Aru
Please provide a brief summary of your research.
Overall, the goal of my research is to be able to distinguish between two of the phenotypes of small cell lung cancer (SCLC), adherent and suspension cells, using machine learning imaging techniques. Yet, this summer, the primary finding of my research work was establishing significant differences in displacement between the two phenotypes using a computer vision technique called optical flow. By establishing this difference, we are now able to use this as one form of information to train our machine learning algorithm to distinguish between the two different phenotypes. After this step, we can now look towards extracting features from the longitudinal images of each cell type in order to use this information to train the classification machine learning algorithm. These features can be how morphology of different cell types changes or stays the same over time, whether that be size or shape, or how each cell population moves over time, as established by optical flow. After collecting these features for each of the two populations separately, we will train an initial machine learning algorithm and then experiment with different machine learning techniques to see which one produces the most accurate classification results of the SCLC phenotypes.
What made you interested in pursuing interdisciplinary research more broadly?
What made me interested in pursuing interdisciplinary research was honestly the amount of potential machine learning has for any field in the world. The ability of machine learning techniques to extract patterns and information so quickly from large amounts of data can be so seminal for a field like medicine where there is still so much ambiguity with why certain patient outcomes occur and the unfortunate persistence of disease. I think it can really change the game with finding patterns in the behavior of disease that we have never even considered.
What made you initially interested in researching your project in particular?
The same reason as above! I think it’s so amazing to see machine learning’s abilities to potentially find motion and morphological patterns of cells over time in order to make the cell populations more distinct. The power of this is so important because classifying phenotypic behavior can help oncologists accordingly target this behavior, especially in regards to metastasis.
Describe your experiences with research thus far in your career.
My experiences with research have always been testing of my ability to persist. When I first started research in high school, it was one of the most disorienting academic experiences I’ve ever had. In any place of academia, people are so knowledgeable and experienced with their field of research, so it’s easy to feel out of place and behind nearly all the time. I think that’s what made it really tricky, keeping a growth mindset while believing in yourself to contribute something meaningful. From this past summer’s research experience, I think the biggest skills I gained was gaining confidence in asserting myself in research related conversation. This came from presenting my research findings to my entire research group each week. Additionally, I was very lucky to have two post-doctoral fellows that were really open to having good, thorough discussions with me about my research work. So, I had the opportunity to truly tap into my curiosity and feel like it was meaningful.
Any tips or advice you have for students interested in pursuing undergraduate research?
I think the biggest piece of advice I have for an undergrad pursuing research is to be patient with yourself. Research will probably be one of the biggest learning curves you will come across since the people you work with are some of the smartest and dedicated people in their field. Don’t be taken aback by how much less you might know than them, and rather take it as an opportunity to really lean into learning about a topic really deeply and being truly curious about it. And always remember that everyone you work with was once at a point you were at. So, don’t count yourself out of doing something incredible and always believe in your ability to grow.
If you had unlimited time, money, resources, support, etc. what is something you would research?
How common disordered eating is among adolescents and young adults and how certain personal/family and societal factors contribute to them.
What meme lives rent free in your head?
Dula peep.
Favorite breakfast food?
Good buttermilk pancakes.
What’s the most interesting thing you’ve learned/read about/listened to this week?
In Neuro 202 this week, I learned that people with intellectual disorders tend to have shorter dendritic spine necks, meaning it takes longer for an electric current to pass through their neurons.
What is your most useless talent?
I can always tell when people have gotten haircuts no matter how little they got cut off. (And jaywalking).