Yash, thank you for participating in our OneNeuro Students Profiles. Please tell us about your academic journey thus far.
I’m a second-year PhD student in the Department of Cognitive Science, where I use deep neural networks to explore how the brain processes visual information. My background is in computer science, having completed my undergraduate studies. After graduation, I worked as a software developer at Amazon. Still, my passion for research led me to leave that role and pursue a year-long research internship at the Gatsby Computational Neuroscience Unit at UCL. There, I worked on a project focused on learning algorithms in the brain. Before starting my PhD, I spent time at the HHMI Janelia Research Campus in Ashburn, where I modeled learning behaviors in flies using behavioral data.
In my PhD, I’m following the computational cognitive science track, which emphasizes computational modeling rather than experimental work like fMRI recordings. Cognitive science is incredibly interdisciplinary, merging fields like neuroscience, computer science, linguistics, psychology, and philosophy. What I find most exciting is the diverse set of skills developed through this field—these skills can be applied to a wide range of professions, not just one specific area.
What made you choose Johns Hopkins?
I was drawn to the cognitive science program and am eager to explore how research can be applied to healthcare during my PhD. While I don’t have direct experience in healthcare, I’ve mentioned my desire to make an impact, and I see significant potential in applying my AI knowledge to the field. Although my healthcare expertise is limited, I believe Hopkins would provide an excellent environment for pursuing this, especially through collaborations with the medical campus. My ideal PhD experience would involve developing an algorithm, testing it through clinical trials, and ultimately deploying it in practice.
Since you’re in the early years of your PhD work, who are your collaborators—students and faculty?
I’m primarily working with Mick Bonner and fellow PhD students in our lab, which I find very rewarding. Being part of a smaller lab allows me to spend more time with my PI and engage deeply with our research’s analysis and finer details, offering a rich learning experience. Our lab collaborates closely with Leyla Isik from the Cognitive Science department and Brice Menard from the Physics and Astronomy department. The main focus of our lab is understanding visual representations in the brain through deep neural networks and statistical methods.
Who or what has inspired you?
Tim Lillicrap at Google DeepMind is not only a prominent figure in the field as a researcher but also incredibly kind. When we worked together, he took the time to meet me at my level, patiently teaching and guiding me despite my lack of experience. He embodies the kind of PI I aspire to be, and what has been most inspiring is learning how to mentor from him.
Outside of science, my father has also been a major source of inspiration. He taught me valuable lessons about being a good person and navigating life with the right mindset.
What are your hobbies?
I have a great passion for sports. I was very active during my undergraduate years and played badminton and squash regularly. I also love running and cooking. Being Indian, I deeply appreciate the diversity of Indian cuisine, with its countless options and unique techniques. It is also very calming (unless my wife is with me in the kitchen :P). One of my favorite dishes to cook is paneer (cottage cheese).
Bonner Lab at Johns Hopkins University: https://www.bonnerlab.org/
Image, linked to paper: Model based inference of synaptic plasticity rules
