes.

Please note that no food or drink (other than covered containers of water) are permitted in the ACTIVE Center, but light refreshments will be provided in the hallway following the presentation.

Capacity is limited, so please RSVP. For more information, contact Marie desJardins ().

Dissertation Defense

Feature Extraction and Fusion for Supervised and Semi-supervised
Classification: Application to fMRI and LTM Data

Wei Du

2:00pm Thursday, 24 April 2014, ITE 325B

Extracting powerful features from high dimensional noisy data promises to significantly improve the effectiveness of further analysis, especially of classification. Since there is no single feature selection and extraction method or classifier that works best on all given problems, developing effective and efficient feature selection and extraction methods and classifiers for specific applications has became one of the most active areas in the machine learning field. The aim of this dissertation is to develop novel data-driven methods for extracting and selecting the most distinguishing features for performing classification using functional magnetic resonance imaging (fMRI) and laser tread mapping (LTM) tire data.

FMRI data have the potential to characterize and classify various brain disorders including schizophrenia. However, the high dimensionality and unknown nature of fMRI data present numerous challenges to accurate analysis and interpretation. Independent component analysis (ICA), as a data-driven method, has proven very useful for fMRI analysis in extracting spatial components as multivariate features used in classification, and more recently, for the analysis of fMRI data in its native complex-valued form. In this dissertation, we first present a novel framework to extract powerful features from components estimated by ICA, allowing us to remove the redundancy and retain the most discriminative activation patterns from multivariate ICA features. We apply the proposed three-phase feature extraction framework to two real-valued fMRI data sets, and achieve high classification rates in discriminating healthy controls from patients with schizophrenia. Second, due to the iterative nature of ICA algorithms, typically independent components (ICs) are not estimated consistently during different ICA runs, and hence it is not clear which result to use further. We present a statistical framework that utilizes an objective criterion to select the best of multiple ICA runs such that the multivariate ICA features from the best run can be used for further analysis and inference. Using the proposed framework, we study the performance of a novel complex ICA algorithm for fMRI analysis, entropy rate bound minimization, which takes all three types of diversity into account, including non-Gaussianity, sample dependence and noncircularity that are present in the complex-valued fMRI data. We show that CERBM leads to significant improvement in ICs that provide higher classification accuracy, and thus is a promising ICA algorithm for the analysis of complex-valued fMRI data.

Classification using LTM data is another problem we address where we first study the use of highly multivariate solutions such as ICA and then note the advantages using lower-level features for classification. In this case, an important problem is the selection of best set of features for the best classification performance. Additionally, there are a large amount of unlabeled tire data that are easy to collect but only a few of them can be easily labeled by expert. In this dissertation, we propose a novel mutual information (MI) based approach to achieve feature splits for co-training, a practical and powerful data-driven method in semi-supervised learning. Inspired by the idea of dependent component analysis, the proposed MI-based approach presents feature splits that are maximally independent between- or within- subsets, and thus selects and fuses features more effectively than other feature split methods. Experimental results on both simulated study and LTM tire data indicate that co-training with MI-based feature splits yields significantly higher accuracy than supervised classification.

Committee: Profs. Tulay Adali (Chair), Joel Morris, Janet Rutledge, Charles E. Laberge, Vince D. Calhoun (University of New Mexico and the Mind Research Network), and Dr. Matthew Anderson (Northrop Grumman Corp.)

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Nidhi Mittal, a 2013 graduate of UMBC’s Cybersecurity Master’s in Professional Studies program talks about her experience. In this video Ms. Mital talks about the value of the cybersecurity program’s instructors, who bring with them a wealth of experience in the public and private sector. 

UMBC offers a variety of master’s degree and certificate options. Our cybersecurity graduate programs leverage a student’s experience toward a range of opportunities within the cybersecurity profession. UMBC’s in-person cybersecurity programs are designed to prepare computer science, information systems, and other experienced professionals to fill management and leadership roles in cybersecurity and cyber operations.

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CSEE’s Jane Gethmann, Assistant to the Chair, received UMBC’s inaugural Karen L. Wensch Endowment Award for Outstanding Non-Exempt Staff earlier this month. She has played a leadership role in our Department since she joined it in 1997 and has been a key staff member for the thousands of faculty, staff and students who have been part of our department in the past 17 years.

The following is the citation for her well deserved award.

Jane Gethmann first came to UMBC in 1971, and over the years has worked in Financial Aid, the Department of Biological Sciences, and the Graduate School. She joined the Department of Computer Science and Electrical Engineering in 1997, and is known as the glue that holds the department together, going above and beyond her responsibilities.

In addition to assisting the chair and handling administrative and financial duties, Gethmann also takes the lead when additional resources are needed or when she sees a way to increase efficiency in the department. She has served as facilities manager and scheduling coordinator, managed the Computer Science Help Center, coordinated part-time faculty hiring, and created a graduate admissions database. She also managed the installation of a new teaching laboratory, working with faculty and Facilities Management in order to get it up and running by the start of the semester.

A leader and trusted advisor, Gethmann’s vast knowledge of UMBC and departmental procedures as well as her excellent judgment make her invaluable to those she serves. She is a dedicated people person with a helpful and positive attitude. Whether working with faculty, staff, students, or visitors, her goal is to help people solve whatever problem they are facing, and ensure that they have what they need.

Jane plans to retire at the end of this academic year. We will miss her and all that that she has done for UMBC and our department.