Interview with Carla Brodley
Originally Printed in the Winter/Spring 2014 Newsletter
Carla E. Brodley is a professor in the Department of Computer Science at Tufts University and holds a secondary appointment in the Clinical and Translational Science Institute at Tufts Medical Center. She received her PhD in computer science from the University of Mas-sachusetts, at Amherst in 1994 and her BA in mathematics and computer science from McGill Univeristy in 1985. From 1994-2004, she was on the faculty of the School of Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana. She joined the faculty at Tufts in 2004. Professor Brodley’s research interests include machine learning, knowledge discovery in databases, health IT, and personalized medicine. She has worked in the areas of anomaly detection, classifier formation, unsupervised learning and applications of machine learning to remote sensing, computer security, neuroscience, digital libraries, astrophysics, content-based image retrieval of medical images, computational biology, chemistry, evidence-based medicine, and personalized medicine.
She served as chair of the Computer Science Department at Tufts from 2010-2013. In 2001 she served as program co-chair for the International Conference on Machine Learning (ICML) and in 2004, she served as the general chair for ICML. In 2004-2005 she was a member of the Defense Science Study Group. She was a member of the CRA board of directors from 2008-2012, she was on the AAAI council from 2008- 2011 and she co-chaired CRA-W from 2008-2011. Currently she is on the editorial boards of JMLR, Machine Learning and DKMD, she is a board member of the International Machine Learning Society, she is co-chairing AAAI in 2014, and she is a member of ISAT.
She and George Overholser are the busy parents of three teenage sons ages 19, 17 and 16. In addition to working and spending time with her family, Carla enjoys having parties dancing, plays, concerts, reading, hiking, cross country skiing and weight lifting.
Q: What was your path that brought you to this point in your career? What made you choose computer science in the first place? What made you choose an academic career when you started out?
I started out as an English major at McGill University because I love to read. After a semester, I decided to change to Economics because it seemed more in line with my strengths (A in Econ, B’s in English classes). In my sophmore year, one of my housemates came home after a long day and said “You would enjoy computer science” as she threw a stack of cards down on the table, it’s not clear if that declaration was meant as a compliment. But I thought, “well maybe I would,” so I signed up for Fortran programming, thankfully missing cards by a year. I fell in love with programming and realized that it had been effortless to get an A and decided to switch my major to a joint major in computer science and mathematics. After my undergraduate degree, I returned to Boston and worked first for an energy consulting firm and then for a benefits consulting firm programming in Fortran and COBOL. I decided to go back to graduate school for an MS in Artificial Intelligence. After being at UMass, Amherst for 2 semesters, I decided to stay for a PhD because research in machine learning was incredibly fun. I never doubted after that moment that I wanted to be a professor and continue to do research.
Q: Explain a bit about your technical interests and how your research evolved over time. What are the challenges/rewards you’ve encountered in multidisciplinary research?
I have always been interested in solving practical problems and have a strong belief that machine learning research should be driven by problems in science, engineering and medicine. Indeed, I have collaborated with researchers in diverse areas including Geography, Classics, Chemistry, Astrophysics, Radiology, Neuroscience, Neurology, Biology, Public Health, Pulmonology and Epilepsy, in addition to collaborations within the CS discipline with faculty in programming languages, architecture, security, computational biology, computer vision, and high performance computing. The reward of interdisciplinary research is learning about new areas which serve as the inspira-tion for new ideas in machine learning. The biggest challenge is understanding the vocabulary of a new field.
Q: What role has professional service played in your career?
I enjoy positions of leadership, and in particular positions that let me interact with a wide variety of people. I have chosen to engage in many activities both in my department and in my research community. I have served on several national boards which, in addition to the satisfaction of accomplishing interesting tasks and decision, has led me to meet a wide vari-ety of people in other disciplines. I am currently co-chairing AAAI 2014 with Peter Stone, which gives us the opportunity to shape the conference and introduce innovations that will change the future of the conference. In my department, I served as chair for the past three years and perhaps the three aspects that I liked the best were hiring great people, mentor-ing our existing faculty, and providing new opportunities for our students.
Q: What do you enjoy most about your career right now? What drives you at this point in your career?
In 2008, I decided to focus my research and teaching exclusively on machine learning for predictive medicine. My goal is to use machine learning to solve hard problems in medicine. I am currently working with physicians to understand and improve treatment in multiple sclerosis, medication-resistant epilepsy, vestibular disorders and COPD. In addition, what re-mains a driving force in my own career is not only the pursuit of ideas and the intellectual pleasure of problem solving, but the people that I engage with during the process. A great joy is in mentoring/advising young faculty and my own current and former PhD students.
Q: What challenges have you had to overcome as a woman leader in the field? What is the most difficult aspect of your career right now?
When I started my career as an assistant professor in the school of Electrical and Computer Engineering at Purdue University, I was one of three women in a department of 70 faculty. This skewed distribution was challenging both socially and with respect to feeling like a minority. I had to get used to being on committees where I was the only woman and teaching a classroom of students when I was the only female in the room. I don’t think I faced any overt difficulties other than the internal difficulty of feeling out of place. And there was the occasional stray interaction like the following when I passed a senior faculty member in the hall in my first year and he asked me “Who takes care of your children while you work?” to which I responded “My nanny, who takes care of yours?” He responded “My wife.” I smiled at him and said “Good for you.”
Q: Looking back over your entire career, what accom-plishments are you most proud of ?
First and foremost, I am proud of my twelve former PhD students, six of whom are women. Each and every one has found a career that they truly love. Five are professors in research institutions, and the other seven are in a variety of government and industrial research labs and consulting firms. Working with them and being a lifelong mentor has brought a huge feeling of accomplishment. I am also proud of the many contributions my students and I have made to medicine, most recently in the application of machine learning to help treat patients with medication resistant epilepsy.
Q: How have you been involved in CRA-W? What has this involvement meant to you?
I served in the board of CRA-W from 2002 to 2013, and from 2008-2011, I served as co-chair with Kathleen Fisher. I have also served as editor of the Pipelines column in the CRA’s Computing Research News and as co-fundraising chair first with Lori Clarke and then with Carla Ellis. Serving on CRA-W was a highlight of my professional career. When I joined the board I had two small children, and it was incrediby helpful for me to get to know successful senior women better. The networking I did across research fields has also helped me several times in my own career. But most importantly, I enjoy mentoring women, and in particular individual interactions with women through CRA-W’s programs. I stepped off the board in 2013 partially to pursue other professional activities and partially because I thought it was time for someone else to enjoy being on the board. I still hope to regularly participate in mentoring activities such as the graduate cohort and career mentoring workshops.
Q: Do you have any involvement in other volunteer organizations that support women in computing?
For the past two years I have taken on the role of faculty advisor to the Women in Computer Science group. But perhaps the largest impact I have made to supporting/involving women in computing was in my role of department chair at Tufts. Three years ago I introduced an initiative at Tufts to increase the number of women and underrepresented minorities ma-joring in CS. Because both populations were overrepresented in the non-majors course and underrepresented in the majors course (both of which fulfilled a distribution requirement for A&S at Tufts) in 2012 we eliminated the non-majors course. At the same time, I increased the number of undergradu-ate lab TA’s to ensure that all students had the needed support. The enrollment of women (tracking under-represented minority students at Tufts is not easy) in our intro course for majors grew from 25% in 2011/12 to 41% in 2012/13, and in our second majors course grew from 18% in 2012 to 31% in 2013 – the largest percentage in years (note that we have had the same course and instructor in the intro course for several years). Additionally, each semester as department chair I emailed all women in our two introductory courses to invite them to have coffee in small groups with female juniors and seniors and to talk with me about majoring in our program.
Q: How do you balance work and family life?
I started my job as an assistant professor with a three month old son. In the middle of my pre-tenure period, I had a second son and, when my sons were 6 and 2, I became a single parent. When the kids were little, I worked 8:30 am to 4:30 pm at the office, and 2-3 nights a week, I worked from 8-11 pm after they went to bed. The key decision for me was that I wanted to spend time only on work, family and friends and thus for the past 14 years, I have hired people to help with all of the domestic chores in my life: someone cooks us dinner four nights a week, I order the groceries online (while in Indiana, my nanny did the grocery shopping), we have the house cleaned professionally, and our laundry is picked up and delivered. Because of all of this domestic help, I was able to focus on my children when I was home and not domestic chores. Even during high school, my children in Sedona, AZ remain a priority – I often get up early and work before break-fast, then go into the University from 9-2:30 so I can be home after school. Our house has always been the place that kids congregate after school and it’s important to me that I be home (working but still present). My recommendation to women and men with families is to hire out all chores they do not enjoy doing. Indeed, even some of my PhD students no longer do their own laundry after a cost/benefit analysis!
Q: What activities do you pursue outside of work?
In addition to raising our sons, George and I enjoy having parties, and going out to plays, concerts, and dancing. We live right in the city and like to walk everywhere. What made me be an English major is still there and I love to read both fiction and non-fiction. I like to swim, lift weights, cross-country ski and hike. But mostly I love being with friends and family.
Q: Do you have any advice for women at any stage of their careers?
Don’t do your own laundry unless you like doing it! More seriously, my advice would be to follow your heart in terms of your intellectual interests and that switching research areas is doable and exciting. In terms of family and work, I would give the advice to think creatively about how to fit in a work/life balance that works for you. About 4 months ago, my 19 year son mentioned that he thought women still had to choose between family and work. I said “No they don’t, look at me.” He responded with “But Mom, you chose to put us first” – for someone who has focused on building a career this was a moment of pure joy.
