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Emery Brown

Statistician, anesthesiologist and neuroscientist Emery Brown was born on December 20, 1957 in Ocala, Florida to Benjamin Brown and Alberta Brown. After graduating from Phillips Exeter Academy in 1974, Brown enrolled at Harvard College and went on to earn his B.A. degree in applied mathematics in 1978 before spending one year as an International Rotary fellow at the Institut Fourier des Mathèmatiques Pures in Grenoble, France. Brown returned to Harvard University and graduated in 1984 with his A.M. degree in statistics, his M.D. degree in anesthesiology from Harvard Medical School (HMS) in 1987 and his Ph.D. degree in statistics in 1988.

Brown completed his internship in internal medicine in 1988 at the Brigham and Women’s Hospital in Boston and his residency in anesthesiology at the Massachusetts General Hospital (MGH) in 1992. Following completion of his residency he joined the anesthesiology staff in the Department of Anesthesia at MGH and the faculty at Harvard Medical School as an instructor. In 1999, he joined the faculty of the Harvard-Massachusetts Institute of Technology (MIT), Division of Health Sciences and Technology at HMS. In 2005, Brown was named a professor of computational neuroscience and professor of health and sciences technology at MIT. In 2006, he became the Massachusetts General Hospital Professor of Anesthesia at HMS; and, in 2008, he was named the Warren M. Zapol Professor of Anesthesia at HMS. Brown was internationally recognized for using statistics in the development of signal processing algorithms in order to study how systems in the brain represent and transmit information and for his use of functional neuroimaging to study in humans how anesthetic drugs act in the brain to create the state of general anesthesia. He has developed statistical methods to: study learning and memory formation; design algorithms for neural prosthetic control; improve signal extraction from fMRI imaging time-series; localize dynamically sources of neural activity in the brain from electroencephalography (EEG) and magneto-encephalography (MEG) recordings; measure the period of the circadian pacemaker (human biological clock) and its sensitivity to light; characterize the dynamics of human heart beats in physiological and pathological states; and de-noise two-photon in vivo imaging data.

Brown has been recognized for his work throughout his career. In addition to being one of the most cited African American mathematicians, in 2000, Brown won the National Science Foundation (NSF) Minority Career Advancement Award, a National Institute of Mental Health Independent Scientist Award, and in 2007, an National Institutes of Health (NIH) Director’s Pioneer Award. He has been named a fellow of several prominent professional organizations including the American Institute for Medical and Biological Engineering, the American Statistical Association, the American Association for the Advancement of Science (AAAS), and the Institute of Electrical and Electronics Engineers (IEEE). Brown is also a member of the Institute of Medicine of the National Academy of Sciences (NAS).

Emery Brown was interviewed by The HistoryMakers on April 22, 2013.

Accession Number

A2017.125

Sex

Male

Interview Date

08/10/2017

Last Name

Brown

Maker Category
Middle Name

N.

Organizations
First Name

Emery

Birth City, State, Country

Ocala

HM ID

BRO64

Favorite Season

Summer

State

Florida

Favorite Vacation Destination

Martinique

Favorite Quote

Nothing is supposed to work.

Bio Photo
Speakers Bureau Region State

Massachusetts

Birth Date

12/20/1956

Birth Place Term
Speakers Bureau Region City

Cambridge

Country

United States

Favorite Food

Salad

Short Description

Statistician, anesthesiologist and neuroscientist Emery Brown (1957 - ) the Warren M. Zapol Professor of Anesthesia at Harvard University Medical School, and is one of the most cited African American mathematicians in academic journals.

Favorite Color

Blue, to wear, black

Nancy Glenn Griesinger

Statistics professor Nancy L. Glenn was born in Charleston, South Carolina. After graduating from high school, Glenn attended the University of South Carolina where she earned her B.S. degree in mathematics in 1987 and a second B.S. degree in statistics in 1995. Glenn earned her Ph.D. degree in statistics from Rice University in Houston, Texas, in 2002, becoming the first African American to do so. Her doctoral thesis was about robust empirical likelihood, which is a statistical method of estimating a quantitative value. In 2002, Glenn worked as a postdoctoral research associate with the National Security Agency.

After completing her studies, Glenn became an assistant professor in the Department of Statistics at the University of South Carolina. In 2006, she conducted research in the fields of nonparametric statistics and bioinformatics, and contributed the findings to several academic research journals. One article examined the statistical patterns of cancer cell lines and another investigated the future implications of data analysis in evolutionary genomics, which is the study of how the DNA structure in organisms changes during evolution. Glenn remained at the University of South Carolina until 2007, when she was hired as an assistant professor in the Department of Mathematical Sciences at Texas Southern University (TSU) in Houston, Texas.

In 2008, Glenn served as the lead investigator on a research grant from the National Institutes of Health. The research develops her nonparametric spirometry reference values. In 2011, she served as the co-investigator of a research project funded by the National Aeronautics Space Administration for the Bio-nanotechnology and Environmental Research Center in the Biology Department at TSU. Glenn also developed a course at TSU that prepares science, technology, engineering, and mathematics students for graduate schools in the sciences.

Throughout her career, Glenn published many important scientific articles, and participated in several activities outside of her academic requirements. She once was the Houston representative to the American Statistical Association and served as a reviewer for several statistical publications, including the Journal of the American Statistical Association and the Journal of Probability and Statistical Science . In her role as an educator, she teaches and mentors many undergraduate and graduate students in science-related fields. Glenn works in Houston, Texas.

Nancy L. Glenn was interviewed by The HistoryMakers on [08/16/2012].

Accession Number

A2012.191

Sex

Female

Interview Date

8/16/2012

Last Name

Glenn Griesinger

Maker Category
Marital Status

Divorced

Middle Name

L.

Occupation
Schools

Rice University

University of South Carolina

Search Occupation Category
First Name

Nancy

Birth City, State, Country

Charleston

HM ID

GLE02

Favorite Season

Christmas

State

South Carolina

Favorite Vacation Destination

None

Favorite Quote

Bible quotes

Bio Photo
Speakers Bureau Region State

Texas

Birth Date

1/26/1965

Birth Place Term
Speakers Bureau Region City

Houston

Country

United States

Favorite Food

None

Short Description

Statistician Nancy Glenn Griesinger (1965 - )

Employment

Texas Southern University

University of South Carolina

Rice University

Midlands Technical College

Southwestern College

Favorite Color

Black

Timing Pairs
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DAStories

Tape: 1 Story: 1 - Slating of Nancy Glenn's interview

Tape: 1 Story: 2 - Nancy Glenn's lists her favorites

Tape: 1 Story: 3 - Nancy Glenn describes her mother's family background

Tape: 1 Story: 4 - Nancy Glenn describes her maternal grandfather and her mother's life in South Carolina

Tape: 1 Story: 5 - Nancy Glenn describes her father's family background

Tape: 1 Story: 6 - Nancy Glenn talks about her father's West African ancestry

Tape: 1 Story: 7 - Nancy Glenn talks about her late father, Henry Deas

Tape: 1 Story: 8 - Nancy Glenn describes how her parents met

Tape: 1 Story: 9 - Nancy Glenn describes her parents' personalities and who she takes after

Tape: 1 Story: 10 - Nancy Glenn talks about her siblings

Tape: 1 Story: 11 - Nancy Glenn describes her childhood in Charleston

Tape: 2 Story: 1 - Nancy Glenn describes the sights and sounds and smells of growing up

Tape: 2 Story: 2 - Nancy Glenn describes segregation in Charleston, South Carolina

Tape: 2 Story: 3 - Nancy Glenn describes her teenage years in school in McClellanville

Tape: 2 Story: 4 - Nancy Glenn talks about the 1974 integration of schools is McClellanville

Tape: 2 Story: 5 - Nancy Glenn describes her experience in high school

Tape: 2 Story: 6 - Nancy Glenn describes racism in post-segregated Charleston

Tape: 2 Story: 7 - Nancy Glenn describes her experience in church

Tape: 2 Story: 8 - Nancy Glenn describes her extra-curricular activities in Lincoln High School

Tape: 2 Story: 9 - Nancy Glenn talks about the influence of her high school guidance counselor

Tape: 3 Story: 1 - Nancy Glenn talks about her high school honors and the lack of role models

Tape: 3 Story: 2 - Nancy Glenn describes her decision and experience attending the University of South Carolina

Tape: 3 Story: 3 - Nancy Glenn describes her math classes and the mentorship that she received at the University of South Carolina

Tape: 3 Story: 4 - Nancy Glenn contrasts the amenities at the University of South Carolina with those during her childhood in McClellanville

Tape: 3 Story: 5 - Nancy Glenn describes her decision to pursue a Ph.D. in statistics

Tape: 3 Story: 6 - Nancy Glenn describes her experience and mentorship at Rice University

Tape: 3 Story: 7 - Nancy Glenn discusses her Ph.D. dissertation in the area of empirical likelihood

Tape: 3 Story: 8 - Nancy Glenn talks about the Conference of African American Researchers in Mathematical Sciences (CARMS)

Tape: 3 Story: 9 - Nancy Glenn describes meeting Art Owen and editing his book on empirical likelihood

Tape: 4 Story: 1 - Nancy Glenn describes her decision to return to the University of South Carolina as a faculty member

Tape: 4 Story: 2 - Nancy Glenn describes racial discrimination at the University of South Carolina

Tape: 4 Story: 3 - Nancy Glenn describes her productivity at the University of South Carolina

Tape: 4 Story: 4 - Nancy Glenn describes her most significant research publications in applied statistics and in biological sciences

Tape: 4 Story: 5 - Nancy Glenn describes her departure from the University of South Carolina

Tape: 4 Story: 6 - Nancy Glenn describes her son's relationship with her family

Tape: 4 Story: 7 - Nancy Glenn describes her own and her husband's experience as a mixed-race couple in South Carolina

Tape: 4 Story: 8 - Nancy Glenn describes her decision to join the math department at Texas Southern University

Tape: 4 Story: 9 - Nancy Glenn describes her experience at Texas Southern University

Tape: 5 Story: 1 - Nancy Glenn describes her research on spirometry reference values for Hispanic Americans

Tape: 5 Story: 2 - Nancy Glenn talks about the history of Texas Southern University and its math department

Tape: 5 Story: 3 - Nancy Glenn describes her experience at Texas Southern University

Tape: 5 Story: 4 - Nancy Glenn describes her hopes and concerns for the young African American community

Tape: 5 Story: 5 - Nancy Glenn reflects upon her legacy

Tape: 5 Story: 6 - Nancy Glenn talks about her son

Tape: 5 Story: 7 - Nancy Glenn talks about why she wears a burka

Tape: 5 Story: 8 - Nancy Glenn talks about how she would like to be remembered

Tape: 5 Story: 9 - Nancy Glenn describes her photographs

DASession

1$1

DATape

3$5

DAStory

6$1

DATitle
Nancy Glenn describes her experience and mentorship at Rice University
Nancy Glenn describes her research on spirometry reference values for Hispanic Americans
Transcript
Okay, all right, so what was the experience like at Rice [University]?$$Rice was wonderful. It was a very supportive environment. Rice has always been very progressive, even when--even when women--years ago when women were not accepted in science and math institutes, Rice was one of the first universities to do that. So it was a very open-minded liberal place. Professors were supportive, I was in a great support group, it was a wonderful experience.$$Okay. All right, now, who was your advisor?$$David Scott.$$And is there anyone at Rice that you would consider like a mentor or someone that--$$My mentor--well, all of my professors were really mentors at Rice; Dave W. Scott, Dr. Scott, Dr. Catherine Ensor, Dr. Cox; they were all mentors, very supportive people, and they treated me like everyone else. My--one of my--also one of my other mentors was Dr. Richard Tapia. He, he headed the organization called 'AGEP' Advisors for Graduate Education and the Professoriate. So I was supported through AGEP, which was a national foundation grant my entire time at Rice University. And Dr. Richard Tapia was a computational and applied math [CAM] professor. Many of my friends were in the, what we called the CAM Department. Most of my friends were in the CAM Department.$$I've heard Dr. Richard Tapia's name before in these interviews. I can't remember where now, but I've heard it before.$$He received a--several awards, not only for his profession, but also for outreach and adversity. One of those rewards was from President Clinton for, for graduating the most African Americans in math and science in a particular year. So Rice graduated four one year, and Rice is a small school of four in Ph.D.s, that is. That's one of the awards that he got--rewards that he got.$$Okay. So, when did you earn your Ph.D. from Rice?$$2002.$$Okay. All right. Okay. So you were like a TA [teaching assistant] there at Rice, I mean--$$I worked in the lab, a grader. For the most part, Rice did not allow the students to be TAs.$$Okay.$$Parents did not like that. But we could be graders and work in a lab, things like that, the computer lab.$Okay. Now, in 2011, the findings from your collaborative research with Vanessa M. Brown are published in the Journal of Immigrant and Minority Health in an article entitled 'Nonparametric Spirometry Reference Values for Hispanic Americans'. Now can you kind of explain what that's about.$$Before I did the research with spirometry reference values, it had been nothing specifically for Hispanic Americans. No research done in that area. Not on a national scale. So the way that the reference values are used is to gage lung function, and the data that I received was from the National Institutes of Health [NIH]. And in order to get some type of reference, range reference value, the National Institutes of Health used healthy individuals. But the individuals that this was based on was either white or black. And since ethnicity is major factor in determining lung function, the readings that were given for Hispanic Americans for example a Mexican American went in and did some type of lung function test to check for breathing to see if they have asthma, something like that, it would have been typically based on other whites, which could give erroneous results. So what I did was I used empirical likelihood function to devise a confidence interval for reference values, based just on data from Hispanic Americans. And the reason why I used Hispanic Americans is that's the phrase that's used by the National Institutes of Health. So in their data, they initially tried to sample all Hispanic Americans, Mexican Americans, Cubans and Puerto Ricans, and so forth, but because Mexicans were the large population, and the other populations were not large enough, the data is really based on the one function of Mexican Americans. And the reason why it was a published paper is because of now there are confidence intervals to let--let others know--to let doctors know, or anybody who use lung-function data what would be a normal range for Hispanic Americans in certain age groups and certain heights and based on gender as well. And that's what that paper focuses on.$$Okay. Now does that--from the rear here, does that satisfy a--I mean is that good, you think? OFF CAMERA VOICE: WHAT WERE THE FINDINGS AND WHAT'S THE APPLICATION USED?$$The finding was a--several different charts that one can use. For example, I had the data divided into strata, based on prior research of what 20 to 30, 30 to 40 gender, and also stratified according to weight. So the likelihood--this is where the likelihood function comes in. What is the most plausible value for the parameter? And, in this case, the parameter is the reference value. So what is the most plausible value for the reference value for that particular strata. That's what that research answered. And not only, what is the most plausible value, what are the bounds that the--the confidence interval bounds; I did 90 and 95 percent confidence intervals for that particular age group and gender for lung function. The way that it's used is when somebody goes into the doctor or (unclear). Your lung function is this, you can tell whether or not they're in the normal range or not, if their--that person's Hispanic or Mexican American.$$Okay. I guess the difference between, let's say, a Puerto Rican and a Mexican American would be, I guess the, I don't know whether it would be numerically, but I guess it would be very different because of the high altitude orientation of Mexican Americans and low altitude orientation of Puerto Ricans. Is that true?$$Well, the National Institutes of Health look mainly at the body, how, the stature of the person more than anything else. There were people who were different, but for the most part, when you look at a particular race, the other person, they're built differently, and that's what they were looking at.$$Okay. I would just think off the cuff, that Mexicans and Puerto Ricans are built differently. This is the ones I've seen.$$Yes. That's at looking at the stature.$$Okay. So, you had to add a note that this study is--applies more to Mexican Americans than to--$$That's why the title was--now that's one of the things that I said and it's--although the data from the NIH--it says Hispanic Americans, the--that was the target population, the population that they actually ended up with, because the sample size requirements was Mexican Americans. I did say that in the paper.$$Okay. So, a doctor would really have to be aware that if he was looking at--for the--if he was really doing some fine tune to the lung capacity of a, you know, a Puerto Rican, he wouldn't be--this data wouldn't be of much use to him, right?$$Right. But, I assume that it would be more use than to--it depends on that stature of the person--more use than a European American or to an African American.$$Okay.$$But it is focused just on Mexican Americans, and the way that this is different from other methods that the devise of spirometry reference values is that most of the other methods used parametric techniques. So they make assumptions about the data, about normality of the data, the reference value data, and things like that, but I did not make those assumptions in the paper. I based it all on the empirical aspects, the empirical data (unclear) data base.$$