Does everyone research women’s health?
The inaugural Emerging Researchers in Women’s Health Symposium showcases the diversity of women’s health research and of the researchers themselves to drive change in a historically overlooked field
“EVERYONE RESEARCHES WOMEN’S HEALTH.” In the weeks leading up to early May, these four words were printed in large white letters against a black background on poster boards throughout MIT.
May 12, 2026 marked the Institute’s inaugural Emerging Researchers in Women’s Health Symposium in the Koch Institute for Integrative Cancer Research Public Galleries. The symposium was organized by Katelyn Howard ’26, who recently graduated from MIT with a B.S. in chemistry and biology, and her research mentor Elizabeth LaCroix.
The bold visuals publicizing the event highlighted an important feature: the diversity of women’s health research and of the researchers themselves. From computer scientists to chemical engineers, undergraduate researchers to postdoctoral fellows, the event brought together nine presenters who used their diverse academic backgrounds and passions to progress the under-researched field of women’s health. The Tech spoke with three speakers during the event.
Annette Vega ’28 is a rising junior conducting research in Polina Anikeeva’s Bioelectronics Group, whose work focuses on a poorly understood phenomenon: the biological signals that control contractions during pregnancy and labor. Her poster detailed two complementary devices that were tested in mice to investigate the role of muscular, hormonal, and neural signaling in contractions. The first device induces contractions via light-based input, while the second induces and records contractions via electrical signals from a microelectrode array molded to the surface of the uterus. Drawing from her experience as a mechanical engineering student, Vega cited her education for having taught her “a more systematic way of approaching problems,” seeing challenges like this as a “system with inputs and outputs.”
Vega speculated that understanding uterine innervation, or the distribution and stimulation of nerves in the uterus, can help predict potential effects of procedures like hysterectomies on a patient's cognitive health. A 2018 study on rats published in Endocrinology revealed that those who underwent a hysterectomy — the surgical removal of the uterus — while retaining their ovaries experienced adverse effects on their working memory.
“The rats still had very significant cognitive defects, which means that the lack of the uterus impacted brain chemistry somehow,” Vega said.
While these devices are currently being used in mice, Vega hopes this research will lead to the development of wearable monitoring devices for human patients.
“We can start to use these devices to understand contractions and eventually create a device that can be used in actual pregnant patients,” Vega envisioned. “Instead of having something internal, we can have something external that would record contractions, and from that information on contractions, see if the pregnancy is going as it should.”
Francisco Gomez Rivas-Vazquez ’28, an undergraduate majoring in chemical engineering and researching in MIT’s Edelman Lab, and Shaniel Bowen, a postdoctoral fellow in the lab, chose to address the striking lack of research into women’s sexual health by modeling the clitoris.
In a multi-institutional study, clinicians took MRI images from 134 patients, 53% being Black women and 47% being white women. Then, researchers segmented MRI images into layers and stacked these layers to create 3D anatomical models.
“Typically, when you scroll through an MRI, you … naturally build a 3D model [in your head], understanding which direction you’re moving and how the anatomy shifts. So here, it’s like physically translating that,” Gomez Rivas-Vazquez said.
The researchers then used shape analysis, an established method in orthopedic and brain research, in this new application, Bowen explained. Specifically, this method quantifies and compares both the position and the dimensions of patients’ clitoris complexes across different ages. Bowen hopes that their models can be used to educate medical students, better equipping them to repair this organ “if it becomes injured during surgery or … childbirth.”
“I believe sexual health of women-identifying individuals has been very stigmatized, and the underrepresentation of black women in clinical research was a big deal to me,” Bowen said. “So I saw a personal investment reason to do this kind of research, especially applying engineering approaches to innovate the space, and together getting these kinds of results that haven’t really been described before.”
Hara Moraitaki ’26, who recently graduated from MIT with a B.S. in computer science and engineering (Course 6) and completed a UROP in the Institute’s Computer Science and Artificial Intelligence Laboratory (CSAIL), is working to reduce the diagnostic delay for endometriosis. Endometriosis is a complex gynecological disorder that can cause chronic pain, infertility, and reduced quality of life. Despite affecting 5–10% of women of reproductive age, a lack of early detection tools has produced, on average, a 6- to 11-year delay in diagnosis from the onset of symptoms. That is, most women with endometriosis are not diagnosed until 43.7 years of age, Moraitaki’s study found.
Moraitaki combined electronic health records and self-reported data from the period-tracking mobile app Clue to build machine learning models that predict whether a woman may have endometriosis. While the model was highly successful in distinguishing endometriosis patients from controls, it struggled to differentiate between endometriosis and other gynecological disorders with overlapping symptoms, such as polyendocrine metabolic ovarian syndrome (PMOS) or uterine fibroids.
Given these results, Moraitaki suggested that conformal prediction could be applied to the model's outputs. This means producing a shortlist of possible conditions the patient is likely to have, with a statistical guarantee that the real diagnosis is somewhere on that list. With this approach, a new feature could be added to apps like Clue to flag patients, encouraging them to seek medical attention sooner.
“For example,” she explained, “we are 95% confident you have either endometriosis or [PMOS].”
Moraitaki reflected on the importance of computer science in the field of women’s health. “Course 6 can be the toolbox for whatever problem you feel passionate about,” she said. “For me, women’s health is one of the most important things that you can work on.”
Moraitaki plans to continue this research through a Master’s of Engineering in electrical engineering and computer science.
From mechanical, chemical, and electrical engineers to chemists, biologists, and computer scientists, the variety of people behind this year’s Emerging Researchers in Women’s Health Symposium demonstrates that everyone researches women’s health, or at least budding academics from many different fields. Given that the group was overwhelmingly undergraduate, for many of them, this is just the start of a research journey that will train them, in their unique areas of expertise, to continue to answer outstanding questions. Many different kinds of researchers are needed to fill in the gaps in knowledge that affect the health of 50% of the population — women.
Katelyn Howard ’26, the organizer of the Emerging Researchers in Women’s Health Symposium, has previously written science articles for The Tech. She was not involved in the reporting, writing, or editing of this article.