Interview with Visiting Scholar: Nasim Tohidi 

by Katsumi Ibaraki (MS student, Michigan AI)

Introduction: Nasim Tohidi is a Visiting Scholar from K. N. Toosi University of Technology. She received the Best Poster Award at the Michigan AI Symposium 2023.
The content of this interview has been edited for coherence and readability.

“When things get tough, which has happened many times to me, you reach a point where you think you cannot (or don’t know how to) continue. Try to maintain optimism and forget about the current situation in your mind for a short time. Think about that moment when everything, all of the difficulties, are finished and you say “Okay! It was hard, but I could make it”. The sweetness of this feeling and the relaxation that you give to your mind, even for a few moments, by skipping the current pressure, give you the passion to continue.

I believe perseverance is very important and you shouldn’t give up.”  – Nasim Tohidi

Katsumi: First of all, thank you so much for taking the time for the interview. Can you briefly introduce yourself to our readers?

Nasim: Thanks for having me here. I am Nasim Tohidi. Currently, I’m a visiting scholar working in Prof. Rada Mihalcea’s lab, Language and Information Technologies (LIT). My main field of research is Natural Language Processing (NLP). Mainly, I have worked on meaning representation, question-answering, and text summarization. The project which we are working on here is about misinformation. 

Katsumi: To follow up, what was the deciding factor to come to Michigan, as a visiting scholar?

Nasim: During my education, I had the chance to work remotely with researchers all over the world, and I knew how international collaborations can widen your horizons and knowledge, and provide you with various opportunities.

Additionally, as you probably know, there are some limitations for researchers and students in my country and we do not have access to many resources. So, like many other students there, I was very passionate about learning more and communicating with people worldwide. Thus, I started searching and I found the LIT lab here. I realized it is vastly diverse and I liked the topics of projects which they are working on. Moreover, having the chance to work with pioneers like Prof. Rada Mihalcea and all the talented students in the lab is a great honor. Further, the university’s strong reputation for cutting-edge research, state-of-the-art facilities, and a vibrant academic community were other factors in my decision.

So I talked to my advisor and he contacted Prof. Mihalcea. After the application process, she accepted me here. However, after that, it took me a long time to receive my visa and be able to start my program here. 

Katsumi: Talking about research, you were one of the winners of the Michigan AI Symposium poster session for your work on Syntax-free Meaning Representation for Natural Language. Was this work what you did in Iran before coming to Michigan? 

Nasim: Yeah, the poster was about the main part of the work I did for my Ph.D. thesis. We have submitted and published papers related to the completed parts of this research and part of it is still a work in progress.

Katsumi: If it is still a work in progress, there might not be a clear conclusion of it yet. But what would you say are the key takeaways from this work?

Nasim: My initial perspective for my thesis was finding a semantic representation of language that is not specific to a certain natural language. Because when you look at all the front-line research in the world, you see that the overwhelming majority of them mainly concentrate on English. But I’ve always been passionate about how we can remove this limitation and make an integrated representation that won’t be dependent on the structure of one natural language. 

In this way, not only can we facilitate communication between humans and machines, but we will also simplify communication among people all over the world. I started with this goal and then I learned about Abstract Meaning Representation (AMR) which was proposed for English. After that, we tried to introduce a meaning representation model based on AMR that is not dependent just on English and tackles some weaknesses of AMR as well. For instance, unlike AMR, it can represent tense and coreference and it works at the document level, not just the sentence level.

Katsumi: Is this still your current focus in research? 

Nasim: We already have proposed the model and its formal structure, and generated a Persian corpus, and an English corpus for the proposed model. We have applied the Persian corpus in some applications, like sentiment analysis, and text summarization, and compared it with state-of-the-art approaches and observed improvement in the results. Currently, I am working on applying the English dataset to some sub-tasks of NLP. 

Additionally, if I look back, as I started my Ph.D. in 2018 and in those days, ChatGPT and large language models (LLM)s weren’t available or accessible to us, in the future, I want to find some connections to see how I can make improvements in the methods I developed that leverage these new models. 

Katsumi: Currently, are you doing related work with the members of the LIT lab?

Nasim: Currently, I’m collaborating with Verónica Pérez-Rosas and Ashkan Kazemi, which I am really glad about. We are working in the area of misinformation and we want to see how the demographic data of users in the U.S. can affect how they look at information and whether they can distinguish between misinformation and true information. The data that we are generating/annotating is related to COVID-19 and its vaccine.

Katsumi: What would you say is your ultimate goal or what do you envision in your research?

Nasim: Great question! Until now, my main concentration has been on NLP during both my Master’s and my Ph.D. But besides that, I’ve worked on other topics such as AI ethics, recommender systems, and evolutionary algorithms. I have always tried to find a connection between NLP and the other fields that interest me. I hope that in the future I will have more time and resources to improve my experience and knowledge in other areas too. 

Katsumi: What advice would you give to students who haven’t decided or maybe they’re in their bachelor’s or in their Master’s that don’t know if they want to go to industry or if they want to stay and go for a Ph.D.?

Nasim: If you are sure that you want to be a member of academia, Ph.D. is the path that you should follow and it’s better to choose labs and people who help you along this path and boost your knowledge and abilities. 

In case you are in your undergrad or Master’s degree and you are not sure if you want to be in academia or industry, give yourself a chance to feel both of them. For example, you can be an industry intern during the summers; after that, you will have the vision you want for the decision.

Also, if you have decided on academia, it’s better to improve your knowledge deeply, in at least one field during your Master’s degree. If you want to enter industry, it is better to test different topics and have more diverse knowledge in various areas.

In the first/second year of your Ph.D., you should decide and then you can quickly plan your future steps. Because when it is clear what you want, you can do it optimally. No matter what happens at last, it’s better to have a point of view about your future.

Katsumi: Looking at the next five to ten years, where do you see yourself?

Nasim: I’ve always been passionate about being part of academia. So my goal after this step is to find a postdoc position and then my ultimate goal is to find a faculty position where I can continue my research and academic collaborations. 

I was lucky because I had the chance during almost my whole education to work as a teaching assistant, tutor, or lecturer. So I have seen how teaching can help you learn things better. Each time you go to the classroom you learn new aspects of the same topic by discussing the subject with the students, and you see how during time gradually topics change and improvements happen. This feeling is something that I can’t replace with anything else.

The atmosphere of academic environments has always been more interesting to me than the industry because I see that young people come to this circle and bring their passion and freshness. Hence, the learning circle is continuous, you never stop and each day you can learn new things and you can feel how you affect society. According to my experience, it is not the same in the industry, however, people and their visions are different. 

Katsumi: Before we wrap up, is there any final advice that you would like to conclude the interview with?

Nasim: It’s better to set some goals for yourself. It doesn’t matter if they’re long-term or short-term, but you should have a goal to have something to keep your courage and to be able to fight for!