Department of Computer Science and Electrical Engineering

UMBC Sophomore Blossom Metevier (CS ‘15) will be a panelist at Fueling the Future: Celebrating Computer Science Education Week and Computer Science in K-12 Classrooms and Policy, a briefing in Capitol Hill that’s part of Computer Science Education Week (CSEdWeek). Ceremonially celebrated during the birthday week of computer science pioneer Grace Hopper (December 9-15), CSEdWeek's goal is to share the message that computing and computer science education are essential.

Organized by the Computing in the Core Coalition and sponsored by the congressional STEM Education Caucus, Fueling the Future will give congressional staff and STEM education stakeholders an overview of the state and prospects of K-12 computer science education. Specifically, the fact that Computer Science is not taught in the majority of American high schools and how that needs to change.

Blossom joins panelists CSEdWEek co-chair Ruthe Farmer, Director of Strategic Initiates for the National Center for Women and Information Technology, technology writer Douglas Rushkoff, Alison Derbenwick Miller from Oracle, and Brenda Wilkerson from the Chicago Public Schools. Representative Dan Lipinski (D- IL), co-chair of the House STEM Education Caucus, will kick off the event with opening remarks.

Blossom will share her journey to becoming a Computer Science major. It started after she unexpectedly fell in love with programming during her Introduction to Computer Science class during her freshman year at UMBC. She will talk about why she chose the major and her future goals in the field. A Meyerhoff Scholar and member of UMBC's track team, Blossom plans on doing data visualization research in Dr. Jian Chen's lab this winter.

UMBC CSEE Colloquium

Energy Efficient Platforms for
High Performance and Embedded Computing

Dr. Tinoosh Mohsenin
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

1:00pm Friday, 7 December 2012, ITE 227, UMBC

Future embedded, high performance, and cloud computing must meet limited energy capacity, cost, and sustainability. These devices will regularly execute over one tera-operations per second (TOPS) with a variety of diverse workloads—from baseband communications to wearable medical devices—while operating on a 5 to 25 Watt-hour cellphone/tablet battery. The need for greater energy efficiency, smaller size and improved performance of these devices demands a co-optimization of algorithms, architectures, and implementations. This talk presents several programmable and application specific solutions that illustrate the cross-domain optimization.

The design of system-on-Chip blocks becomes increasingly sophisticated with emerging real-time computational and limited power budget requirements. Two such algorithms, Low Density Parity Check (LDPC) decoding and Compressive Sensing (CS), have received significant attention. LDPC decoding is an error correction technique which has shown superior error correction performance and has been adopted by several recent communication standards. Compressive sensing is a revolutionary technique which significantly reduces the amount of data collected during acquisition. While both LDPC decoding and compressive sampling have several advantages, they require high computational intensive algorithms which typically suffer from high power consumption and low clock rates. We present novel algorithms and architectures to address these challenges.

As future systems demand increasing flexibility and performance within a limited power budget, many-core chip architectures have become a promising solution. The design and implementation of a programmable many-core platform containing 64 cores routed in a hierarchical network is presented. For demonstration, Electroencephalogram (EEG) seizure detection and analysis and ultrasound spectral doppler are mapped onto the cores. The seizure detection and analysis takes 900 ns and consumes 240 nJ of energy. Spectral doppler takes 715 ns and consumes 182 nJ of energy. The prototype is implemented in 65 nm CMOS which contains 64 cores, occupies 19.51 mm2 and runs at 1.18 GHz at 1 V.

Dr. Tinoosh Mohsenin is an assistant professor in the Department of Computer Science and Electrical Engineering at the University of Maryland Baltimore County since 2011. Prior to joining UMBC, she was finishing her PhD at the University of California, Davis. Dr. Mohsenin’s research interests lie in the areas of high performance and energy-efficiency in programmable and special purpose processors. She is the director of Energy Efficient High Performance Computing (EEHPC) Lab where she leads projects in architecture, hardware, software tools, and applications for VLSI computation with an emphasis on digital signal processing workloads. She has been consultant to early stage technology companies and currently serves in the Technical Program Committees of the IEEE Biomedical Circuits & Systems Conference (BioCAS), Life Science Systems and Applications Workshop (LiSSA), International Symposium on Quality Electronic Design (ISQED) and IEEE Women in Circuits and Systems (WiCAS).

More information and directions: http://bit.ly/UMBCtalks

Center for Hybrid Multicore Productivity Research (CHMPR)
Distinguished Computational Science Lecture Series

Parallel Real-Time OLAP on Multi-Core Processors

Frank Dehne
Chancellor's Professor of Computer Science
Carleton University, Ottawa, Canada
http://www.dehne.net

3:00 p.m. Thursday, 6 December 2012, ITE 456, UMBC

One of the most powerful and prominent technologies for knowledge discovery in Decision Support systems is On-line Analytical Processing (OLAP). Most of the traditional OLAP research, and most of the commercial systems, follow the static data cube approach proposed by Gray etal. and materialize all or a subset of the cuboids of the data cube in order to ensure adequate query performance. Practitioners have called for some time for a real-time OLAP approach where the OLAP system gets updated instantaneously as new data arrives and always provides an up-to-date data warehouse for the decision support process. However, major problems for real-time OLAP are significant performance issues with large scale data warehouses. The aim of our research is to address these problems through the use of efficient parallel computing methods. We present a parallel real-time OLAP system for multi-core processors. To our knowledge, this is the first real-time OLAP system that has been parallelized and optimized for contemporary multi-core processors, providing the opportunity for real-time OLAP on large scale data warehouses. Our system allows for multiple insert and multiple query operations (transactions) to be executed in parallel and in real-time. We evaluated our method for a multitude of scenarios (different ratios of insert and query transactions, query transactions with different sizes of results, different system loads, etc.), using the TPC-DS “Decision Support” benchmark data set. The tests demonstrate that our parallel system achieves a significant speedup in transaction response time and a significant increase in transaction throughput. Since hardware performance improvements are currently achieved not by faster processors but by increasing the number of processor cores, our new parallel real-time OLAP method has the potential to enable OLAP systems that are real-time and efficient/feasible for large databases.

The new UMBC Cyber Scholars Program is seeking applicants. Incoming Freshman for the Fall 2013 school year, current students, and transfer students interested in careers in cybersecurity are encouraged to apply by January 15, 2013.

Starting Fall 2013, the Scholarship program will support 15-20 students annually with financial awards of $5,000-15,000 per year. The scholarship is more than a financial award; it is a scholarship program that fosters a community through common on-campus living-learning housing, events, and activities. Cyber Scholars will learn from and support one another throughout their college careers, and from core interaction with UMBC faculty and mentors.

Every Cyber scholar is assigned a faculty advisor who is pursuing cybersecurity-related research of their own. Advisors will help students find research and internship opportunities best suited to them.

To apply for the UMBC Cyber Scholars Program, visit Cybersecurity.umbc.edu/cyberscholars

MS Thesis Defense

Simultaneous Feature Acquisition and Cost Estimation

Zachary Kurtz

11:00am Thursday, 6 December 2012, ITE 325b

This thesis will address classification problems with two sources of cost: the cost of acquiring feature values and the cost of incorrect classifications. In particular, I address problems with feature costs and instance-dependent misclassification costs. Many real-world applications, such as medical diagnosis, contain both feature acquisition costs and instance-dependent misclassification costs. The goal of my research is to minimize the total cost of classifying an unknown instance. This goal is accomplished with a new approach: Simultaneous Feature Acquisition and Cost Estimation (SFACE), which combines feature acquisition methods with a regression algorithm that estimates misclassification costs. The estimated cost values are used to estimate the expected cost reduction for the acquisition of each feature. SFACE is evaluated by comparing the total cost of operation to the cost incurred by existing cost-insensitive, cost-sensitive, and feature acquisition algorithms. The results show that SFACE results in lower total cost for the tested datasets.

Committee: Dr. Marie desJardins (Chair), Dr. Tim Oates and Dr. Michael Grasso

MS Thesis Defense

Stateless Detection of Malicious Traffic:
Emphasis on User Privacy

Paul Halvorsen

1:00pm Monday, 3 December 2012, ITE 346, UMBC

In order to allow flexibility in deployment location and to preserve user privacy we have performed research into stateless classification of network traffic. Stateless detection allows for flexibility in deployment location because traffic on a network does not necessarily follow the same path to and from the end points. By only requiring a single direction of traffic, we have the ability to deploy this classifier anywhere on a network. We also do not require the data from a packet which preserves user privacy and allows for the classification of encrypted traffic.

Our research shows that it is possible to determine if traffic is malicious by using packets traveling in a single direction and without the data contained in the packet. Our research shows that with the use of the timing of the packets, time to live value, and source and destination IP addresses and ports, it is possible to determine if the traffic is malicious. In this way we are able to deploy the classifier anywhere on a network, preserve user privacy, and classify encrypted traffic.

Committee members:

• Dr. Anupam Joshi (chair)
• Dr. Charles Nicholas
• Dr. Tim Finin

Originally from Montclair, New Jersey, Celia is a Computer Science and Math double-major and CWIT Scholar.

About Celia

When did you become interested in Computer Science? I’ve always been interested in math and solving puzzles since I was a little girl.  In my senior year of high school, I had the opportunity to take two programming classes at a local college.  At the time, I was thinking I might want to create games for women and children.

What area of Computer Science interests you the most? Now I’m thinking about being a data scientist, somebody who makes sense of the large amounts of data that are growing rapidly in so many fields.  I’ll want to take classes in machine learning algorithms, computer graphics, and data visualization. 

What Computer Science courses did you take in high school? I took seven math classes, including AP Calculus BC and statistics.  I realize now that the programming classes I took at the local college weren’t great, but they helped pique my interest in computer science.

What is your dream job? Google and Facebook created the idea of data science and now there are a lot of start-up companies in Silicon Valley that specialize in mining complex data.  Everyone from the NSA to General Electric are now looking for people who can do this, too, and it would be fun to be part of the exciting breakthroughs in this information technology.

About being a CS major

Who is your favorite professor or course? My favorite class is Discrete Structures with Dr. LaBerge. He’s wonderful.  He’s got so many office hours, and he encourages us to come see him.  He never thinks any question is dumb.

Are you part of any on-campus clubs, organizations, teams, or labs?  I’m a member of the Society of Women Engineers, and I’m joining the A-Team, a group who helps the admissions office when prospective students visit. Every Tuesday I have lunch with a group of intellectually challenged students attending UMBC under the new SUCCESS program. I’m also working on my 3^rd degree black belt in Taekwondo. I was on a demonstration team that won a national championship in 2010.

What is the best part about being a CWIT Scholar? I love living in the Center for Women in Technology (CWIT) LLC in Erickson Hall.  We all got to be good friends before school started at a retreat in August.  It’s so much fun, and it’s really helpful, to have friends right there who are studying the same subjects.

About life at UMBC

What is the best part of college so far? Being on my own and away from home.

What is the best part about campus life at UMBC? Hanging out with friends.

What is your favorite spot on campus? The Commons, because it is so full of life.  There is an awesome game room, many dining options, and many SEB events take place there.

Where can you get the best coffee/lunch/ food or beverage of choice? My favorite place to eat is the Admin Café.  I go there with fellow CWIT scholars every weekday morning and get this delicious bacon, egg, and cheese sandwich.  My favorite lunch there is a turkey, lettuce and tomato sandwich on wheat bread with honey mustard and a pickle on the side.  I also love the chicken tenders at the Mesquite BBQ and Grill and the smoothies at Au Bon Pain!

CSEE professor Dr. Alan Sherman and his Ph.D. advisee Josiah Dykstra have been invited to give the keynote address at the Institute for Defense and Government Advancement’s (IDGA) Forensic Enabled Intelligence Summit. Scheduled to be held in Washington D.C. in April 2013, the conference is one of the IDGA’s most anticipated government technology summits of the year.

The keynote will discuss Sherman and Dykstra’s research in cloud forensics. Their work explores ways to conduct forensic exams of crimes  committed in the cloud.

Dr. Oates is a Professor of Computer Science and Electrical Engineering at UMBC. He is the Principal Investigator of UMBC’s Cognition, Robotics, and Learning (CoRaL) Lab, where he pursues research in the broad areas of artificial intelligence, machine learning, robotics, and natural language processing.

Congratulations to Dr. Tim Oates, named an Oros Family Professor in Computer Science and Technology. The five-year endowed professorship will fund Dr. Oates’ newly proposed research project in the area of mobile healthcare.

"I was delighted to recommend Dr. James T. Oates' appointment as Oros Family Professor in Computer Science and Technology, an endowed professorship established to honor and support the work of faculty pursuing scholarly activity in computer science,” says Dr. Warren Devries, Dean of UMBC’s College of Engineering and Information Technology. “Tim Oates is a first rate teacher and scholar, and I had a chance to work with him as a key part of the College and CSEE department's accreditation activity. Taken together this is precisely the type of faculty member this professorship is intended to recognize. The CSEE department's faculty, staff and students are fortunate to have Tim Oates as a mentor and colleague."

The funds will support graduate students to work with Dr. Oates on a project to improve healthcare in developing countries. “The issue is that in developing countries, almost everything is still done on paper,” explains Dr. Oates. That means that every record—things like immunization records and medical histories–are taken by hand. It’s an inefficient process that makes it hard to keep track of medical data.

His proposed solution is to develop an algorithm that can extract data from a cell-phone photo of the paper record. Once digitized, the medical data can be more easily shared and analyzed.

Dr. Oates chose to develop this technology for cell phones because they are a common and reliable tool in these areas, he explains. In many cases, cell phones can be found where basic needs are absent. “There are people living in villages that don’t have access to clean water, but they have cell phones,” he says.

Dr. Oates joins last year’s Oros Family Professor appointee, Dr. Anupam Joshi, who is similarly using the funds for his research in mobile healthcare.

ACM Distinguished Speaker

Cloud based Active Archiving Solution for Databases

Dr. Mukesh Mohania
IBM Research – India

2:30pm Friday, 30 November 2012
Room 102 (LH8), ITE Building, UMBC

In the second talk of the UMBC ACM Student Chapter's Tech Talk Series, ACM Distinguished Speaker Dr. Mukesh Mohania will visit UMBC and talk about "Cloud based Active Archiving Solution for Databases".

Cloud computing offers an exciting opportunity to bring on-demand applications to customers and is being used for delivering hosted services over the Internet and/or processing massive amount of data for business intelligence. In this talk, we will discuss the architecture of cloud computing, MapReduce, and Hadoop. We will then discuss how the cloud infrastructure can be used for data management services, how the massive amount of data can be processed over cloud for various business intelligence applications, and how the cloud can be used for 'Active' Data Archival for near real-time data access. We discuss various issues concerning the active archive system including schema modification, query federation, query optimization, access control and data provenance. Using TPC-DS benchmark data, we present evaluation results that shows the ability of our system to seamlessly query archive data along with data stored in the warehouse in order of minutes compared to hours required to move the data into the warehouse from traditional archival systems.

Mukesh Mohania received his Ph.D. in Computer Science & Engineering from Indian Institute of Technology, Bombay, India in 1995. Currently, he is a Senior Technical Staff Member and IBM Master Inventor in IBM Research – India. He has worked extensively in the areas of distributed databases, data warehousing, data integration, and autonomic computing. He has published more than 120 papers and also filed more than 50 patents in these or related areas, and more than 14 have already been granted. He received the best paper awards in CIKM 2004 and CIKM 2005. His work on Data Quality, Information Integration, and Autonomic Computing has led to the development of new products and also influenced several existing IBM products. He has received several awards within IBM, such as "Excellence in People Management", “Outstanding Innovation Award”, "Technical Accomplishment Award", “Leadership By Doing”, and many more. He also received IEEE Meritorious Service Award. He is an ACM Distinguished Scientist, and a member of IBM Academy of Technology.

Light refreshments will be served after the talk outside ITE-325

RSVP via Facebook https://facebook.com/events/378277722253548/

More information and directions: http://bit.ly/UMBCtalks