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)

The post Game Developers Club Fall 2018 Opening Meeting and Game Jam, 1pm Fri 9/7 appeared first on Department of Computer Science and Electrical Engineering.

Statistical Learning 101: Regression vs. Classification

Dr. Ergun Simsek
Co-director, Computer Science and Information Technologies Department
Bahcesehir University, DC campus

11:30-12:30pm Wednesday, 5 September 2018,  ITE 325b, UMBC

In the last decade, statistical learning, which is the concept of using algorithms to identify patterns and/or make predictions based on input data sets, has received increased interest due to its potential to answer diverse questions in various industries such as finance, business, and health. In this talk, I will introduce the two most fundamental methods of statistical learning that are applicable to both data and computer science: regression and classification. Real world examples will be provided to highlight the differences and similarities between these two methods and place them into appropriate contexts.

Dr. Ergun Simsek earned his PhD from Duke University in 2006. He is the co-director of the Computer Science and Information Technologies Department at the Bahcesehir University’s newly established DC campus (BAU DC). He joined Bahcesehir University’s Electrical and Electronics Engineering Department and later was promoted to associate professor. Upon moving back to the United States, he spent six years at the George Washington University’s Department of Electrical & Computer Engineering before returning to BAU at their DC campus. Dr. Simsek’s private sector experience includes working for Schlumberger Doll Research (SDR) Center’s Math and Modeling Department as a post-doctoral research associate, where he helped develop new numerical techniques for various oil and gas industry applications. He continues researching how to solve emerging engineering problems through efficient and robust computational techniques.

Host: Dr. Richard Forno (*protected email*)

The post talk: Statistical Learning 101: Regression vs. Classification, 11:30 9/5 appeared first on Department of Computer Science and Electrical Engineering.

Are you interested in working in the government for the summer or after you graduate? If so, the Career Center would like to tell you about a great opportunity for UMBC students!

Workforce Recruitment Program
The Workforce Recruitment Program for College Students with Disabilities (WRP), coordinated by the Office of Disability Employment Policy (ODEP) and the U.S. Department of Defense, is a recruitment and referral program that connects federal and private sector employers with highly motivated college students, graduate students, and recent graduates with disabilities who are eager to prove their abilities in the workplace through summer or permanent jobs.

Eligible students must:
- have a disability and be eligible under the Schedule A hiring authority
- be a United States citizen
- be enrolled in a degree program on a substantially full-time basis OR have graduated with a degree in April 2018 or more recently.

If you are interested in interviewing with a representative from WRP or learning more about the program, please contact: Caroline Bodnar, carolc@umbc.edu.

Please visit www.wrp.gov for more information regarding WRP and click on the student registration button to get started!  For more information watch this youtube video.

Registration opens 8/26/2019 and ends 10/11/2019.  For the 2020 WRP release, interviews will be held in the fall of 2019. The interview period for the 2019 cycle will take place between October 28, 2019 and November 19, 2019. 

We hope your fall semester is off to a great start!