
Richard Lee:
I'm a PhD student at MIT EECS. I work on acoustic sensing, computational manufacturing, and audio machine learning. My research is conducted at the Research Laboratory for Electronics with Prof. Mark Rau and supported by a Presidential Fellowship.
Before this I got my MA at Stanford, working with Takako Fujioka and Jeremy Dahl. I completed my BS EE at Columbia, advised by Paul Sajda and Nima Mesgarani.
My inspirations draw from concerts, cognitive science, compilers and architecture, and I write and make art in my free time.
rtlee at mit [.] edu
Publications
Google Scholar- 2026
Covert Perception of AI Adversely Impacts Team Performance and Changes Physiological Dynamics Despite Human-Level AI Competence
Y Qin, RT Lee, P Sajda
npj Artificial Intelligence
- 2026
Audio-Tactile Association Improves Pitch Perception in Listeners With and Without Cochlear Implants
A Hodges, M Fitzgerald, L May, RT Lee, R Goldsworthy, T Fujioka
Brain Research
- 2025
Physiologically Informed Predictability of a Teammate's Future Actions Forecasts Team Performance
Y Qin, RT Lee, W Zhang, X Sun, P Sajda
iScience 28 (5)
- 2026
MOV-AAD: A Large-Scale Multimodal Dataset for Dynamic Auditory Attention in Naturalistic Listening
X He, V Choudhari, T Spratt, A Raghvan, R Lee, N Mesgarani
Interspeech
- 2024
Pupil-Linked Arousal is Predictive of Team Performance in a Virtual Reality (VR) Sensory-Motor Task
Y Qin, W Zhang, R Lee, X Sun, P Sajda
IEEE EMBC
- 2023
MaxPy: An Open-Source Python Package for Text-Based Generation of MaxMSP Patches
RY Liu, S Peterson, R Lee, M Santolucito
NIME
- 2022
Predictive Power of Pupil Dynamics in a Team Based Virtual Reality Task
Y Qin, W Zhang, R Lee, X Sun, P Sajda
IEEE VRW