My broad research interests are in examining the cognitive-level organization of memory in the brain, identifying the principles behind them, and applying such principles to improve memory management in computer systems. Currently, I am investigating how theories of pattern recognition and recall from cognitive neuroscience can inspire better prefetching at all levels of the computing stack. The overall goal of my work is to find solutions to computational, storage, and learning constraints of deep learning techniques that serve as obstacles to their use in real-world computer systems, perhaps with the use of cognitively rather than neurobiologically-inspired learning models.
Prior to my Ph.D., I obtained bachelor's degrees in both Computer Science and Mathematics from Rutgers University. There, I also worked with Prof. Bhattacharjee at Rutgers University on HALO, a flexible architecture for implantable Brain-Computer Interfaces (BCIs).
I am a recipient of the NSF Graduate Research Fellowship.
B.S in Computer Science, Mathematics [2017 - 2021]