As a high school student, Jay Appaji was on the radar of multiple colleges.
They liked that he was an accomplished musician, having mastered the South Indian classical mridangam (“mrih-dun-gum”) by the time he was 13. They liked that he was performing in Texas and in India, and helping raise funds for music education in underprivileged communities in both countries. They noted that he received the 2013 Percussive Arts Society’s M&J Lishon/Franks Drum Shop national scholarship in his junior year, and the Texas Commission on the Arts Young Masters Award his senior year.
Then there was his interest in the sciences. He had already started doing research while still in high school, working with music cognition veteran Dr. Jay Dowling at The University of Texas at Dallas.
All of the colleges pursuing him offered him scholarships.
When Appaji thought about college, he wanted to major in music but he also wanted to study the sciences. “You can double major in music and the sciences at °ÄÃÅÁùºÏ²ÊÔ¤²â,” he says. “A lot of other schools, especially music schools, won’t let you double major. If you’re doing music, then you’re only allowed to do music and nothing else.”
He picked °ÄÃÅÁùºÏ²ÊÔ¤²â. The three scholarships offered by °ÄÃÅÁùºÏ²ÊÔ¤²â helped; Appaji is a Meadows Scholar, an °ÄÃÅÁùºÏ²ÊÔ¤²â Founders Scholar and a Discovery Scholar, the latter of which is an honor awarded to science and engineering students. He is pursuing two degrees at once: the 51-credit hour B.A. in music, and the 102-credit hour B.S. in electrical engineering.
He was also attracted to the school’s relatively small size. “I wanted to have good access to the professors and learn from them,” he says.
During his first year Music History class, he got to know Assistant Professor of Musicology Dr. Zachary Wallmark. Appaji learned that Wallmark was planning on starting a new music cognition lab, and he jumped at the chance to be part of it.
“I thought it would be a great opportunity to work with him,” he says. “I was able to help him set it up at the end of my first year. By the spring of my sophomore year I was able to administer the second part of the study I had started in high school. Mine was one of the first projects held in the new MuSci Lab.”
That was in 2016. The following year, Appaji would travel to his first professional conference to present his findings on memory for rhythmic patterns played on the mridangam.
Learning how humans encode South Indian classical rhythms into memory
Appaji’s research at °ÄÃÅÁùºÏ²ÊÔ¤²â concentrated on two things: memory, and the ability to determine similarity and differences between separate passages of unfamiliar music. The people surveyed (“subjects”) listened to musical sound bites played on a mridangam in the traditional Carnatic style of South Indian music, a style that is mostly unfamiliar to the Western ear.
“Having a passion for Indian percussion and rhythm in general, I was interested in understanding the techniques people’s brains use when learning and processing rhythm,” says Appaji. “After playing mridangam for nine years, most of what I play is pretty instinctive at this point, so I also wanted to understand what mechanisms my brain was using to make challenging aspects of the music become easier over time.
“I hoped to understand what features of South Indian rhythm were most memorable, as well as what effect cultural unfamiliarity had on recognition accuracy. Given what we know about the difficulties for humans to remember and perceive plain rhythm, I wanted to understand what effect the pitched nature of the mridangam’s sound had on encoding rhythms in memory.”
In the first experiment, the listener heard a sample, then a delay time—a short, medium or long delay—and then the listener would hear another sample. “The second sample would either be similar to or different from the original one, and the listener would then rate how similar or different the samples were,” says Appaji. “We had a rating scale, with ‘1’ as ‘sure same’ and ‘4’ as ‘sure different.’”
After the experiment, Appaji and Wallmark were surprised that the subjects were identifying the correct musical passage more accurately than they had expected, especially since the Carnatic musical style was an unfamiliar style. Dowling, Appaji’s research mentor from his high school days, collaborated with Appaji and Wallmark on the experiment’s analysis, and together they determined that a second experiment was needed.
“The second experiment was similar in design,” says Appaji. “The listener would hear a sample of rhythmic South Indian percussion, then, after clicking a button, they’d hear a random ordering of three additional samples: one similar to the original sample, one different, and one the same as the original sample.”
While the researchers expected the “same-different-similar” samples to impact the listeners’ accuracy, the subjects did well on that configuration, too.
“We found that recognition accuracy was highest when the original sample was in position one, and slightly decreased in position two and tailed off a bit in position three,” says Appaji. “The lowest accuracy rate we saw was around 75 percent, which is still really good.”
Previous studies in the music cognition field have primarily dealt with Western rhythm, says Appaji. “Given that South Indian classical music is a very complex rhythmic tradition, it serves to add a new area of study to the general body of cross-cultural music cognition and perception research,” he says. “Having an understanding of how humans encode South Indian classical rhythms into memory can lead to larger generalizations about certain universal rhythmic features.”
Research leads to conferences in London, California, Montreal
In summer 2017, Appaji was accepted for a month-long research internship at University of California San Diego Institute for Neural Computation. In the fall, he traveled to London for his first conference, the International Conference of Students of Systematic Musicology held at Queen Mary University. There, he met like-minded students studying music from computational, psychological, sociological and other non-traditional perspectives, and he started to learn how to present his findings in poster sessions.
L to r: Mary Lena Bleile (B.M. Performance/Cello ’18), Camille Van Dorpe (B.B.A. Finance and B.A. Philosophy ’20), Jay Appaji (B.A. Music and B.S. Electrical Engineering ’19) and Assistant Professor of Musicology Dr. Zachary Wallmark at the 2017 Society for Music Perception and Cognition conference in San Diego.
“The SysMus conference was a good first experience,” says Appaji. “I got a lot of good feedback.”
After that, he presented his findings from his memory for rhythmic patterns study at the Stanford Undergraduate Research Conference (SURA), followed by the International Conference for Music Perception Cognition in Montreal. “Montreal was really cool,” says Appaji. “It’s filled with experts from the field. It was great to be able to meet the researchers whose research I had read but whom I’d never met. And it’s great meeting your peers and exchanging research ideas, and getting their suggestions on your projects.”
On to Stanford internship
Back when Appaji was still in high school, he dreamed about someday being able to be part of Stanford University’s Center for Computer Research and Music and Acoustics. “CCRMA is colloquially known as Karma,” says Appaji. “It was something I always wanted to be a part of, maybe in undergrad or grad school. Close to the end of my sophomore year in college, I had reached out to some people there to see if they had any need for research assistance, but at the time, they didn’t. However, one person told me to be in touch with her for a possible opportunity in the next year or so.”
Appaji stayed in touch. By the end of his junior year at °ÄÃÅÁùºÏ²ÊÔ¤²â he was invited to come to Stanford over the summer of 2018 and be part of their research team.
“It was slightly different than the research I was doing here at °ÄÃÅÁùºÏ²ÊÔ¤²â,” he says. “The research was more in cognitive neuroscience and audiology. I learned what that kind of research entails, like the setup process for using EEG (electroencephalography) headsets. It’s a really meticulous process: You first have to soak the net and get all the electrodes hydrated, then you have to put it on the person, and then rehydrate the electrodes, make sure everything’s working correctly, thenyou can start the experiment. I also learned the analysis side, the computational methods that are used. As an engineer, I really appreciated being able to learn that, because being able to apply my engineering background was probably my favorite part about it.
“I think it was probably one of the best things that I’ve done, just from an overall perspective, life and career wise.”
Appaji will travel with the Stanford team to present at conference in Paris, France, September 23–27, 2018.
Read more about the °ÄÃÅÁùºÏ²ÊÔ¤²â Meadows MuSci Lab, °ÄÃÅÁùºÏ²ÊÔ¤²â Meadows Division of Music and °ÄÃÅÁùºÏ²ÊÔ¤²â Lyle School of Engineering. Learn more about and his music, upcoming performances and news coverage.
