Meet students researching implants, manufacturing and more

What made you want to get involved in this program? Why did you choose the project you’re working on?

My research interest started when I took CSE 475 Foundations of Machine Learning at ASU, which opened my eyes to the power of AI in education. Later, I got the chance to work with Professor Huan Liu, and that experience shaped my passion for making models more transparent and trustworthy. I chose EduCBM, which is the name of my project, because I want to reduce the uncertainty in automated grading and give students and educators clearer, more interpretable feedback.

How will your engineering research project impact the world?

EduCBM tackles one of the biggest problems with AI in education — its “black box” nature. By making grading models interpretable, it ensures fairness and builds trust among students, instructors and institutions. In the long run, I see it helping educational systems adopt AI more responsibly and improving the way learning outcomes are measured.

What has been your most memorable experience as a student researcher in this program? Did you have a particular “aha!” moment during your project?

My most memorable moment was when I first saw how concept bottlenecks could explain a model’s decision in plain terms rather than just numbers. It felt like I had unlocked a window into how AI “thinks.” That moment confirmed to me that interpretability isn’t just a research goal — it’s a necessary bridge between technology and people.

Have there been any surprises in your research?

Yes, I was surprised by how often large language models can sound convincing but still give uncertain or inconsistent results. It was eye-opening to realize that even powerful models need additional layers, like concept bottlenecks, to make their outputs meaningful and reliable in high-stakes fields like education.

How do you see this experience helping with your career or advanced degree goals?

This project has deepened my interest in research and prepared me for graduate studies in machine learning and AI. It gave me hands-on experience in combining theory with practical applications, which I believe will help me pursue advanced degrees and eventually contribute to building trustworthy AI systems in both academia and industry.

What is the best advice you’ve gotten from your faculty mentor?

Professor Liu told me that research is not just about solving problems but about asking the right questions. That advice helped me shift my focus from chasing results to really thinking about why a problem matters and how my work can make a difference.

Why should other students get involved in this program?

I think FURI is one of the best ways to explore your passions beyond the classroom. It gives you the chance to ask big questions, work closely with faculty and build skills that carry forward into your career or graduate studies. More importantly, it shows you that your ideas can have a real-world impact even as an undergraduate.

What made you want to get involved in this program? Why did you choose the project you’re working on?

I was part of the Biocomputing Scholars Program and had already become familiar with [Dr. Forrest’s] project over the past couple of months. I decided to apply to FURI because I wanted to dive deeper into research and get more hands-on experience. I chose this project specifically because it’s in a domain I hadn’t worked in before, and I was excited about the opportunity to learn something completely new.

How will your engineering research project impact the world?

This work can have a significant impact by making software development more reliable and efficient. By automating the detection of bugs, it can reduce human error, save developers valuable time and improve the overall quality of software. In critical systems, faster and more accurate bug fixes can lower costs and ensure that technology works as intended for users everywhere.

Have there been any surprises in your research?

Yes, there have been some surprises. I was replicating results and did not anticipate it would take this much time. It ended up taking almost three to four times longer than I expected. This taught me to be more patient and helped me improve my time management by planning better for unexpected challenges.

How do you see this experience helping with your career or advanced degree goals?

Through this research, I’ve learned how to use new technologies that I wouldn’t have gotten to work with in class. I’ve also learned from my faculty mentor and postdoctoral mentor, who both bring a lot of experience from research and industry. Their guidance, along with the technical skills I’ve gained, will really help me as I start my career.

Why should other students get involved in this program?

Students should get involved with FURI because it allows you to go beyond the classroom and explore real-world applications of what you learn in class. You get the chance to work on projects that are not covered in coursework and build valuable skills that prepare you for future internships and careers. Through FURI, you’ll build connections with faculty mentors who can support your academic and career goals.