Answer ALS Innovators of the Future Profile: Ashwitha Surabhi

In their senior year at Thomas Jefferson High School for Science and Technology in Northern Virginia, Ashwitha Surabhi and her project partner settled on a computational research project in the school’s neuroscience lab, intending to train a machine learning model to predict ALS symptoms early and classify frontotemporal dementia. Most of the comprehensive biomarker datasets their approach required were restricted to researchers with institutional credentials, which they did not have. “A lot of the information wasn’t available publicly, especially to high schoolers who didn’t have the research credentials to gain access to this data,” Surabhi said.

Searching online, the pair came across Answer ALS and its open data portal, Neuromine, and sent a cold email introducing their project. Dr. Terri Thompson at Answer ALS responded, helped them set up access, and walked them through the data. At Thomas Jefferson, Dr. Laura Locklear, the director of the neuroscience lab, helped them think through the research design. With access to Answer ALS’s gene and laboratory data, Surabhi and her project partner built data processing pipelines and trained machine learning models with the goal of predicting ALS and the presence of frontotemporal dementia. “Other data we found online wasn’t really comprehensive in what we wanted to do,” she said. The Answer ALS dataset gave them the volume and patient diversity they needed.

At the 2022 Answer ALS segment of the Packard Center at Johns Hopkins’ Annual Meeting, Surabhi presented the work to an academic audience and, for the first time, met researchers who were working on the same questions she wanted to study. “Seeing all the different researchers present on their different ideas really opened up a lot of pathways for me that I could pursue,” she said.

That experience shaped her path at Caltech, where she enrolled in Computational and Neural Systems and began with research on wearable biosensors in Wei Gao’s lab. At Dr. Brian Lee’s lab at the Keck School of Medicine of the University of Southern California, she analyzed stereoelectroencephalography data from epilepsy patients to trace seizure propagations and helped design an experiment to predict how surgical resections in different parts of the brain affect a specific patient’s memory. In the summer of 2025, she joined the Sensorimotor Bionics Group at the University of Chicago Pritzker School of Medicine, where she ran sessions with brain-computer interface participants and watched patients with implants regain sensation in their fingers. The work she is doing now, focused on restoring movement and sensation, returns her to the questions that drew her to ALS as a high school senior. She plans to pursue an M.D.-PhD.

Surabhi traces her own path back to the moment when Answer ALS treated a cold email from a high school student as one worth answering. The experience of working with real patient data gave her something she could not have gotten any other way: an understanding of how data is messy, how processing it is its own discipline, and how much she learned by working inside a project rather than simply reading about one. She wants that experience for the students who come next, and she is thinking about how to help create it.

Answer ALS has kept Neuromine publicly accessible since its launch, making patient data available to researchers at any institution. Surabhi wants more students to know these resources exist and is thinking about how to help direct them toward it. Her advice to them is direct. “No dream is too big,” she said. “You shouldn’t feel limited by anything. Just send that email out, just reach out to the person.”