Four Tartans Among 2021 Goldwater Scholars
Juniors Esther Bedoyan, Ethan Lu, Arvind Mahankali and Jinhyung (David) Park are among the 410 recipients of this year’s award, chosen from a pool of more than 5,000 college sophomores and juniors.
CMU is eligible to nominate four students each year to be Goldwater Scholars, and this is the second consecutive year where all four nominated students have been chosen.
“The Goldwater Scholarship is a superlative award that recognizes high achievement and depth in research. That our four nominees were all selected not once but twice consecutively — in 2020 and 2021 — is remarkable and to be celebrated,” said Brittany Allison, CMU’s assistant director of undergraduate research and national fellowships, and Goldwater campus representative. “This accomplishment signifies the exceptional research and academic talents that our students work so hard to cultivate and serves as a testament to the outstanding mentorship that they receive from the faculty and staff at CMU and beyond.”
The scholarship, offered to students in the natural sciences, engineering and mathematics, provides up to $7,500 annually for tuition, fees, books and housing.
Esther Bedoyan
Esther Bedoyan is a junior majoring in electrical and computer engineering (ECE) and biomedical engineering (BME) with a minor in Chinese studies.
“Ever since pursuing fascinating research projects nestled in the intersection of ECE and BME at Carnegie Mellon, the Center for the Neural Basis of Cognition and Case Western Reserve University, I’ve been inspired to pursue a Ph.D. in device sciences research,” Bedoyan said. “My experience at CMU also showed me that I really enjoy learning, whether through classes or hands-on research. I am excited to continue exploring my curiosities and passions through graduate school and beyond.”
Since last fall, Bedoyan has been conducting research on developing a technique that removes electrical interference from electrophysiology data in the lab of Maysam Chamanzar, an assistant professor of electrical and chemical engineering.
Upon graduation, she plans on completing the Integrated Masters Bachelor Program at CMU, then pursuing a Ph.D.
“I look forward to continuing to expand my understanding of modern micro- and nanodevices, especially as they relate to biomedical applications, and directing an independent Ph.D. project focused on my own research interests.”
Ethan Lu
Ethan Lu is a junior in the Mellon College of Science studying mathematical sciences. Lu is a member of the Geometry Collective at CMU, which is a group of researchers interested in geometry and computer science.
Lu has used his mathematical skills to help others, working as a tutor and faculty at various math camps, as well as volunteering for CMU’s Informatics and Mathematics Competition and Princeton University’s Mathematics Competition.
“I enjoy studying mathematics because of how it can combine both abstractness and practicality, which is something I find really beautiful,” Lu said. “I’m interested in analysis research because of how it can leverage extremely powerful and advanced theoretical results to solve real-world issues that people care about, whether that be in computer graphics/simulation or in fluid dynamics and partial differential equations.”
Arvind Mahankali
Arvind Mahankali is a junior studying computer science and considering a second major in mathematics. His research has focused on the theoretical underpinnings of machine learning. For example, gradient descent works well as an algorithm for training neural networks, but there isn’t a complete theoretical explanation of why, Mahankali said.
“Understanding those types of questions in a more theoretical way might be useful in improving the safety of these algorithms,” Mahankali said. “It is interesting and practically important, especially with regards to the safety of neural networks.”
During the Freshman Immigration Course, which is designed to introduce first-year students to computer science at CMU, Mahankali said he realized the importance of developing the theory behind machine learning when learning how adversarial examples can disrupt the intended function of an algorithm. When a neural network — designed to identify the type of animal in a given picture — is fooled into thinking a panda is a banana, Mahankali wants to understand why that is.
“These questions seem pretty important to me,” Mahankali said. “Safety is critical in certain applications. If self-driving cars are able to be fooled, then we might be in trouble.”
Jinhyung Park
Jinhyung Park, a junior, studies artificial intelligence (AI) and has worked on computer vision projects related to autonomous vehicles. He has sought to create better models of the real world by fusing 2D and 3D inputs into a more robust image. This not only helps self-driving cars see better but improves how robots interact with their surroundings.
“I’ve still only scratched the surface of what computer vision has to offer,” Park said. “If AI systems have a better understanding of 3D inputs, they can have a better understanding of the real world.”
Park said it was during his sophomore year that he decided to pursue research. He would read a paper and start thinking how he could improve upon the idea or fuse it with another field.
“There was so much out there, and there was so much that people were working on, and I just wanted to find out more,” Park said. “I wanted to read and not just observe this progression, but I wanted to be part of it.”