Meet CTC: Andrew Walker

Andrew Walker Lab

May 28, 2020 --  A Twin Cities area native, Andrew Walker is an undergraduate student in the Gagliardi group. He recently completed his second year at the University of Minnesota (UMN), majoring in computer science with minors in math, management, and Chinese. 

Andrew is working on a project applying machine learning within the Gagliardi group. With the project, he is learning how to effectively apply machine learning methods and about the importance of understanding the data that the machine learning is being done on. Data science can seem as straightforward as feeding data into models, but to get good results, it's helpful to have a sense of domain knowledge, or an understanding of the realm the science is being conducted in. While working with machine learning, he also learns about the chemical world. However, as a computer science student, he focuses more on computer science applications rather than the chemistry itself. “In my time in the lab, I’ve learned as much about the different ways I can utilize Python as I have about chemistry, if not more.” 

The goal of this type of project is to use machine learning techniques to bypass expensive computations by predicting values instead of computing them. Machine learning is being applied to a lot of research areas. Andrew is especially excited about it being successfully utilized in so many different fields, even those that don’t seem like a computer would be able to make sense of. For example, machine learning is being applied to linguistics, computer vision, and speech recognition. A lot of the success of machine learning in these areas come from redefining problems in a new, not immediately obvious way.

He does all of his coding in Python notebooks, including scripting, mathematical modeling, and visualization. He says he has found that “there’s always a tool in the Python toolbox to help answer a problem at hand.” Specifically, he uses NumPy (a computing package), pandas (a data manipulation package), and scikit-learn (a data science package). He also utilizes data generation and data collection packages like PySCF. With these, he codes basic send and receive commands in order to get his intended data. “I do most of my science work with the data once it's already been generated. My research focuses more on data analysis than the data generation.”

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Andrew’s favorite part about the UMN campus is how quickly he can travel by bike. He says, “my commutes are fast, and it’s no problem going from East Bank to West Bank, or getting to a new building if I want a change of scenery while studying.”

How did you become interested in studying chemistry, and what gets you the most excited about your field?

A prominent memory of mine is my brother and I watching Nova’s “Making Stuff” series after school. Since then, I’ve always been drawn to materials science and engineering. What makes me most excited about chemistry is that real, physical meaning can be understood without needing to always rely on experimental results. The fundamental causes of physical phenomena can be described by looking at the math and models. I like that research projects in computational chemistry labs are focused on finding new chemicals or methods in order to accomplish difficult tasks efficiently, guiding the efforts of discovery.

Why did you choose the University of Minnesota, and what led you to join your research group?

I have no singular reason for choosing UMN. A number of factors influenced my decision: the familiarity of the campus and surrounding areas, the proximity to home, the practicality, and the quality of education. I didn’t do a ton of research on the University before I applied; it just felt like the obvious choice. I’m glad to say that over the course of the past two years, UMN has become my home and I’ve had a terrific undergraduate experience so far.

I became interested in the Gagliardi Group when I took CHEM 4502: Introduction to Quantum Mechanics and Spectroscopy with Prof. Gagliardi. Towards the end of the semester, I was looking for ways to incorporate both my computer science and chemistry interests in research. During a meeting with Prof. Gagliardi, I learned that there was a project in the group working on machine learning applications to chemical computation problems. I got a feel for both the chemistry/physical modeling side as well as the computer science/statistical modeling side of the project. Working on the project also helped me choose to major in computer science after discovering I was more drawn to the computer science side of the research rather than the chemistry.

You’re an author on a recent publication. What was it like undertaking this large project as an undergraduate?

I enjoyed being part of a coordinated effort with multiple people. My school assignments have been individual projects to be done in two weeks, with the approach outlined by the professor. There's very little independent decision making required. With this project, there wasn’t a predefined "right way" to do it, and everyone was working on different pieces that had to come together. Meetings were interesting because even if I didn't always know what was going on in parts of the project I wasn't working on, it was fulfilling to see the project progress and evolve week by week. 
 

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What do you enjoy most about your research?

I like that the research is so open-ended. When I was focusing on the chemistry topics early in my work, there was a vast ocean of knowledge I was just beginning to navigate. On the computer science side, there has also been so much to learn. It’s daunting to know that there’s so much that’s unknown to me and more so, still unknown to humanity. I’m glad I can research what interests me most and that the others in the lab are there to support me on my journey towards understanding. 

What are you passionate about?

I’m most passionate about trying to tackle environmental and energy problems. Industrial chemical processes and human activity have done a lot of harm to the environment and redirecting chemistry research will help make us more sustainable.

What are you most proud of about your academic career so far, and what’s one thing you’d like to achieve in the future?

It took me a while to ultimately decide what to major in, but I’ve been happy with my decision to pursue computer science, while also finding ways to apply it to chemistry. Although it took me a while to decide my major, the time allowed me to dabble in many potential interests. In the future, I’d like to understand a topic well enough to where I feel comfortable sharing my work in a publication.

What other activities are you involved with on campus?

I’m involved with the Chinese American Student Association (CASA), last year as the External Vice President, and this upcoming year I’ll serve as president. Through CASA, I’ve found a sense of home and community through a shared experience with others. I’ve become more comfortable embracing my Chinese American identity instead of hiding it. I also share it with others in the university community. We host events on a variety of topics, ranging from cultural to educational to activist, in order to promote diversity and understanding on campus. If you’re interested, stop by an event or ask me more!

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What’s the best piece of advice you’ve received?

It feels like there’s a sense in computer science that you can’t succeed unless you’ve been coding since you were in elementary school. Even though I enjoy the coursework and subject of computer science, I sometimes find myself worrying about how I compare to others.

The advice I remind myself of is: do what you enjoy most and don’t compare yourself to others. Instead, let the feeling of growth and excitement for a topic guide you. Unnecessarily stressing by unfairly comparing yourself to others is unproductive and destructive. Instead of looking at someone else and thinking “I still have so far to go,” think about how far you’ve come since you’ve started, and think about how you improve every day. It’s more sustainable to think about how far you’ve come rather than to stress about feeling behind. 

What are your plans for after graduation? How will your involvement in your research group help you achieve this goal?

I don’t have a straightforward goal in mind, but until I graduate, I will continue to push myself to grow and better understand the world around me. I hope to make a positive impact on the world and expand our collective understanding of how the world works.

My involvement in the Gagliardi group has helped me understand that the research world is very collaborative and that group members want to see each other’s best work and help each other realize their potential. When I share my thoughts and goals with the other members, they give feedback and help me improve. Everyone is very supportive of each other.