SHUTTERSTOCK

The Computer Science Connection

My friend once told me a story about her sister’s college interview. Th e interviewer asked her sister if she spoke any languages other than English. Jokingly, my friend’s

sister replied “Java,” the popular programming language that is now ubiquitous in the world of mobile applications, embedded systems, and commercial and business applications. I loved this story because I could imagine myself saying the same thing. I had learned Java, my fi rst programming language, when I was 11 years old.

by Megha srivastava

www.cty.jhu.edu/imagine imagine 15

From a very early age, I was addicted to anything related to computer technology. However, as I grew older and encountered new subjects, I became passionate about many of them: music, mathematics, photography, chemistry, genetics, and more. I sometimes found it depressing that I didn’t have a single clear passion that I wished to pursue or any idea of what I wanted to be when I grew up. Because all the subjects I loved were so distinct, I worried that I wouldn’t be able to pursue them all later in life.

But that was before I realized that computer science—one of my fi rst and most intense interests—was diverse and interdisci-plinary enough to allow me to pursue everything I loved to do.

A Common threadIn middle school, I chose summer camps based on whatever computer science topic piqued my interest at the time. I attended a robotics camp, learned HTML in a summer pro-gram on web design, and taught myself how to create an iPhone application using Corona SDK. Each experience demonstrated to me the power of computing in creating lively and interactive solutions to complicated problems. I began to see that sophisti-cated surgical robots, social networking sites such as Facebook, and popular applications such as Instagram all had computer science in common.

I started to think of ways I could relate computer sci-ence to the things I love. From reading Douglas Hofstadter’s Gödel, Escher, Bach: An Eternal Golden Braid, I learned about the mathematics behind music by famous composers such as J.S. Bach. Th is inspired me to sign up for a course called Psychoacoustics & Creative Computing at the California State Summer School for Math & Science (COSMOS) in the summer before 10th grade. Th ere, I studied how the technical parame-ters of sound, such as frequency, relate to the human perception of pitch, how musical instruments are engineered based on scientifi c principles, and how sounds of diff erent timbre and textures are created. I also learned how analog-to-digital con-verters sampled and digitized analog sound waveforms into streams of bits that can be stored and processed by computers. It was fascinating to learn how the MP3 fi les I had grown up listening to were generated by special algorithms that reduce the size of an audio recording by using fewer bits to represent frequencies of sound that are less audible to the human ear. I found these intersections of music and computing, two of my strongest passions, incredibly exciting.

In high school, aft er discovering yet another interest—chemistry—I decided to take a summer college course in nanotechnology at the University of Pennsylvania. Th e course

approached nanotechnology from physics, chemistry, and other perspectives, but I was especially excited to fi nd that it also had applications in computer science. When I did a project on the delivery of growth factor chemicals for stem cell cultures, I learned that special robots were currently being used to make the delivery and synthesis of these chemicals more effi cient. Some friends in the program did a project on quantum computing, an emerging area of study that could lead to much more powerful computers. Traditional comput-ers store memory in “bits” that can be in either a “1” or “0” state. Quantum bits, or qubits, on the other hand, can be in both states simultaneously, which means that quantum com-puters can run algorithms more quickly.

It seemed that everything I was learning was bringing me back to computer science. It was time to dive in.

A new Way of seeingOverlooking the ocean in Marina del Rey, California, is a research branch of the University of Southern California called the Information Sciences Institute (ISI). ISI researchers collaborate on a variety of topics in computing, from artifi cial intelligence to health informatics to natural language process-ing. I took a chance and sent an email to Dr. Yolanda Gil, who was doing interesting work in the areas of text analytics and “semantic workfl ows,” to ask if I could do an internship in her lab. A workfl ow is a series of several programs that feed into one another to accomplish a certain goal. When I was accepted as an intern, I got to see how these workfl ows help scientists analyze complex raw data.

My fellow interns and I started off by learning the details of the specifi c workfl ows that ISI researchers create. For our fi rst project, we ran two HTML fi les through a workfl ow to determine how similar the fi les were by topic. Th e fi rst step would rate words’ importance in each article by determining how frequently they appeared; subsequent steps compared the words’ frequencies in both articles, allowing us to come up with a number that described how similar the two articles were. Th is project helped us understand a range of applications; for exam-ple, when scientists need to fi lter huge volumes of data to fi nd only relevant data pertaining to a certain topic, these workfl ows will aid in determining how similar various groups of data are. Th e general technology that these workfl ows incorporate is also used in targeted advertising systems that determine a person’s main interest and customize advertisements accordingly, and in specialized search tools that help researchers locate high-quality articles on a specifi c topic.

My summers at isi gave me

the chance to work on

challenging, cutting-edge

projects and also

introduced me to many fascinating people. As

a bonus, writing

algorithms introduced

me to concepts

from linear algebra,

which gave me a head start on a

subject i’m now studying

at school.

16 imagine may/Jun 2013

Next, we wrote our own components for these workfl ows. Our goal was to be able to run Twitter data—specifi cally, all the tweets surrounding the 2010 Haiti Earthquake—through a workfl ow to detect the topics represented and then group the data based on those topics. I wrote a program to remove special characters, punctuation, and numbers, and because we received the Twitter data as HTML fi les, we also had to remove extra symbols used in HTML. In addition, we had to overcome the language barrier: the workfl ows are written for only one language, and tweets can be in any language.

After running the cleaned-up data files through our own workfl ow components, we were able to analyze the topic trends for the week following January 12, 2010, the day of the earthquake. By looking at the common words and the spikes in the number of tweets at certain times, we gained a new insight into the emotions surrounding this event. Words like “pray” and “God” appeared frequently at the beginning of the time period; later, in the aft er-math, words such as “help”, “support,” and “aid” demonstrated a shift from fear and shock to motivation to help.

Computational Code breakersTh e following summer I returned to ISI to work under Dr. Kevin Knight in his research on natural language process-ing. Dr. Knight had just made news for using computer science algorithms to break the Copiale Cipher, the code of an 18th-century German secret society. Th is work was not only groundbrea king for the computational techniques he had used, but also promises to help historians gain a better understanding of the secret society. Ever since taking a cryptography course through CTYOnline in elementary school, I had been fasci-nated by secret codes and hidden messages, so I found this work immensely interesting. I was thrilled when Dr. Knight accepted me into his lab for the summer.

I worked on devising effi cient algorithms and writing soft -ware for solving certain cryptographic problems. My graduate student mentor and I wrote an algorithm for decrypting cipher text from Enigma, the German World War II machine. Th e Enigma is one of the most interesting, complex, and historically important encryption systems. In fact, I had once seen many cryptographic machines, including Enigma, during a visit to the National Security Agency’s National Cryptologic Museum. Figuring out a way to solve messages encrypted with it was incredibly challenging and enlightening. We then ran the algo-rithm on USC’s multi-core cluster computers (many computers connected to each other to increase speed and performance) to decode previously unbroken Enigma messages. Later, I

had the opportunity to work with other ciphers and codes, including the Voynich manuscript, codes from the Swedish Freemasonry, and codes from a secret women’s society in China called “Nushu.” We are now working on a machine-learning approach to have a computer detect what kind of cipher any kind of encryption is using.

My summers at ISI gave me the chance to work on chal-lenging, cutting-edge projects and also introduced me to many fascinating people. I met researchers working on the comput-ing behind language translation, collaborated with graduate students from universities such as UC Berkeley and Carnegie Mellon, and interacted with professors with a wide range of expertise. As a bonus, writing algorithms introduced me to concepts from linear algebra, which gave me a head start on a subject I’m now studying at school.

Participating in these internships and summer programs has opened my eyes to how interdisciplinary computer science

is. I am now that girl who, when there is a complicated series of calculations to be done for chemistry lab, quickly writes her own computer program to do it for her. I’m a pianist who now plays with an appreciation for the mathematics behind the sounds I am hearing and how computer algorithms can apply those mathematical foundations in myriad ways. I’m a photographer who loves learning about the algorithms behind Photoshop and how computer scientists contribute unique capabilities to new advanced cameras. Even if I don’t major in computer science in college, I know that whether I’m studying music, math, biology, physical sciences, or even the humani-ties, there will always be an opportunity to apply my skills and interest in computer science.

Megha Srivastava is a junior at Harvard-Westlake School in California. She loves math, chemistry, and computer science, and recently was named a national runner-up and a Southern California affi liate winner for NCWIT’s Aspirations in Computing award. She is a member of her school’s Science Bowl and FIRST

Robotics clubs, a member of the swim team, and a peer tutor in math, and serves as a student ambassador for her school. Outside of school, Megha enjoys pursuing her passion for the piano and photography, and volunteers at Vision to Learn, a charity that helps provide free eye exams and glasses to low-income families in Los Angeles.

www.cty.jhu.edu/imagine imagine 17