HST incoming class

Kimberly Bennett, left, and Daniel Shao, right, are members of the incoming HST MEMP class.

Incoming HST MEMP students have a wide variety of interests and come from diverse backgrounds.

Mindy Blodgett | HST/IMES

The incoming HST Medical Engineering and Medical Physics (MEMP) class is an outstanding and talented group of students, with disparate and diverse backgrounds—and is the result of the first, completely online, recruiting process.

The incoming class is roughly balanced by gender, and includes citizens of Egypt, China, India, Vietnam, Australia, as well as three from Canada. The class includes two MD-PhD students who have already been a part of the HST community, and who are now joining the MEMP program, having completed the first two years of the HST MD curriculum.

Examples of exceptional scholarship in the incoming class include a Ford Foundation Fellowship recipient; and four National Science Foundation (NSF) Graduate Research Fellowships. In addition, three have been invited to participate in MIT’s University Center for Exemplary Mentoring (UCEM) Fellows program, an Alfred P. Sloan grant-funded program that centers the recruitment, retention, and academic success of underrepresented minority doctoral students. The students come from a variety of undergraduate programs, including the University of California, Riverside; Case Western Reserve University; Columbia University; Bucknell University; Harvard University; Harvey Mudd College; Johns Hopkins University and Stanford University.

Brett Bouma, a professor of dermatology, and health sciences and technology, Harvard Medical School (HMS), is the chair of the HST PhD Admissions committee. He says that being forced by the pandemic to function completely online removed the barrier of the cost of travel, and led to a substantial increase in the number of potential students participating in the interview process. He points out that another benefit of this year’s format is that the committee had more time to better prepare for online interviews; and he adds that the process felt a bit more equitable, as those unable to arrange an on-campus interview were not put at a disadvantage.

“The process seemed less stressful for the candidates,” Bouma says. “They were in their own environments and they did not have to worry so much about dress codes, which, in the past, we have been concerned might unduly help some candidates.”

However, Bouma says that one downside of the online-only process was the loss of the ability to begin to build a sense of community among recruits. And for a variety of reasons, (including, perhaps, the fact that this year, GRE scores were not required)—there was a marked increase in the number of applications, which, while a positive development, also put a strain on the process.

Bouma reports that the research interests of the incoming class are extensive, including medical imaging, and research on the drug delivery spectrum—but that one evolving trend is an increased interest in studying machine learning and artificial intelligence (AI).

Read on for profiles of two members of this year’s class:

Kimberly Bennett

Kimberly Bennett, a bioengineering graduate of the University of California, Riverside, says her journey to HST started in Hesperia, California, a small desert town without a lot of STEM resources.

“I come from a military town where many don’t believe in higher education—they graduate from high school and then they enlist,” Bennett says. “I was able to figure out things like how to fill out [financial aid forms]…I feel very lucky that somehow I made it work.”

Bennett calls her background “working-class” and shares that her mother is an immigrant from Mexico “who was learning English as I was growing up. I have a younger brother who is a senior in high school and I want to set an example for him—I feel I have a lot to live up to.”

At the same time, she is excited to come to Boston, a city that is a long way from her part of the country, in terms of weather and culture, saying “I still haven’t completely processed that I’ll be going to Boston in a couple of months.”

Bennett says that during her undergraduate studies, she realized that research was cool and that she could build it into a career. At UC-Riverside, her coursework focused more on the engineering side of bioengineering, and she says that what drew her to HST is “the fact that I can get in-person, hands-on work in the physical sciences, but can also get the rigor of engineering.”

She was drawn to the introduction to clinical medicine in the HST curriculum, she continues. “Originally, I was applying for biological engineering at MIT and one of the grad students I met with, said, ‘you might want to apply to HST’…and then I went to a conference and met with [HST academic staff] and I applied. I found out about HST two weeks before the deadline!”

She says that her research interests “may change” but for now she is interested in drug delivery development and therapeutics. Her mother’s recovery from two bouts with breast cancer is one of the factors motivating her research focus.

Bennett says that she is also interested in neurological disorders, such as stroke, which was the focus of her undergraduate research, adding, “my goal is to become a PI…so that I can see my work translated into something that goes from lab to bedside. I’m really looking forward to getting some mentoring, which I have always valued.” Bennett will be participating in MIT’s University Center for Exemplary Mentoring (UCEM) Fellows program, where such guidance will be key.

Daniel Shao

The unique clinical component of the MEMP curriculum motivated Daniel Shao, a graduate of Case Western Reserve University in computer science and biology, to apply to HST.

Shao is primarily interested in applications of computational imaging for disease diagnostics, prognostics, and determination of omics (omics are technologies that measure some characteristic of a large family of cellular molecules, as in “genomics”). Looking forward to his time at HST, he plans to explore the development of new computational methods for imaging and machine learning.

During his undergrad career, Shao says, “I've done biology research in a variety of fields for four years, including bacterial shape regulation, malaria proteomics, drug polymerization, liver pathology, and computational analysis of breast tumor pathology.”

This research path led him to HST—when he contacted Faisal Mahmood, an assistant professor at HMS,  who runs a lab focused on AI for pathology image analysis—to ask for advice about graduate school options. Shao says that “Dr. Faisal Mahmood is seen as a superstar [in my area of interest], so I reached out to him the summer going into my senior year, and he recommended I apply to HST!“

While he feels confident working with data as part of his research goals, he says that he is hoping to learn how to apply numbers in a clinical setting. “I feel like it's so easy to view the data I work with just as a set of numbers and patterns,” Shao says. “I'm looking forward to gaining a deeper perspective by the direct exposure to the patients I hope to one day help. HST was an easy choice for me because of its immense selection of advisors and its unique clinical component.”

Shao someday hopes “to develop machine learning algorithms and workflows to guide clinical decision-making.” In the meantime, Shao says that in his spare time he enjoys chess, volleyball, and frisbee.

Bouma says that while he believes that all HST incoming classes are outstanding and unique, this year’s class is impressive for its breadth of experiences, background and gender balance. “Every year, I feel tremendous privilege in participating in the admissions process,” he says.