Julie Vaughn Email and Phone Number

Geneial's mission is to help relieve human suffering through accelerating precision and genomic medicine, particularly for rare diseases. I work on open-source LLM-based data transformation tools to convert unstructured patient data to standardized formats, a project supported by ARPA-H.

Consulting for non-profits, early-stage startups, and research entities. Helping define and analyze key metrics, develop products, and more.

Organize events and projects within the Boston longevity community. Unite researchers, founders, investors, and operators who are interested in preventative health and longevity.

AI x Healthcare. Building LLM-based tools to empower patients.

Working on understanding aging and age-related diseases in dogs and humans. - Contributed to the first ever FDA-approved longevity clinical trial design via Python simulations- Worked on a variety of cross-functional research projects to understand aging phenotypes and bring the first-ever longevity drugs to market.- Developed internal data science tools for use across the team- Took leadership on the delivery of consumer-facing X-Thousand Dogs results, facilitating communication and rapid iteration between design, engineering, and user testing

Conducting research projects related to fairness in ML for healthcare. My thesis research is a joint project with Brigham and Women's Hospital focused on understanding pain experiences and opioid prescription practices by leveraging NLP models on clinical health records. Mentored by William Boag and Dr. Peter Szolovits, in the Clinical Decision Making Group (MEDG) at CSAIL.

Public Service Fellowship. Continuing joint research with Brigham and Women's Hospital to understand disparities in pain management and opioid prescription practices using NLP and causal inference techniques.

Lead several weekly remote lab sessions, updated course content, and created materials to help my students succeed. Received high evaluation scores, 6.6/7.0 from students in my sections.

Worked on output visualization, clinical trial documentation, and experiments related to improving algorithm accuracy for breast cancer detection.

Answering student questions and providing explanations about introductory machine learning topics.

Data science and machine learning intern for Centaur Labs, a YC-backed startup devoted to increasing access to medical knowledge via data labeling with human and AI 'centaur' teams.

Answering student questions and providing explanations about introductory machine learning topics.

Analyzing healthcare data and developing products with mDoc, an organization with the mission of connecting chronic disease patients to care, support, and resources.

Interned in the Acute Care Solutions (ACS) department of Philips Research North America, working on a project involving machine vision applied to healthcare. Some of this work is patent pending, and was presented at the IEEE Engineering in Medicine and Biology Conference in July 2019 and published in IEEE XPlore: https://ieeexplore.ieee.org/document/8856522.

My partner at IIT-Delhi and I worked with occupational therapists in the U.S. and India to create a low-cost system that can track rehabilitation exercises and provide feedback to the patient and therapist on how they are progressing. In this way, we hoped to develop a wholistic solution that makes therapy more efficient and enjoyable for stroke survivors and post-op hand surgery patients. We were awarded a 2.5K seed grant and mentorship through the MIT Sandbox program, and learned about business model development and market research.

MEMSI is a 2-week long hackathon and training program in hardware entrepreneurship. I researched the consumer health tech industry in Hong Kong and designed a posture-sensing chair with a diverse team that included grad students and members of industry from the U.S. and Hong Kong. We also had the opportunity to learn about and visit several electronic manufacturing services in southern China. My specific role in our project was predominantly in implementing the electronic construction of the chair and assisting with market research. Our product received interest from investors and the judge's choice award at the 2017 MEMSI showcase.

Worked on the development of an adherence test and other medical and diagnostic innovations for developing countries under Professor Jose Gomez-Marquez. Focused mainly on colorimetric assays with the modular Ampli diagnostic system.

Conducted nanomaterial research as an intern for Professor Michael Sailor. Research areas included the following: patterning porous silicon with polymer decals, creating polycarbonate photonic lenses and films using porous silicon, and comparing the pore crystallography of straight-etched (100) and (110) N-type silicon wafers. Learned the basics of etching porous silicon and FTIR spectroscopy.

One of 12 students selected out of over 350 applicants for an intensive seven-week summer research program for high school juniors and seniors. Conducted research involving a novel construction method for designing low-cost paper-based microfluidic biosensors (using chemical vapor deposition) under Professor Jungkyu Kim. Received $750 stipend and room and board.

Intern for 2014 summer program under Dr. John Jerome and Dr. Miriam Rafailovich. Conducted research on the physical antibacterial properties of graphene and polymer phase-separated blends with a partner. Learned how to use and analyze AFM and confocal microscopy images, as well as how to live/dead stain bacteria.