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NSA highlights strong partnership with UMBC in Featured School campaign

Over the past two decades, UMBC and the National Security Agency (NSA) have developed a strong relationship, which has led to research, internship, and career opportunities for faculty, students, and alumni. UMBC is the first institution to be highlighted in NSA’s Featured School Series, which launched on September 4.

“UMBC’s long-standing partnership with NSA has provided valuable experiences for our students, faculty, and alumni to pursue internships, careers, and collaborative research opportunities,” said President Freeman Hrabowski. “Through this work we are helping to address the need for well-trained cyber professionals by creating a network of talented people to protect the state, nation, and world.”

More than 1100 NSA employees are UMBC alumni, including Darniet Jennings ‘98, M.S. ‘99, Ph.D. ‘03, information systems management. Jennings continued his dissertation research when he took a job at NSA, where he developed a system to manage big data effectively, which was patented in 2010.

The opportunities at NSA include careers in a broad range of disciplines including cybersecurity, engineering, computer science, language, and biological and chemical sciences. Regina Hambleton ‘87, mathematics, has held a number of positions at NSA and is currently the Agency’s deputy director of Engagement and Policy. She began working at NSA while she was a student at UMBC, and participated in a program that allowed her to spend a semester at UMBC taking courses followed by a semester working at NSA.

The partnership between NSA and UMBC also helps prepare an increasing number of graduates for careers in cybersecurity-related fields, to protect the nation from cyber threats.

Charles Nicholas, professor of computer science and electrical engineering, is also highlighted in the Featured School Series campaign. He has spent two sabbaticals at NSA during his time at UMBC, and has mentored students who completed NSA internships, in addition to students who went on to pursue careers at NSA. Nicholas is interested in the intersection of cybersecurity and data science, and the tools that are used to compare malware specimens.

“There are so many opportunities in the intelligence community, including at NSA,” Nicholas says. “It is important for students interested in those careers to develop technical ability, as well as critical and creative thinking, and I enjoy the chance to help them grow those skills.”

For more information about the partnership, and a few UMBC alumni who work at NSA, visit the UMBC page on the NSA website.

Adapted from a UMBC News article by Megan Hanks. Banner image by Marlayna Demond for UMBC.

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Ballerina, a modern programming language
focused on integration

Dr. Sanjiva Weerawarana
Founder, Chairman and Chief Architect, WSO2

2:00-3:00pm, Thursday, 6 September 2018, ITE325, UMBC

Ballerina is a concurrent, transactional, statically typed programming language. It provides all the functionality expected of a modern, general purpose programming language, but it is designed specifically for integration: it brings fundamental concepts, ideas and tools of distributed system integration into the language with direct support for providing and consuming network services, distributed transactions, reliable messaging, stream processing, security and workflows. It is intended to be a pragmatic language suitable for mass-market commercial adoption; it tries to feel familiar to programmers who are used to popular, modern C-family languages, notably Java, C# JavaScript.

Ballerina’s type system is much more flexible than traditional statically typed languages. The type system is structural, has union types and open records with optional/mandatory fields. This flexibility allows it also to be used as a schema for the data that is exchanged in distributed applications. Ballerina’s data types are designed to work particularly well with JSON; any JSON value has a direct, natural representation as a Ballerina value. Ballerina also provides support for XML and relational data.

Ballerina’s concurrency model is built on the sequence diagram metaphor and offers simple constructs for writing concurrent programs. Its type system is a modern type system designed with sufficient power to describe data that occurs in distributed applications. It also includes a distributed security architecture to make it easier to write applications that are secure by design.

Ballerina is designed for modern development practices with a modularity architecture based on packages that are easily shared widely. Version management, dependency management, testing, documentation, building and sharing are part of the language design architecture and not left for later add-on tools. The Ballerina standard library is in two parts: the usual standard library level functionality (akin to libc) and a standard library of network protocols, interface standards, data formats, authentication/authorization standards that make writing secure, resilient distributed applications significantly easier than with other languages.

Ballerina has been inspired by Java, Go, C, C++, Rust, Haskell, Kotlin, Dart, Typescript, Javascript, Swift and other languages. This talk will discuss the core principles behind Ballerina including the semantics of combining aspects of networking, security, transactions, concurrency and events into a single architecture.

Sanjiva Weerawarana founded WSO2 in 2005 with a vision to reinvent the way enterprise middleware is developed, sold, delivered, and supported through an open source model. Prior to starting WSO2, Sanjiva worked for nearly eight years in IBM Research, where he focused on innovations in middleware and emerging industry standards. At IBM, he was one of the founders of the Web services platform, and he co-authored many Web services specifications, including WSDL, BPEL4WS, WS-Addressing, WS-RF, and WS-Eventing. In recognition for his company-wide technical leadership, Sanjiva was elected to the IBM Academy of Technology in 2003.

Sanjiva also has been committed to open source development for many years. An elected member of the Apache Software Foundation, Sanjiva was the original creator of Apache SOAP, and he has contributed to Apache Axis, Apache Axis2 and most Apache Web services projects.

In 2003, Sanjiva founded the Lanka Software Foundation (LSF), a non-profit organization formed with the objective of promoting open source development, not usage, by Sri Lankan developers. He is currently its chief scientist and a director. LSF’s success stories include many Apache Web services projects and Sahana, the predominant disaster management system in the world. In recognition of his role in promoting open source participation from developing countries, Sanjiva was elected to the board of the Open Source Initiative (OSI) in April 2005, where he served for two years.

Sanjiva also teaches and guides student projects part-time in the Computer Science & Engineering department of the University of Moratuwa, and he is a member of the university’s Faculty of Engineering Industry consultative board. Prior to joining IBM, Sanjiva spent three years at Purdue University as visiting faculty, where he received his Ph.D. in Computer Science in 1994.

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Jordan Troutman is a Computer Science and Mathematics major and just spent his summer conducting research at Rutgers University-  and he’s only a SOPHOMORE!

List any Scholars/Honors programs you are a part of: Meyerhoff Scholars, Honors College

Title of your research project: Understanding Machine Learning Bias without a Ground Truth

Describe your project: My project aimed to understand how predictive computer algorithms can impose biases across protected groups (e.g. race, gender, etc.) when it is not possible to use common measures of comparing an algorithm's predicted outcome with its intended outcome. 

Who is your mentor(s) for your project? How did you find your mentor? Why did you choose them? My mentor was Dr. Anand Sarwate, Assistant Professor in the Department of Electrical and Computer Engineering at Rutgers University.  It is ironic, actually, because he found me. I applied to the RiSE Research Experience at Rutgers through the Big Ten Academic Alliance Summer Research Opportunities application, and he reached out to me because my interest in data science and machine learning would be a perfect fit for this project.  I chose him because I was primarily interested in this field, but also because I was honored someone would want to take me under their wing to conduct research.

How did you become interested in this project? This project sparked my interest because it lies at the intersection of ethics and computer science.  I have always loved coding. But also, I think it is important to understand how individual actions contribute to the structure of our society.  We inherently give power to computers when we start to depend on them to make very complex human decisions, like choosing from a pool of resumes who the most qualified applicants are for a job.  For the computer scientists who create these machine learning algorithms, it is important that we understand the impact to what our programs--discriminatory or not--can affect the world we live in. Since the field of machine learning fairness stems from an analysis that saw black men to be twice as likely of being miscategorized of being high risk of committing a crime again compared to white criminals, I wanted to make sure that people who look like me are not going to be marginally discriminated against based upon a computer's decision.

What has been the hardest part about your research/what was the most unexpected thing about being a researcher? The hardest part about researching this summer was overcoming the jargon barrier used in this specific field of machine learning fairness.  Being fairly new to research, the  novel vocabulary made research feel very advanced and out of my scope of understanding.  Once I got over the language barrier, I remembered that research is simply asking questions and then seeing if those questions can be answered.  Reading papers and getting acclimated to the conventions of contemporary researchers took a lot of time and effort, but it was overall worthwhile because research is really fun!

What has been the most rewarding part? The most rewarding part about researching this summer is that I can talk about the importance of making fair predictive algorithms to anyone.  Making people aware that machine learning algorithms, like Google search results, learn from observations (data), and if the scope of their observations is biased, then the algorithms will inherit those biases as well.  Since this field is very interdisciplinary, I believe it is crucial for researchers to be able to express their ideas in ways that individuals of varying fields and expertise can easily understand why their work is important.  This allows for more collaboration from other academic areas as well as making the essence of research a more inclusive experience.  Bringing more viewpoints on an important topic like machine learning fairness will point us in the direction of the best solution.

How will you disseminate your research? I have presented my research at the RiSE at Rutgers Symposium and the UMBC Summer Undergraduate Research Fest (SURF).  I plan on presenting at URCAD in April, and at an undergraduate research conference this year.

What is your advice to other students about getting involved in research? For UMBC students wanting to get into research, there is no requirement to be in a scholars program or have honors achievement.  Research is a simple concept that anyone can do.  Anyone who has ever identified a problem and envisioned the problem being solved is a researcher at heart.  It may be really intimidating to be working with people who have high degrees and extensive amounts of experience, but those garnishes will never replace the foundation of a researcher.  When anyone enters the world of research, it is important for them to bring their own experiences, perspective, and culture.  Diversity of thought makes problem-solving progress faster.  Additionally, treat attending class as an opportunity to understand rather than to get good grades; this skill and knowledge-base will easily transfer into research.  Get in contact with a professor who has interesting research, talk with them about their research, then get started!  If research may be too much for the school year, applying to summer research opportunities is a great option!

What are your career goals? After going to graduate school and getting my Ph.D., I would love to work at a university as a professor, then maybe become the dean of a college.  I want everyone to feel that learning is an exciting, thriving, living aspect of our everyday lives.  I would also like to work with computer scientists, educators, and policymakers to ensure developing technologies are being developed for the overall social good of our world.

Want to know how you can find a summer research experience?

Want to be the next Researcher of the Week? 

Email: aprilh@umbc.edu or visit ur.umbc.edu

Game Developers Club Fall 2018
Opening Meeting and Game Jam

The UMBC Game Developer’s Club (GDC) explores the art and science of game development in a club environment and includes members from many backgrounds, including computing, digital art, computer modeling and music composition.

Their first meeting will start next week at 1pm on Friday, September 7th, in Engineering 005a. This meeting will kick off their annual Fall Game Jam, where participants will have a chance to propose game ideas, form teams, and develop a prototype over the course of the weekend (9/7 through 9/9).

The meeting will start with announcements and a brief presentation about the club for new members, followed by game idea proposals and the Game Jam itself. If you want to propose an idea for the Game Jam, be ready to give a brief presentation on the following things on September 7th:

• A 1-2 sentence summary of your idea
• What you want to have done by the end of the game jam
• What team roles you still need to fill
• Whether it will be 2D/3D/no preference
• Game engine preference (if any)

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