Sneha Rajana: Voices of Penn Engineering Master’s Alumni

Sneha Rajana: Voices of Penn Engineering Master’s Alumni

Sneha Rajana

This is part of our series of articles, written by Penn Engineering alums in their own words, of their experiences at Penn and how it shaped their lives. This article is written by Sneha Rajana, who graduated from the M.S.E. Program in Computer and Information Science in 2017. She is currently a Software Development Engineer at Amazon and is based in Seattle.

I was introduced to my first dance lesson when I was 5 years old. I remember quickly identifying dance patterns and being fascinated by how a combination of simple movements can form wide varieties of complex choreographies. That was just the beginning of my love for dancing.

As I grew up performing and choreographing dance sequences, these skills extended to math and language. I absolutely enjoyed reading and problem solving. I went through a phase of constantly playing with words and phrases in my head, and at one point in the fifth grade, I was an expert at spelling words backwards. These early experiences in pattern recognition drew me to computer science in college and eventually to the path of language understanding and data science, which is all about pattern recognition and data analysis.

I now work at Amazon in Seattle as a software engineer, which requires understanding and improving the ways in which customers engage with notifications sent to them by Amazon. I also interned with Audible, an audiobook company and an Amazon subsidiary, during the summer after the first year of my master’s program.

I grew up in Bangalore, known as the Silicon Valley of India, so I was exposed to technology from a young age. During the final year of my bachelor’s program in Information Science and Engineering at PES University, I took a natural language processing course that taught me the basics of automatic language understanding and machine learning while building a chatbot from scratch for the final project. I was curious to dive deeper into these fields upon graduation and applied to relevant master’s programs. I was also excited to experience life outside of Bangalore.

The flexibility of the Computer and Information Science (CIS) program attracted me to Penn. The program allows students to explore the breadth of computer science courses or dive deep into specific areas like artificial intelligence or distributed systems. The interdisciplinary courses that I took at Penn Engineering and The Wharton School had the right mix of creativity, research, engineering and business. I learned solid engineering skills that guide most of the technical decisions I make on a daily basis.

My master’s thesis and PennApps were the highlights of my Penn experience. Professor Chris Callison-Burch was not only my thesis advisor, but has been a wonderful collaborator, mentor, and the person who got me interested in natural language processing and machine translation research. I first worked with Professor Callison-Burch for an independent study, during which I focused on discovering an automated technique for learning antonyms with paraphrases. I worked on creating techniques for generating large datasets and trying to model difficult language patterns. I extended this study to a master’s thesis, solving the same problem using deep learning techniques by training different language datasets using a morphology-aware neural network. This is essentially a recurrent neural network model which understands forms of words and uses that knowledge to classify or predict the semantic relationship between two words or phrases.

I also advised an undergraduate team who used this work to create a game of semantic relationships called KnowYourNyms? for their Senior Thesis. I presented my work at various conferences, including the Grace Hopper Conference and MASC-SLL, and published at renowned natural language processing conferences like the Association of Computational Linguistics Annual Meeting and the Conference on Empirical Methods in Natural Language Processing.

I participated twice in PennApps, the world’s largest college hackathon hosted by Penn. My team made it to the top 10 during PennApps XII and secured second place during PennApps XIII. The first time around my team built an automated transcription system that produces a transcript and summary of meetings, complete with speaker recognition. The second time, we built an automated solution for tracking and management of breast milk for neonatal intensive care units. This project has since evolved into a startup called Keriton.

Apart from course projects and hackathons, I enjoyed working on exciting projects as a research assistant for the Wharton Behavioral Lab and Wharton Finance. The Wharton Behavioral Lab provides a variety of services that support data collection for behavioral research on business-related topics. I worked on the data collection, analysis and improvement of an eye tracking software to enhance the research productivity of Wharton faculty by minimizing the operational costs, both time and money, of conducting research.

Professor Ani Nenkova gave me the opportunity to be a teaching assistant for Computational Linguistics (CIS 530). I’ve loved teaching since high school and was thrilled to have opportunities to do this at Penn. I enjoy giving back to the community and continue to do this today by speaking at conferences and teaching courses at the Machine Learning University, a program that teaches machine learning to software developers at Amazon.

I also worked closely with Professor Boon Thau Loo, who not only headed the CIS master’s program at the time, but was also my academic advisor. I am profoundly grateful to him for helping me to make exciting choices throughout my master’s program. I also served as the CIS master’s program events coordinator and worked with Professor Loo to organize networking and social events for graduate students in the Computer and Information Science department. Additionally, I served on the Student Advisory Board for Advancing Women in Engineering, started a Bollywood dance group with my peers called Penn Curry, and taught dance classes as part of GAPSA’s Penn Shape initiative for student wellness. I was honored to receive the Penn Engineering Master’s in Engineering Leadership Award for my services to Penn and the Philadelphia community during my time as a Penn master’s student.

An education at Penn was certainly challenging. But as a dancer, I was encouraged to take risks, push myself beyond my limits, learn from my mistakes and get back on my feet. After employing these lessons at Penn, these experiences have shaped my life and taught me to accept challenges with confidence. The myriad experiences at Penn taught me how to deal with ambiguous problems and make the most of opportunities. I met the smartest and most fantastic people, and fell in love with research and the infinite possibilities in computer science.

Sneha Rajana