Signal processing & Artificial Intelligence for Time variant Health data
We are looking for fellow innovators and collaborators who share our mission
Join us now!
Our lab hires at multiple levels of experience: undergraduate, masters, doctorate and post-doctorate.
We’re Changing the Way the World Thinks About Personal Health
How can we better understand sleep, stress, & mental health, using data-driven tools?
Can passively collected lifestyle data quantitatively measure depression, stress & anxiety?
How does the timing of health-related interventions affect their efficacy?
Can we quantify the conditions and susceptibilities of the brain by measuring it's electrodynamic state?
Can we revolutionize clinical treatment plans by directly measuring the efficacy of medications in the brain?
We Develop Tools and Approaches That Enhance Our Ability to Discover New Digital Biomarkers & Phenotypes
How can we cluster multidimensional, multiscale, and multivariate, longitudinal time series data?
What approaches can we use to maintain prediction quality despite intermittently missing longitudinal data?
Which change point detection algorithms are most effective for interpreting smartphone/smartwatch/EEG data?
How does signal artifact affect the mathematical values of key nonlinear measures (e.g. entropy, RQA, etc.)?
How can we use deep learning methods to identify micro-activity in high-frequency longitudinal signals?
We are currently not hiring additional undergraduate students until Fall 2022. If you are enthusiastic, eager, and ready to learn, feel free to reach out!
No experience necessary.
Please introduce yourself via email and attach a copy of your CV/resume, and schedule for the semester.
We are not currently accepting additional Northeastern graduate students. For those who are passionate about innovating in the digital health space, stay tuned!
Our research requires a variety of different expertise, so if you interested in getting involved, please do not hesitate to reach out!
We are currently not hiring postdoctoral fellows, software developers or any support staff. Please stay tuned, as this may change in the future!