August 3, 2022

Newest Faculty Member: Shohini Bhattasali!

In the Fall, we will be welcoming a new faculty member to the Department of Language Studies at UTSC! Shohini Bhattasali will be joining us as a computational linguist! We had the great pleasure of sitting down with her for an interview. Keep reading to learn more about her! 

What attracted you to the UofT linguistics department?

UofT has an incredible intellectual community and this is reflected through the research and the curriculum. I would love to help strengthen the computational linguistics program and I’m very excited to collaborate within Linguistics and with other departments (e.g. cognitive science, and information science). I also like how each campus has its unique identity but still makes up one cohesive whole. 

Do you have any expectations regarding the department? 

Everyone seems really welcoming and friendly. I am excited to see what everyone is working on and learn more about collaborative, interdisciplinary opportunities. The students at UofT seem very motivated and I’m excited to work with them and guide them along the way. I’m especially looking forward to working with students who want to incorporate computational modelling into their projects or are interested in the cognitive science of language and need guidance. 

You have taught/assisted many courses ranging from computational linguistics to Hindi to writing, which has been your favourite? 

Definitely the linguistics courses! They line up with my interests much more. While I was a teaching assistant for linguistics courses, I got to design tutorials. This was a great teaching experience as I got to see how the students were able to apply the theories they were learning. The writing courses were also great because I was able to design a course from scratch for first-year students. It was very fulfilling to see the students' trajectories as they improved their academic writing skills. These courses were the most rewarding in terms of seeing students improve and gain confidence in their writing! 

Do you notice any trends amongst your top students?

My top students are typically the ones who are engaged and ask questions in class. They are the ones who are not afraid to dive deeper into ongoing topics during class discussions. I know some students are shy and might be intimidated by speaking up in class, but they can still participate in tutorials and drop by during office hours. While it is hard to generalize, student engagement can often be an indicator of how they are doing. If they can relate their personal interests to the material, they will be more motivated and interested in learning. It is great to see students interested in what I am lecturing about and how it changes the way they see linguistics. Students coming from high school often don’t know much about linguistics so it's particularly enjoyable to observe the ah-ha moment where their interest is sparked and they figure out how linguistics isn’t centred around prescriptivism. 

What has been your most memorable research project? 

My dissertation was mainly based on a large-scale fMRI study. I had started grad school with an interest in computational linguistics and discovered neurolinguistics along the way. My advisor was starting a new cognitive neuroscience project and gave me an opportunity to be involved in this cross-linguistic fMRI study. He believes in experiential learning so it was a steep learning curve but I was involved in the experimental design, data collection, data analysis and then training other grad students and undergrad RAs. It was my first time working with neuroimaging data, but this experience really helped guide my research program. It took over a year to collect the brain data but the good thing with using continuous, naturalistic fMRI datasets is that it's not tailored to one research project and we can use it for many different research topics. I’m a big fan of naturalistic fMRI/EEG/MEG datasets for reusability and replicability purposes!

What are some of the issues you face in the field of computational linguistics?

In the last 10 years, the field has exploded and grown exponentially. It can be challenging to even define what “computational linguistics” is as the field is changing so quickly. Additionally, the line between natural language processing and computational linguistics is getting blurry. I personally see computational linguistics as a scientific study of language using computational tools, whereas natural language processing is more about engineering and building tools that are useful for language applications, e.g., Amazon Alexa (speech recognition) and Google Translate (machine translation). 

Artificial intelligence and machine learning approaches have also become tremendously popular, but we need to be careful in applying these approaches blindly to neuroimaging data because there is still so much about the brain we don’t know. While we can use these new fancy tools to get good results on certain tasks, we cannot always rely on them to understand why we get the results we get. For example, a computational model like GPT-3 is very good at predicting the next word in a sentence, but we don’t fully know how the prediction is being generated. If we don’t fully understand the representations being learnt by these models, how can we use them to understand the representations that the brain is using? As scientists, we always critically think about the tools we use and this is just another tool we have at our disposal. Maybe in a few years, we will have a more in-depth understanding of these models, and we can leverage that to understand cognitive mechanisms behind language comprehension and production. I do use computational models in my work to operationalize and embody cognitive hypotheses but I always prefer using simple and interpretable models over these fancier, black-box models.

Do you have any hobbies / secret passions? 

I love reading! I also like to bake since it’s a great way to destress while still feeling productive. Dance and music have played a large role in my life. Growing up in India, I trained as a classical Indian dancer (Odissi) for 15 years and then, I was on my college dance team too. I also love attending classical music concerts and dance performances. I’m looking forward to attending more of those in Toronto! 

What are you most looking forward to about living in Toronto? 

Toronto is a big diverse city which is exciting! I grew up in a large city too, but I have mostly lived in smaller, college towns during undergrad and grad school so I’m very happy to be moving to an urban area. I’ve also heard a lot of good things about Toronto’s multicultural food scene which makes sense given the large immigrant population. I also love visiting museums, discovering local bakeries, and finding new go-to coffee spots. It will be interesting to see what I will find in Toronto! I’m also looking forward to exploring more of Ontario and Canada in general since I’ve only visited Quebec City. 

I will be going back and forth between the Scarborough and St. George campuses, and luckily for me I already have a few connections on all campuses which I’m excited about. Nathan Sanders  (Facultywas actually my undergrad thesis advisor so it’s such a small world moment to now be his colleague! One of my best friends from grad school is a faculty in iSchool (Shion Guha) and another friend is joining UTM Language Studies (Lingzi Zhuang, new faculty member). Overall, I am excited to join UofT and am looking forward to creating a lab at the intersection of computational linguistics and cognitive neuroscience, meeting the students and making more connections here!

We would like to thank Shohini for taking the time out of her busy schedule to be interviewed! We look forward to seeing her on campus in the Fall! Feel free to connect with her on Twitter if you have any questions or if you want to introduce yourself! 

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