This coming weekend, the UMBC chess team will play for the President’s Cup in the Final Four of College Chess. UMBC will compete with chess teams from Webster University, the University of Illinois at Urbana Champaign, and Texas Tech University.

The match has been held each year since 2001 between the top four US schools from the Pan American Intercollegiate Team Chess Championship and the winner is considered the top chess team among U.S. colleges and universities.  UMBC has placed first at the Final Four a record six times.

CSEE Professor Alan Sherman, who is the director of the UMBC chess program, will accompany the team to the match, which will be held at the New York Athletic Club in New York City on Friday through Sunday, April 4-6, 2014. Games will be broadcast live on Monroi.

The UMBC team will consist of:

• Board 1: GM Niclas “The Dark Knight” Huschenbeth (USCF rating 2610)
• Board 2: GM Akshayraj “The Indian Knight” Kore (2519)
• Board 3: M Levan “The Georgian Gangster” Bregadze (2469)
• Board 4: IM and WGM Nazi “The Black Widow” Paikidze (2378)
• Alternate: WGM Sabina “Sunshine” Foisor (2315)

Talking to Robots: Learning to Ground Human
Language in Robotic Perception

Cynthia Matuszek
University of Washington

1:00pm Monday, 7 April 2014, ITE325b, UMBC

Advances in computation, sensing, and hardware are enabling robots to perform an increasing variety of tasks in ever less constrained settings. It is now possible to imagine robots that can operate in traditionally human-centric settings. However, such robots need the flexibility to take instructions and learn about tasks from nonspecialists using language and other natural modalities. At the same time, learning to process natural language about the physical world is difficult without a robot’s sensors and actuators. Combining these areas to create useful robotic systems is a fundamentally multidisciplinary problem, requiring advances in natural language processing, machine learning, robotics, and human-robot interaction. In this talk, I describe my work on learning natural language from end users in a physical context; such language allows a person to communicate their needs in a natural, unscripted way. I demonstrate that this approach can enable a robot to follow directions, learn about novel objects in the world, and perform simple tasks such as navigating an unfamiliar map or putting away objects.

Cynthia Matuszek is a Ph.D. candidate in the University of Washington Computer Science and Engineering department, where she is a member of both the Robotics and State Estimation lab and the Language, Interaction, and Learning group. She earned a B.S. in Computer Science from the University of Texas at Austin, and M.Sc. from the University of Washington. She is published in the areas of artificial intelligence, robotics, ubiquitous computing, and human-robot interaction.

UMBC ACM Student Chapter

Tech Talk: What can a Humanoid Robot Learn?

Professor Tim Oates, UMBC

10:00am-11:00am Friday, 4 April 2014, ITE346

We hope everyone had a fun spring break! We are back with another talk in our UMBC ACM techTalk series. Professor Tim Oates, who is also one of the faculty advisers of the ACM student chapter, will talk about “What can a Humanoid Robot Learn?”. Dr. Oates will split the talk into two sessions. In the first half, he will introduce the topic and talk about current research being pursued in the area of humanoid robots. Whereas, the second half of the talk will be an interactive session focusing on ideating challenges and future research directions. To make the discussion interactive, Dr. Oates encourages you to spend a few minutes beforehand to think about what you would do if you had access to a humanoid robot for research purposes.

Abstract: Robots and AI have a long history together, both in the popular culture and in research.  In this talk I will review some of my past work at the juncture of robotics, AI, and machine learning, as well as ongoing work with collaborators at UMCP along the same lines.  With those collaborators, I wrote a proposal to buy a few humanoid robots that was funded, so I’ll next describe the robots that we’ve bought.  Finally, I’d like to have an open discussion about my ideas for research using these robots, and ideas that those in the audience might have as well.  My goal is to get as many people as is practical involved with the robots, which are relatively expensive and thus not a common resource.  If you’re coming to the talk, spend a few minutes beforehand thinking about what you would do if you had access to a humanoid robot for research purposes.

Dr. Tim Oates is an Oros Familty Professor of Computer Science at the University of Maryland Baltimore County. He received B.S. degrees in Computer Science and Electrical Engineering from North Carolina State University in 1989, and M.S. and Ph.D. degrees from the University of Massachusetts Amherst in 1997 and 2000, respectively. Prior to coming to UMBC in the Fall of 2001, he spent a year as a postdoc in the Artificial Intelligence Lab at the Massachusetts Institute of Technology. In 2004 Dr. Oates won a prestigious NSF CAREER award. He is an author or co-author of more than 100 peer reviewed papers and is a member of the Association for Computing Machinery and the Association for the Advancement of Artificial Intelligence. His research interests include pattern discovery in time series, grammatical inference, graph mining, statistical natural language processing, robotics, and language acquisition.

RSVP for the talk at http://my.umbc.edu/events/23881

Three students in UMBC’s College of Engineering and Information Technology (COEIT) Department of Computer Science and Electrical Engineering (CSEE) have been selected for major scholarships to pursue studies in cybersecurity-related fields under UMBC’s participation in the National Science Foundation’s (NSF) Scholarship for Service (SFS) Federal CyberCorps program. As SFS Scholars, students receive full tuition, fees, annual reimbursement of professional development expenses ($3,000), a nine-month stipend ($20,000 for undergraduates, $25,000 for MS/MPS students, and $30,000 for PhD students) for up to two years (three years for PhD or BS/MS), and assistance with federal cybersecurity internships and career placement. To be eligible for SFS funding, applicants must be full-time students at UMBC committed to cybersecurity-related research and education activities, have an excellent academic record, and not have any significant outside employment obligations.

The first-round awardees for AY14-15 are:

• Anastasia Raffucci, BS (CMPE)
• Jackson Schmandt, Ph.D. (CMPE)
• Brooke Young, BS (CMSC)

These new awardees will join existing UMBC SFS Scholars Oliver Kubik (BS, CMSC), Mary Mathews (PhD, CMSC), Nathan Price, MS (CMPE). Punlada Muangrat BS (IS), Alex Cooke BS (IS), and Denis Danilin MS (IS).

ADDITIONAL SLOTS AVAILABLE! Applications for SFS support for AY14-15 will be accepted through 12PM (noon) on Friday, May 2, 2014 with notice of awards made by May 23, 2014. All levels of study are welcome to apply — however, students must be admitted to (or already enrolled at) UMBC first before applying for SFS. For information about SFS (including application information and instructions) and other US government-related cybersecurity scholarships available, please visit the CISA website.

The CyberCorps program produces highly-qualified professionals to meet the United States government’s increasing need to protect American’s cyber infrastructure. While in the program at UMBC, SFS CyberCorps Scholars participate in special SFS program activities, have opportunities to engage in mentored research opportunities both at UMBC and its partners from industry and government, and must complete a paid summer internship for the federal government. Upon graduation, each student must work for the government (for pay) for one year for each year of scholarship received. CSEE Drs. Alan Sherman and Richard Forno direct the program under a five-year $2.5 million NSF grant received in 2012.

Arduino Workshops from UMBC commonvision on Vimeo

TL;DR: UMBC’s IEEE student branch will hold free weekly workshops on Arduino starting next week. Register at http://bit.ly/OVzA1f.

The Arduino micro-controller is a great device for anyone who wants to learn more about technology. It is used in a variety of fields in research and academia as well as by hobbyists. Arduino can be used for projects ranging from quadcopters to thermal cyclers  and even wearable electronics. Here is more information about the Arduino.

The workshops are intended for ANY student from ANY major and only require a basic understanding of basic programming concepts such as if-statements and loops. The majority of the code will be provided.

The Arduino workshops are offered on a weekly basis at two levels: Level 1 for those new to Arduino and Level 2 for students who have completed Level 1 or have a basic familiarity with Arduino. The Level 1 workshop is offered on Tuesday and Wednesday from 7:00pm to 9:00pm starting the week of April 1st. You may select to participate in either our Tuesday lecture or Wednesday lecture. The Level 2 workshop is only offered on Thursday from 7:00pm to 9:00pm starting the week of April 1st as well. For both workshops, you will need to bring your laptop and you must able to download the Arduino IDE.

Register at http://bit.ly/OVzA1f. Seats are limited. Contact Sekar Kulandaivel () with questions about registration, downloading the IDE, or anything else.

The next Council of Computing Majors (CCM) will be at Noon this Wednesday, March 26th, in Math/Psychology 008. One of our group members, Patrick McElvaney, will give a presentation about a new CCM project: using the Raspberry Pi and photo-receptors to analyze water in the Chesapeake watershed. His talk will provide an overview of the installation of sensing equipment, specific details on how the photo-receptors can differentiate between organic and inorganic compounds, and information on how other students can get involved.

The CCM is a student organization for undergraduate computer science and computer engineering majors as well as other students interested in computing. If you are interested in starting your own project, please come and speak with any of the officers after the meeting.

Underwater Acoustic Communication and
Networking for Ocean Sampling

Dr. Aijun Song

Assistant Research Professor
College of Earth, Ocean, and Environment
University of Delaware, Newark, DE 19716

11:45am – 12:45pm Thursday, 27 March 2014, ITE325b, UMBC

On our planet Earth, the marine ecosystem is undergoing significant changes due to human activities and natural processes. These changes call for enhanced capabilities to sample and communicate in the oceans. With this background, underwater acoustic communication has attracted much attention across multiple disciplines, as a means to access oceanographic data in real-time and to support navigation of underwater vehicles. This talk will focus on my recent efforts in 1) characterization and modeling of the ocean environment as a communication medium, 2) development of high data rate acoustic modems, both software and hardware, and 3) application of underwater acoustic communication networks in ocean sampling.

Dr. Aijun Song received his Ph.D. degree in the Department of Electrical Engineering, University of Delaware, Newark, Delaware in 2005. From 2005 to 2008, he was a postdoctoral research associate at the College of Earth, Ocean, and Environment (CEOE), University of Delaware. During this period, he was also an Office of Naval Research (ONR) postdoctoral fellow, supported by the special research award in the Ocean Acoustics program. Since 2008, he has been an Assistant Research Professor of the CEOE, University of Delaware. His research interests include advanced signal processing and communication techniques for mobile radio frequencies as well as for underwater acoustic environments, underwater acoustic signal propagation, and the general area of ocean sampling.

The Baltimore Code Craftsmanship meetup group will hold its monthly meeting at 7:00pm on Thursday, March 27 in room 107 of the Physics on the UMBC Campus. The meetup is for students, faculty and software developers in the Baltimore area that care about the quality of their work and want to practice and improve their programming skills, share what they know and learn new things from others.

This is a hands on coding user group with no presentations. Each meeting will be a dojo where we will go through a challenging software craftsmanship exercise that focuses on clean code, test-driven development, design patterns, and refactoring. We will pair up and practice on a kata in order to learn and apply the values, principles, and disciplines of software craftsmanship. Come with your laptop equipped with your favorite programming and automated unit testing environment. If you don’t have a laptop, come anyway, we will need only one laptop for every two people. Be prepared to pair up, learn, share and have fun!

Join the meetup and register to attend at the meetup event page.

Feature Engineering for Large Scale Predictive
Modeling with Electronic Health Records

Dr. Fei Wang
Healthcare Analytics Research group
IBM T. J. Watson Research Center

1:00pm Wednesday, 26 March 2014, ITE325b, UMBC

Predictive modeling lies in the heart of many medical informatics problems, such as early detection of some chronic diseases and patient hospitalization/readmission prediction. Typically those predictive models are built upon patient Electronic Health Records (EHR), which are systematic collection of patient information including demographics, diagnosis, medication, lab tests, etc. We refer those information as patient features. High quality features are of vital importance to building successful predictive models. In this talk, I will present two feature engineering technologies to improve the quality of the raw features extracted from original patient EHRs: (1) feature augmentation, which constructs more effective derived features from existing raw features by exploring the event sequentiality; (2) feature densification, which imputes the missing feature values via knowledge transfer across similar patients. Along with each technique we also developed a visual interface to facilitate the user exploring the derived features. Finally I will conclude the whole talk with some future research directions.

Dr. Fei Wang is currently a research staff member in Healthcare Analytics Research group, IBM T. J. Watson Research Center. Before his current position he was a postdoc in Department of Statistical Science, Cornell University. He received his Ph.D. from Department of Automation, Tsinghua University in 2008. Dr. Wang’s major research interests include data mining, machine learning as well as their applications in social and health informatics. He actively publishes papers on the top venues of the relevant fields including AMIA, KDD, ICML and InfoVis, and he has filed over 20 patents (four issued). Dr. Wang has given seven tutorials on different topics at ICDM/SDM/ICDM, organized seven workshops on KDD/ICDM/SDM/WSDM, and edited three special issues on Journal of Data Mining and Knowledge Discovery. His Ph.D. thesis was awarded the National Excellent Doctoral Thesis in China. His research paper was selected as the recipient of the Honorable mention of the best research paper award in ICDM 2010, and best research paper finalist in SDM 2011. More information can be found on his homepage.

Host: Prof. Kostas Kalpakis,