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ASU graduate stands out as gifted student, researcher and yo-yo artist


Photo of Nicholas Ho

Nicholas Ho will receive a bachelor's degree in computer science and mathematics with honors from Barrett, The Honors College at ASU.

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April 28, 2023

Editor’s note: This story is part of a series of profiles of notable spring 2023 graduates.

Nicholas Ho is a gifted student, researcher and yo-yo performer who has been named a 2023 Outstanding Graduate for Research by Barrett, The Honors College at Arizona State University.

Ho, a computer science and mathematics major, has carried a 4.0 GPA and engaged in high-level research throughout his undergraduate career. He will graduate with a bachelor’s degree with honors from Barrett in May.

He received the New American University President’s Award; the Wojcik Family Research Fellowship, which supported his research at the ASU Biodesign Institute; the ON Semiconductor Engineering Scholarship from the Ira A. Fulton Schools of Engineering; and Barrett Honors Thesis Funding, which helped fund his travel to New Orleans to attend and present at the Neural Information Processing Systems 2022 machine learning conference.

In 2019, Ho joined the computational biophysics laboratory run by Abhishek Singharoy, assistant professor in the School of Molecular Sciences.

Ho, who was one of the youngest lab members, studied Hexokinase 1 proteins using molecular dynamics simulation software called NAMD and worked on projects with graduate students, according to Singharoy.

“He spent a significant amount of time self-studying the physics and chemistry for this neurobiologically relevant system. Even though his background is in computer science and mathematics, his capacity to learn biology and physics is immense,” Singharoy said, adding that Ho’s contributions will be the basis of a publication.

“One of Nic’s strengths is his capability to not only propose his own independent research topics, but also study necessary theoretical background and lead his own research projects,” said Singharoy, who served as director for Ho’s honors thesis, which focused on using reinforcement learning in tandem with existing tools for biological dynamics.

“His thoroughness and curiosity as a researcher is an impressive trait that makes Nic stand out among his peers.” 

In addition to research at ASU, Ho conducted research in Carnegie Mellon University’s Department of Data Science and Statistics in summer 2021, where he developed a novel statistical framework for learning dynamics in soccer games and presented his results at the Carnegie Mellon Sports Analytics Conference.

Ho also did research in Harvard Medical School’s Department of Biomedical Informatics, where he used advanced machine learning tools to integrate biological and clinical data into drug discovery. He collaborated with a graduate student to develop machine learning models to predict the adverse side effects of taking multiple drugs.

While busy with lab work and his studies, Ho took time out to serve as an executive board member of the ASU Machine Learning Club and a member of the Mathematical Organization for Rehumanizing Education Club.

Ho's creativity in research is matched by his skill with the yo-yo. He taught himself intricate tricks and practiced them during study breaks. He performed for amazed and amused audiences as part of the Barrett student talent show during Family Weekend in 2021 and 2022.

We asked Ho to reflect on his experiences as an ASU undergraduate. Here’s what he had to say.

Question: What was your "aha" moment when you realized you wanted to study the field you majored in?

Answer: My special moment happened in high school, when I watched a YouTube video on using machine learning for protein folding. I loved the challenges and intricacies of biological problems, as well as the creative freedom of computational programming. There were so many crazy advancements taking place with computer vision and natural language processing, I couldn’t help but wonder how these incredible tools could be used in the biomedical space. Those were thoughts I had five years ago, and it’s amazing to see how much machine learning in the biomedical space has evolved since then.

Q: What is something you learned while at ASU — in the classroom or otherwise — that surprised you or changed your perspective?

A: While I conducted research at the Biodesign Institute, the sheer complexity and interdisciplinary nature of computational biological problems kept surprising me. Coming from a background of computer science and mathematics, I kept learning and relearning that interdisciplinary problems in computational biology required extensive collaboration between various disciplines and experts.

Q: Why did you choose ASU?

A: A massive amount of research and resources, brand-new facilities such as the Biodesign Institute, a large campus, very nice honors college dorms and the support of a great scholarship.

Q: Which professor taught you the most important lesson while at ASU?

A: I really cannot narrow it down to a single professor or one class. I am greatly indebted to many kind individuals who had a profound influence on my trajectory. Meeting Professor Huansheng Cao in my freshman year helped me to get involved in research very early on. Professor Abba Gumel fostered my interests in mathematics and pushed me to add as many math courses as I could. Professor Abhishek Singharoy mentored me for my honors thesis project and encouraged me to always ask questions — to trust but verify everything I could. Last but not least, Professor Ross Maciejewski has taught me how to lead inspiring group projects through my senior capstone.

Q: What is the best piece of advice you would give to students?

A: Get involved with research as early as you can, and try your best to find a good mentor. Finding a good mentor is key for having a productive academic experience.

Q: What was your favorite spot on campus, whether for studying, meeting friends or just thinking about life?

A: I have many fond memories of the Great Court lawn at Barrett, The Honors College in Tempe. It was a beautiful place to just hang out with my friends and on occasion do some work.

Q: What are your plans after graduation?

A: I plan to begin my PhD studies in computational biology at Carnegie Mellon University through the Carnegie Mellon/University of Pittsburgh computational biology program. In this joint program between CMU Computer Science and the Medical School, I plan to take the opportunity to research cutting-edge machine learning to solve challenging biological problems and eventually bridge these discoveries to medicine. I believe my unique experiences in both mathematics and computer science as an undergraduate as well as my experiences at the Biodesign Institute, Carnegie Mellon University and Harvard Medical School, set me up in a great position to pursue my PhD in this area.

Q: If someone gave you $40 million to solve one problem on our planet, what would you tackle?

A: This is a difficult question for me, because there are so many challenging and fascinating problems in biology I would like to tackle. At this moment, I would like to do more work on machine learning for genetic engineering and spatial transcriptomics to better understand disease mechanisms and develop interventions.

Barrett student Rebecca Smalley contributed to this story. 

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