Convocation is happening this week, which means having to confront a reality that can be disconcerting for the graduate: you have to take your knowledge out into the real world! We've asked some of our past graduates about what happens after graduation with a linguistics degree in hand, and they have been gone on to do some amazing things.

Vagrant Gautam is finishing this Spring with a BSc in Computing Science and Linguistics and has been a huge contributor in many of the department labs as a coding wiz and all-around great linguist. Xe has already been offered a number of jobs in computational linguistics as well as placement in computational linguistics departments at The University of Edinburgh, Carnegie Mellon University, and the University of Washington; for now, xe's decided to pursue industry work revolving around xyr main interests at Dialpad.

We asked xem a few questions on xyr thoughts and experience, and xe has very generously shared xyr wisdom, including some very helpful specific resources for those interested in computational linguistics:

• Are you surprised by the incredible offers? You’ve contributed quite a bit to our department over the past few years. How do you think your experience in labs here has shaped your applications?
  

Yes, I was surprised and thrilled about all of the offers. It's very validating to have been accepted into the top graduate schools for computational linguistics and it makes me feel like all my effort over the last 4 years has been worth it. I believe my research experience has been instrumental in my university acceptances and my offer to work at Dialpad. I have worked at Dr. Ashley Farris-Trimble's lab, the Phonological Processing Lab, for three years, and I have worked with Dr. Maite Taboada at the Discourse Processing Lab for the last year of my degree.

At the Phono Lab, we do research in experimental phonology using eye-tracking. Through this, I was exposed to the process of scientific experimentation in linguistics right from experimental design, ethics and experiment creation, to data collection, collation and the analysis of results. Grad schools value this kind of strong experimental background. Additionally, being the most computational research assistant at the lab for a while, I got to write new Matlab scripts and demystify old ones for other lab members by adding detailed comments to the files. During my internship at GE Digital, I found that being able to explain your code to someone who is non-technical (in sales or product management) is a critical part of the job of a software developer. This is not as highly emphasised in computing science classes and this work helped hone those skills.

I received two Undergraduate Student Research Awards (USRAs) to work at the Discourse Processing Lab, where I have been involved in a number of projects: I have analyzed the constructiveness, toxicity and topics of online comments and articles; I have collected lists and statistics about a curious construction we call the "adverb-ly adjective"; and I have been part of the Gender Gap Tracker team, where we have shown a huge disparity in how often Canadian news outlets quote women compared to men. What all these projects have in common is their use of computational linguistics methods. These experiences have given me knowledge of the tools currently used in the field, and the open-endedness of research work has taught me skills that are hard to learn with the constraints of classes. My work on these projects and my explanation of the skills I had acquired through them made my applications competitive.

• What is your goal right now in life? Academic path? Job path? What sort of job would you like to do?
  

My short-term goal has been to get a job because I need to work to save up for graduate school at any of the places I have been admitted to. I have accomplished this and I am very excited about joining Dialpad because this is exactly what I want to do! I love the intersection of computing science and linguistics and so to have a job title like Computational Linguist is just incredible.

Long-term, I see myself doing a Masters and probably also a PhD because they are common requirements in this field. I am quite particular about wanting to do a Masters first because I believe doing a smaller-scale thesis will help me better evaluate whether committing to a PhD is something I really want.

What got me into computational linguistics was Google Translate (specifically, how bad it was for anything more than simple sentences). So I do hope to someday work on Google Translate. Machine translation is a very interesting area, and having not had much exposure to it so far, I would love to have that at some point.

• You’re a computational linguist. What advice or message would you give to undergraduates who are maybe afraid of pursuing this discipline?
  

First of all, I completely understand the fear. Before I came to SFU I was worried that everyone in Computing Science would have been coding since high school and would know much more than me. I had no coding experience prior to my first term at SFU. Even after my first two terms, when I had taken a few CMPT courses, I was not doing as well as I was doing in my LING courses, which was discouraging. At that point, it helped me to consider the similarities between linguistics and computing science.

Almost all of computing science is logical and like puzzle-solving. In this way it is a lot like linguistics - when you work through a phonology or morphology dataset, you are solving a puzzle! Writing a program to sort a list of numbers in ascending order is quite similar. You break down the problem into smaller steps and then you write them down as instructions for the computer.

Because a machine has to understand these instructions and not a person, programming languages are very structured. So learning Python or Java is very different and much easier than learning Mandarin or Malayalam.

I encourage everyone who is afraid of programming to just try a course - be it at SFU or a free online course (there are lots of good ones out there). Knowing the similarities between linguistics and computing science might help to actually enjoy it!

• Is there anything else you'd like to share, or anybody you'd like to acknowledge?

For those interested in computational linguistics but not sure where to start, I have some suggestions:

• Take CMPT 120: This is the most basic CMPT class offered at SFU, for students with no experience in programming. You typically learn Python, which is the main language used in computational linguistics.
• Learn Python The Hard Way: This is a good book to learn Python basics that helped me a lot when I was getting started: https://learnpythonthehardway.org/book/
  
• NLTK Book: After learning some Python, you can use it with NLTK, a programming toolkit for natural language processing: http://www.nltk.org/book/
  
• Take LING 807: This is our department's computational linguistics course, usually taught by Dr Maite Taboada who is amazing. Although it is an 800-level (graduate) course, you can get special permission to take this course if you are an undergraduate in 3rd or 4th year.
  
• Applied Text Mining in Python: This is a MOOC, a Massive Open Online Course. I love the courses offered online on websites like Coursera and edX and they have been hugely useful for me in the last several years of my studies. You will need to know some Python to do this and the programming exercises are a lot of fun: https://www.coursera.org/learn/python-text-mining
• Advanced NLP with spaCy: In research and professional computational linguistics work, spaCy is the library (programming toolkit) that is used rather than NLTK. NLTK is more of a teaching tool to learn the concepts. This online course requires good knowledge of Python for you to get the most out of it: https://course.spacy.io/
  

People I would like to specially acknowledge:
Our entire department is fantastic and every single instructor I have taken a class with has been passionate about what they do. I want to specially mention Dr Ashley Farris-Trimble and Dr Maite Taboada because I have worked most closely with them. In my time at SFU there have been countless occasions when I have gone to them for advice, and they were references on all my applications. I can’t imagine I could have gotten into the schools I got into without their strong recommendations. I would be remiss if I didn’t also talk about our undergraduate advisor, Rita Parmar. Beyond her resourcefulness and patience as an advisor, she has always been genuinely interested in what I was doing. There are many opportunities - including this opportunity to be featured on the website - that I wouldn’t have had if not for her.

There are so many avenues for linguistics graduates, so the next time somebody asks you "what are you going to do next?", you can confidently reply: "anything I want!"

Are you a grad who has done something interesting? Do you have an experience you want to share? Contact us at lingcomm@sfu.ca so we can tell everybody about it to inspire the next round of linguists.