People

Amelia is a PhD student in the Harvard-MIT Program in Health Sciences and Technology. After receiving her B.S. in Biopsychology from UC Santa Barbara, she worked as a research assistant processing and analyzing PET data for clinical dementia research at UC San Francisco. Her current research is focused on quantifying brain tissue motion and its relationship to cerebrospinal fluid flow using motion-encoded MRI. She is co-advised by Dr. Jonathan Polimeni at Stanford University.

Erin is an MEng student in the Department of EECS. She received her BS from MIT with a double major in Artificial Intelligence & Decision Making and Brain & Cognitive Science. She is interested in machine learning applications to neuroscience. Her projects with the Lewis Lab include applying machine learning to fMRI data to automatically segment cerebrospinal fluid inflow signal, and to predict arousal state transitions in the ascending arousal network.

Merel has a background in Psychology, Cognitive Neuroscience and Dementia studies. She earned her Ph.D. at Maastricht University in the Netherlands, where she applied high-field MRI to study the brain’s waste clearance system in relation to Alzheimer’s disease. At MIT, in the Lewis Lab, she now investigates this system during wakefulness and sleep using EEG and diffusion MRI. Her work is supported by the Dutch Alzheimer Society (Alzheimer Nederland).

Dragana has a background in biomedical engineering and cognitive neuroscience. She completed her PhD at the Paris Brain Institute, where she used multimodal neuroimaging and machine learning to investigate states and disorders of consciousness, followed by a postdoctoral position studying local sleep-like activity during sleep deprivation. At MIT, in the Lewis Lab, she studies sleep-wake regulation in humans using multimodal neuroimaging (high-field fMRI, EEG, physiological signals) combined with novel AI methods. She is supported by the MIT-Novo Nordisk Artificial Intelligence postdoctoral fellows program.

Trang is a Ph.D. student in the Brain and Cognitive Sciences program at MIT. She received her B.A. in Biochemistry and Math from Mount Holyoke College, where she worked on research related to protein misfolding in neurodegenerative diseases. After graduation, she worked as a research assistant studying dendritic contributions to cortical computations in mice and humans. Her current interests include aging, neuromodulation, and brain-body interactions.

Adiya earned a Ph.D. in Bioengineering from the University of Pittsburgh, where she investigated how inhibitory neurons influence network activity and regulate cerebral blood flow. Using multiphoton and optical imaging techniques alongside EEG recordings in mice, she examined brain activity while selectively manipulating neuronal subpopulations with optogenetics and chemogenetics. Now, as a postdoctoral researcher in the Lewis Lab, Adiya aims to integrate fNIRS and fMRI to explore how neuromodulatory nuclei shape neurovascular coupling in the cortex and across the brain.

Aaron is a PhD student in the Electrical Engineering and Computer Science program at MIT. He obtained B.S. from University of California, San Diego in 2020 with in Electrical and Computer Engineering. He also received M.S. in Electrical and Computer Engineering from Carnegie Mellon University in 2023 before coming to Boston. Aaron's past experiences span both hardware and computational research for neuroscience. He previously worked with Dr. Maysam Chamanzar at CMU to create automated propagation loss characterization system for optical neural probes. Afterwards, he worked with Dr. Michele Insanally at University of Pittsburgh to study the synaptic origin of behavioral flexibility through spiking RNN models. Aaron aims to combine both hardware and software research to improve neuromodulation in humans, and he is currently working on refining stimulation algorithm for slow wave sleep.

Gabby is a PhD student in the Electrical Engineering and Computer Science program at MIT. She graduated from Johns Hopkins University in 2024 with B.S. from the Biomedical Engineering and Computer Science Departments, as well as an M.S. in Biomedical Engineering. Previously, she worked with Dr. Adam Charles in the Neural Signals and Computation Lab at JHU, where she worked with evaluating and improving spike deconvolution algorithms for calcium neural signal imaging. Gabby’s research interest is in using computational techniques to extract biological relevance from neuroimages, and she is currently investigating the predictability of CSF flow from EEG.

Hannah recently graduated from Johns Hopkins University with a degree in neuroscience and cognitive science. As an undergraduate, she worked at the Neuroplasticity and Development Lab, investigating how sensory loss affects brain function and cognition. She completed a thesis project on English braille letter recognition. Hannah also joined the Poverty and Inequality Research Lab, where she examined the systematic connections among socioeconomic factors, housing, health, and educational attainment. Hannah is broadly interested in how experience shapes the brain. She hopes to gain proficiency in neuroimaging techniques and learn more about neural circuits and functional brain connectivity related to sleep.

Danlei received her Ph.D. in Psychology from Northeastern University focusing on the functional involvement of the human brainstem in cognition using ultra-high field fMRI. Her general interest is in investigating whole-brain neural dynamics that regulate the autonomic systems over time, especially during different levels of arousal. Currently, she uses fast, high-resolution neuroimaging, measures in both central and peripheral physiology, and computational approaches to explore the relationship between changes in BOLD signals, cerebrospinal fluid flow, and peripheral physiological patterns across a spectrum of arousal states.

Brandon recently graduated from Dartmouth College, where he studied cognitive science with a focus on human cooperation. He conducted research at the PhilLab on causal reasoning using online game theory studies and physics simulations, and he wrote his thesis at the SCRAP Lab on social signal prediction using machine learning techniques. Brandon hopes to pursue clinical psychology and study methods that allow practitioners to predict the most effective treatment for a patient. Broadly, he is interested in learning more signal processing, machine learning, and brain state transitions.

Banban recently graduated from UNC Chapel Hill in neuroscience major and philosophy minor with Honors and Honors Carolina laureate. She worked in Dr. Charlotte Boettiger’s lab and finished an independent honor thesis on early binge drinking’s effect on value-based attentional bias as well as neural activity in the caudate. In her free time, she enjoys practicing karate, hiking, and writing sci-fi.