I am a final-year Ph.D. Student at UC San Diego and Graduate Researcher in the Digital Health Technologies Lab under the supervision of Dr. Edward Wang. I am passionate about the intersection of human-machine interactions, engineering, and user-centered design. My research areas include Human-Computer Interaction (HCI), User-Centered Design, User Experience (UX), digital health systems, telehealth, AI and health sensing. My thesis aims to transform interactions between healthcare practitioners and their stakeholders in telehealth consultations through an AI-mediated patient triaging system.

I was a former UX research intern at Qualcomm, working towards usability testing and how to reduce the effects of cybersickness in extended reality (XR) devices, integrating between UX and engineering teams for better systems. In the summer of 2018, I was a research intern at Microsoft Research in the clinical sensing and analytics group, working on techniques for racially fair PPG sensing on wrist-worn devices.

 I am currently on the job market, seeking internship positions (Summer 2024) in research and full-time industry and foundation research positions (January 2025). Feel free to reach out if you want to discuss opportunities.

Breast pain is one of the most common reasons for breastfeeding patients to reach out to their providers, seeking ways to mediate their pain and solve the issue. Our pain assessment application allows the patient to solicit remote guidance from their provider (i.e., lactation consultant (LC)) by informing details about their pain and providing an image of the wounded area. An AI pipeline analyzes the image for a quality check and pre-determines the possible condition of the patient, reporting this data to the healthcare provider and providing the patient temporary guidance to mitigate the issue while the patient waits for the provider’s contact. At the same time, the LC receives patient reports in order of severity so they know who to prioritize first.

Accepted, to appear at CHI-EA 2024 

Current telehealth services help mothers seek Lactation Consultants (LCs) for breastfeeding support, where images help them identify and address many issues. Due to the disproportional ratio of LCs and mothers in need, these professionals are often overloaded and burned out. We investigate the effectiveness of a convolution neural network (CNN) in detecting healthy lactating breasts and six breastfeeding-related issues using only RGB images. Our goal is to assess the applicability of this algorithm as an auxiliary resource for LCs to manage their time more effectively, respond promptly to patient needs, and enhance the overall experience and care for breastfeeding mothers.

2023, [Under Review]

The limited adoption of Extended Reality (XR) Head-Mounted Devices (HMDs) due to device quality and cybersickness highlights the need for a deeper understanding of their impact on User Experience (UX). Previous studies evaluated visual perception, usability, and technical interventions as discrete elements. While some gather only quantitative measures, others gather qualitative measures at a more surface level. We propose a within-subjects mixed-methods evaluation to address these gaps to investigate hardware and software influences on user experience and task performance while wearing Video See-Through (VST) HMDs. This evaluation’s insights inform features that can improve device quality and user adoption across various domains.

2023, [Under Review]

BPClip is a low-cost 3D-printed smartphone attachment for blood pressure monitoring that utilizes a smartphone's camera and flashlight. This device aims to make blood pressure measurement more accessible, particularly in resource-limited settings. By promoting the use of this affordable technology, the intention is to facilitate better management of hypertension and overall health for individuals worldwide.

2023, Nature Scientific Reports

Lactation consultants (LCs) positively impact chestfeeding rates by providing in-person support to struggling parents. In Brazil, LCs are a scarce resource and in high demand, risking chestfeeding rates across many communities nationwide. The transition to remote consultations during the COVID-19 pandemic made LCs face several challenges in solving chestfeeding problems due to limited technical resources for management, communication, and diagnosis. This study investigates the main technological issues LCs have in remote consultations and what technology features are helpful for chestfeeding problem-solving in remote settings.

2023, Frontiers Digital Health

Long-term breastfeeding has been shown to exhibit several environmental benefits and health benefits for both the mother and baby. Despite the known advantages, several mothers choose not to maintain breastfeeding long-term. How long a mother breastfeeds is heavily influenced by lactation and latching, and so the mother’s critical point of support is the lactation consultant (LC), who guides and provides instruction for creating a more positive breastfeeding experience. Empowering lactation consultants with methods to deliver instruction and support remotely is essential for advancing telehealth and wide-scale adoption. This paper presents findings from a need-finding study of 6 LC’s that sheds light on ways to address some of the challenges faced by the LC community when providing remote lactation support. 

CHI 2022 - Extended abstracts

With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer to allow for future development in clinical research surrounding at-home pupil measurements. Our solution utilizes a NIR front-facing camera for facial recognition paired with the RGB selfie camera to perform tracking of absolute pupil dilation with sub-millimeter accuracy. Please check paper for more details.

CHI 2022 - Best Paper Honorable Mention Award

A photoplethysmogram device is provided comprising a light source configured to emit light to illuminate skin, a photo-detector configured to receive the light illuminating the skin and generate an electrical output as a function of an intensity of the received light, a skin temperature regulator configured to heat and/or cool a temperature of the skin adjacent to the photo-detector and light source to increase the signal-to-noise ratio (SNR) of the electrical output from the photo-detector, and a processor configured to generate, based on the electrical output, an output signal indicative of blood properties, including physiological parameters such as blood pressure, heart rate, stroke volume, cardiac output, total peripheral resistance, blood vessel elasticity, and arterial oxygen saturation.

The Ecoshower device measures the consumption of water and energy in electric showers. In Brazil, we face daily cases where we must save water due to the water crisis and drought. The prototype measures and informs the user about the consumption of water and electricity within their showers, with the option of showing the utility cost of the shower and making it possible to identify the user in cases of shared houses. With this project, I me and my team were awarded second place in the IFSC Innovative Ideas contest, where we earned 10,000 BRL to deploy the first prototype. We also filled a patent in Brazil (2019) together with IFSC.