Emma Ricci-DeLucca
Portrait of Emma Ricci-DeLucca

I am a current Engineering PhD candidate at Dartmouth College, advised by Prof. Liz Murnane. Prior to that, I earned my Master's in Engineering degree at Duke University, and my Bachelor of Science at Swarthmore College.

My research focuses on understanding the gap between what AI can predict from wearable data and what clinicians can act on, with the goal of designing more effective human-AI collaboration in healthcare. My thesis focus has been on AI-assisted sensemaking of multimodal wearable data, spanning personal mental health tracking, ML-based depression prediction in postpartum populations, and dashboard design for care providers.

I apply mixed-methods research grounded in scientific and epistemological rigor, combined with design synthesis, to build systems people can understand, question, and act on.

Experience

  1. 2022–now
    Dartmouth College, HCI PhD candidate Elizabeth Murnane
  2. 2022–2023
    FemTechnology Summit, Intern Oriana Kraft
  3. 2021–2022
    Duke University, MEng in Biomedical Engineering Paul Fearis, Eric Richardson
  4. 2022
    Siemens Healthineers, Global Business Development Intern Cam Atkins, Kelly Berchuck
  5. Summer 2019
    University of Pennsylvania, Undergraduate Student Researcher Charlotte Pfeifer, Michael Tobin, Dennis Discher
  6. 2017–2021
    Swarthmore College, BS Engineering & BA French and Francophone Studies Vidya Ganapati, Matt Zucker, Carina Yervasi

Research

Research pipeline diagram

Projects

Mechanoacoustic wearable for physiological event detection
Mechanoacoustic wearable for physiological event detection Designed and prototyped wearable device combining inertial, mechanoacoustic, and thermal sensing to detect bruxism. Identified optimal sensor placement strategies for capturing jaw-movement signatures associated with nocturnal grinding. Built custom firmware and BLE data streaming, validating sensor performance through multi-channel measurements.
Emergency Department management solution
Emergency Department management solution Conducted ethnographic research in hospital emergency department, observing workflows and clinician-patient interactions. Developed low-to-mid fidelity prototypes of platform, validated through iterative feedback sessions with clinical stakeholders.
Biomedical circuits & systems
Biomedical circuits & systems Design of electronic instrumentation and measurement systems (ECG-based heart rate monitor, electronic stethoscope, automatic blood pressure monitor, blood oxygenation monitor)
Advanced Data Visualization
Advanced Data Visualization JavaScript, HTML widgets, and dashboards, for the creation of dynamic and interactive visual narratives.