CE21-Maryland Summit raises awareness about need for more women and minority Computer Science majors

Computer Science

posted Thursday, May 16th, 2013

You don’t know until you try.

This is what the leaders behind Computing Education for the 21^st Century (CE21-Maryland) have figured out. Drs. Marie desJardins, Penny Rheingans, and Susan Martin say that removing the mystery and misconceptions surrounding Computer Science is the key to getting more women and minorities to purse careers in the field.

Historically, Computer Science has been dominated by white males. Just take a look at the numbers. In 2010-11 only 12.7% of computing degrees went to women. A mere 4.6% of Computer Science graduates were African Americans and 6.5% were Hispanics.

It’s not that women and minorities are no good at Computer Science. It’s that they often think they’re no good. When you walk into a classroom and no one looks like you, it’s easy to feel like you don’t belong.

Dr. Marie desJardins, a CSEE professor, gives one part of the explanation for this trend. “Youth gaming culture is really dominating Computer Science majors,” she says. Boys who love video games naturally gravitate to Computer Science in college. Women aren’t typically avid gamers. Instead, they tend to gravitate towards social careers–not something they associate with the field of Computer Science.

Herein lies the problem: most of us don’t know what computer scientists actually do. “There are some iconic careers that we understand,” says CSEE Professor Penny Rheingans. “We know what doctors do. We know what lawyers do. But, nobody knows what Computer Scientists do.”

Only by experiencing the discipline firsthand will kids understand if the field is for them. Take Dr. Rheingans, who was headed down the path to becoming a lawyer when she took a Computer Science class: “And I fell in love,” she says. It was hard and sometimes frustrating, but that challenge got her hooked. “Not enough students have the opportunity to experience that.”

Even if women and minorities want to take Computer Science, they don’t always have the opportunity in high school. Throughout Maryland, inconsistent curriculum and spotty availability has made it hard for students to be introduced to the subject.

Computer Science is not a graduation requirement, nor is it even offered at every Maryland high school. Most schools offer it as an elective like ceramics or woodshop. Since the class doesn’t count for credit, those students– who aren’t otherwise encouraged by parents, or a longstanding love of computers–don’t have much incentive to take it.

Computers are becoming an increasingly ubiquitous part of our lives. As such, Dr. desJardins thinks that Computer Science should be a requirement for high school students. “We make them take Government, Math, Science, and English. But, we don’t make them take Computer Science—but it’s the fastest growing job market of any discipline,” she says. “I think it’s morally wrong that we’re not teaching children how to master this technology.”

In March 2012, Drs. desJardins, Rheingans, and Martin formed CE21-Maryland to get a deeper understanding of the shortcomings of Computer Science education in Maryland, and to help solve this problem. The group is supported by NSF’s Computing Education for the 21^st Century (CE21) program.

Last August, CE21-Maryland held its first mini-summit to raise awareness of these issues among Computer Science high school teachers across the state. The summit successfully helped establish connections among teachers who share this passion for change. “Having a community is absolutely important to helping empower people,” says Dr. Rheingans, who has proven the importance of community first-hand as the director of UMBC’s Center for Women in Technology (CWIT).

On May 17, CE21-Maryland will hold its second Summit for Computing Education. Teachers, administrators, legislators, and industry leaders will gather at UMBC to explore these issues, network, and discuss plans for increasing the number and diversity of students studying Computer Science in our state.

The summit will include a college student panel, where current computing majors will share their journey to becoming Computer Science majors. One session will take a look at the AP CS Principles course, a proposed AP course being developed by the College Board and National Science Foundation, with pilots offered around the country.

Dr. desJardins realizes that recognizing the Computer Science curriculum problem is a lot easier than fixing it. “It’s a chicken or the egg problem,” she says. Regulating Computer Science classes across the state can’t happen until teachers are trained to teach it. Training is not likely to happen unless enrollment increases. CE21-Maryland envisions a two-pronged approach to train teachers and make connections with legislators who can make a difference.

The women behind CE21-Maryland are working hard to change the compostion of Computer Science majors. But, why?

“First of all it’s a numbers problem. Second of all it’s a diversity problem,” explains Dr. Rheingans. By 2018, nearly 40,000 new computing-related jobs will be available in Maryland each year. But, only about 2,000 bachelor’s degrees in computing and information systems are awarded by Maryland institutions annually. Recruiting more women and minorities to the major will help satisfy the huge need for computing majors in the future.

But, perhaps more importantt is the chance to add diversity to the next generation of technological problem-solvers. “Different perspectives leads you to stronger, more robust solutions,” she says.

PhD proposal: A Semantic Resolution Framework for Manufacturing Capability Data Integration

posted Monday, May 13th, 2013

Ph.D. Dissertation Proposal

A Semantic Resolution Framework for
Manufacturing Capability Data Integration

10:30am Tuesday, May 14, 2013, ITE 346, UMBC

Yan Kang

Building flexible manufacturing supply chains requires interoperable and accurate manufacturing service capability (MSC) information of all supply chain participants. Today, MSC information, which is typically published either on the supplier’s web site or registered at an e-marketplace portal, has been shown to fall short of the interoperability and accuracy requirements. This issue can be addressed by annotating the MSC information using shared ontologies. However, ontology-based approaches face two main challenges: 1) lack of an effective way to transform a large amount of complex MSC information hidden in the web sites of manufacturers into a representation of shared semantics and 2) difficulties in the adoption of ontology-based approaches by the supply chain managers and users because of their unfamiliar of the syntax and semantics of formal ontology languages such as OWL and RDF and the lack of tools friendly for inexperienced users.

The objective of our research is to address the main challenges of ontology-based approaches by developing an innovative approach that can effectively extract a large volume of manufacturing capability instance data, accurately annotate these instance data with semantics and integrate these data under a formal manufacturing domain ontology. To achieve the objective, a Semantic Resolution Framework is proposed to guides every step of the manufacturing capability data integration process and to resolve semantic heterogeneity with minimal human supervision. The key innovations of this framework includes 1) three assisting systems, including a Triple Store Extractor, a Triple Store to Ontology Mapper and a Ontology-based Extensible Dynamic Form, that can efficiently and effectively perform the automatic processes of extracting, annotating and integrating manufacturing capability data.; 2) a Semantic Resolution Knowledge Base (SR-KB) that incrementally filled with, among other things, rules/patterns learned from errors. This SR-KB together with an Upper Manufacturing Domain Ontology (UMO) provide knowledge for resolving semantic differences in the integration process; 3) an evolution mechanism that enables SR-KB to continuously improve itself and gradually reduce the human involvement by learning from mistakes.

Committee: Yun Peng (chair), Charles Nicholas, Tim Finin, Yaacov Yesha, Boonserm Kulvatunyou (NIST)

PhD proposal: Training Neural Networks and Recurrent Deep Learning Machines

posted Friday, May 10th, 2013

Ph.D. Dissertation Proposal

Convexification/Deconvexification for Training Neural

Networks and Recurrent Deep Learning Machines

Yichuan Gui

9:30am Thursday, 16 May 2013, ITE 325b, UMBC

The development of artificial neural networks (ANNs) has been impeded by the local minimum problem for decades. One principle goal of this proposal focuses on devel- oping a methodology to alleviate the local minimum problem in training ANNs. A new training criterion called the normalized risk-averting error (NRAE) criterion is proposed to avoid nonglobal local minima in training multilayer perceptrons (MLPs) and deep learning machines (DLMs). Training methods based on the NRAE crite- rion are developed to achieve global or near-global minima with satisfactory learning errors and generalization capabilities.

Many advantages of DLMs have been analyzed in recent research works of ANNs, and effective architectures and training methods have been explored from those works. However, feedback structures are commonly ignored in previous research of DLMs. The next objective of this proposal is to develop recurrent deep learning machines (RDLMs) through adding feedback structures to deep architectures in DLMs. De- signing and testing works are expected to illustrate the efficiency and effectiveness of RDLMs with feedback structures comparing to feedforward DLMs.

Preliminary works presented in this proposal demonstrate the effectiveness of NRAE-based training methods in avoid nonglobal local minima for training MLPs. Methods based on the NRAE criterion will be tested in training DLMs, and the de- veloping and testing of RDLMs will be performed in subsequent works. Moreover, an approach that combining both the NRAE criterion and RDLMs will also be explored to minimize the training error and maximize the generalization capability. Contribu- tions of this proposed research are expected as (1) provide an effective way to avoid local minimum problem in training MLPs and DLMs with satisfactory performance; (2) develop a new type of RDLMs with feedback connections for training large-scale dataset efficiently; (3) apply the NRAE criterion to train RDLMs for minimizing training errors and maximizing generalization capabilities. Those contributions are expected to significantly boost research interests in ANNs' fields and stimulate new practical applications in the future.

Committee: James Lo (mentor), Yun Peng (mentor), Tim Finin, Tim Oates, Charles Nicholas

MS defense: Social Media Analytics: Digital Footprints, 5/13

posted Wednesday, May 8th, 2013

MS Defense

Social Media Analytics: Digital Footprints

Sandhya Krishnan

9:00am Monday, 13 May 2013, ITE325b

In this work we describe an approach to distinguish real and impostor/ compromised accounts on social media. Compromising a user's social media account is not only a breach of security, but can also lead to dissemination of misinformation at a fast pace on social media. There have been several such high profile attacks recently, including on Twitter feeds of AP, CBS, and Delta Airlines. A fake account for the Prime Minister's Office in India was used to spread malicious rumors last year. Our approach builds a profile or footprint of users using both the content of their tweets and the structure of their network. We analyze the real time content of users (Tweets, Facebook posts, etc.) and compare them with information about the user from reliable sources on the Web (e.g., newspapers, news channels, etc.) in order to compute a similarity metric between content from the two sources. We also compute a metric based on the social network analysis of the users: who connects to them, who they are connected with, and how central they are in their network. We have shown how such an approach can easily detect fake accounts for not just well known people such as President Obama, but also for lesser known people and organizations. We also show promising initial results on how this approach can be used to detect an account which has been hacked.

Committee: Anupam Joshi (chair), Tim Finin, Tim Oates, Ponnurangam Kumaraguru (IIIT Delhi)

Mobile computing class demos and posters, 5/14

posted Wednesday, May 8th, 2013

mobile_user

Professor Nilanjan Banerjee's Introduction to Mobile Computing class will hold a poster and demonstration session showcasing student class projects from 12:30 to 2:00 on Tuesday, May 14 in room 210 of the ITE building. The projects inlcude mobile apps, games, and systems that have built during the semester. Pizza will be served.

The course was partially sponsored this year by Microsoft Research's Hawaii Initiative, which provided students with hardware and access to cloud services for storage, computing and data.

Anyone who is interested in mobile technology is welcome to attend and intereact with Professor Banerjee and the students, who include both upper-level undergraduates and graduate students. See the event flyer for more information.

Here are the systems that will be demonstrated:

Food Life-cycle Manager: Reduce food waste, Save your money
Home Guard: The easiest way to protect your home from anywhere without compromise
JUMP: Keep Jumping up
DIY Picture Dictionary: making learning Fun Multiple Places Near you Trackit: Anytime anywhere
SpotOrNot: A crowdsourced parking app for UMBC
Build-A-Bill: An easy to use bill splitting app (even after you've had a few drinks)
Pocket Philosopher: What would YOU do?
Golf score browser
Math Path
Community: Share whats on your mind
System Android Powered Telepresence: Accessible and Low-cost Telepresence with Android
Beat Box: tap and mix your musical mind
PillNote: Capturing user's interaction with medication
YASLA (Yet Another Shopping List App): app that saves the day by saving your lists and suggesting stores.

For more information, contact Prof. Banerjee at nilanb at umbc.edu.

PhD proposal: Rapidly Deployable Image Classification System Using Multi-Views

posted Tuesday, May 7th, 2013

rosebrock

Ph.D. Dissertation Proposal

A Rapidly Deployable Image
Classification System Using Multi-Views

Adrian Rosebrock

11:00am Friday, 10 May, ITE 325, UMBC

Constructing an image classification system using strong, local invariant descriptors is time consuming and tedious, requiring many experimentations and parameter tuning to obtain an adequately performing model. Furthermore, training a system in a given domain and then migrating the model to a separate domain will likely yield poor performance. As computer vision systems become more prevalent in the academic, government, and private sectors, it is paramount that a framework to more easily construct these classification systems be created. In this work we present a rapidly deployable image classification system using multi-views, where each view consists of a set of weak global features. These weak global descriptors are computationally simple to extract, intuitive to understand, and require substantially less parameter tuning than their local invariant counterparts. We demonstrate that by combining weak features with ensemble methods we are able to outperform the current state-of-the-art methods or achieve comparable accuracy. Finally, we provide a theoretical justification for our ensemble framework that can be used to construct rapidly deployable image classification systems called "Ecosembles".

Committee: Dr. Tim Oates (chair), Dr. Jesus Caban, Dr. Tim Finin, Dr. Charles Nicholas

Research papers sought the UMBC Review, vol. 15

posted Sunday, April 28th, 2013

The UMBC Review is a journal for undergraduate research done at UMBC. CMSC and CMPE majors who have recently finished a research project or paper or plan to do so before the fall should consider submitting it for volume 15, which will be published next April. The Review publishes papers in all disciplines, including the computing sciences.

Papers may be submitted at any time between now and 13 September 2013 for consideration in the next volume. Students graduating this spring or summer are eligible to submit papers on work completed as an undergraduate. See the table of contents of the current issue to get an idea of the range and length of published papers.

If you are interested, fill out this online form to get additional information.

MS defense: Modeling Individual Nodes in Dynamic Link Prediction

posted Tuesday, April 23rd, 2013

MS Defense

Modeling Individual Nodes In Dynamic Link Prediction

Maksym Morawski

2:00pm Thursday, 25 April 2013, ITE325b, UMBC

The question of how to predict which links will form in a graph, given the graph’s history, is an open research problem in computer science. There are many different approaches to the link prediction problem, one of which involves building a set of features for pairs of nodes and using supervised learning to build a model that predicts when these pairs of nodes will link. Typically, this model is learned over the entire graph. In this thesis, I investigate building this model over each individual node in an attempt to learn the particular ways in which that node behaves before making predictions about it. In addition, research into link prediction to date lacks intelligent ways of utilizing the graph over large timespans. To address this, I introduce a variety of ways to include temporality into the link prediction process by introducing new ways of using existing features.

Committee: Dr. Marie desJardins (Chair), Dr. Tim Oates, Dr. Tim Finin

MS defense: A Hybrid CPU/GPU Pipeline Workflow System

posted Sunday, April 21st, 2013

MS Thesis Defense

A Hybrid CPU/GPU Pipeline Workflow System

Tim Blattner

11:45am Thurday, 25 April 2013, ITE 325b, UMBC

Heterogeneous architectures can be problematic to program on, particularly when trying to schedule tasks on all available compute resources, overlapping PCI express transfers, and managing the limited memory available on the architectures. In this thesis we propose a workflow system that is capable of scheduling on all available compute resources, overlaps PCI express transfers, and manages the limited memory. A procedure for creating the workflow system is described and two case studies are analyzed.

Image Stitching, which implements the workflow system and achieves two orders of magnitude speedup over an image stitching plugin found in the popular Fiji ImageJ application. Implementing the image stitching algorithm without the workflow system yielded only one order of magnitude speedup over the image stitching plugin.
Out of Core LU Decomposition, which does not implement the workflow system. This case study demonstrates the impact of the PCI express on a problem with a large number of dependencies. A proposed workflow system for this algorithm is provided in Future Work.

Using the workflow system, programmers have a method for scheduling any algorithm on all available compute resources and is capable of hiding the I/O impact by overlapping computation with I/O.

Committee Members: Milton Halem, Yelena Yesha, Shujia Zhou, John Dorband, Walid Keyrouz

CMSC town hall meeting, 12-2pm Thur 4/18, ITE456

posted Friday, April 12th, 2013

students

The CSEE Department will hold a "town hall" meeting for undergraduate COmputer Science (CMSC) majors, minors and other interested students in ITE 456 from 12:00 to 2:00 on Thursday, April 18.

This is an opportunity to interact with your department chair, Professor Gary Carter, the CMSC undergraduate program director Professor Marc Olano and other faculty members. During the meeting you will hear about recent developments in the department and CMSC program, and have opportunities to express opinions, raise issues, make suggestions, ask questions and discuss how to make the CMSC program better. There will also be pizza and drinks.

If you plan on attending, please send an email message to so we can be sure to order enough food. If you have any questions or topics that you would like to raise in advance, send them to We look forward to a lively and useful event where the communication flows both ways.

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