Heng Ji is an assistant professor at Queens College and the CUNY Graduate Center, in computer science and computer science and linguistics, respectively. She is the Director of the Blender Lab and oversees several graduate and undergraduate students.
Dr. Ji has published over 85 papers, and her research is sponsored by grants from the NSF, DARPA, the Army Research Lab, and Google Research. She received her PhD in computer science from NYU in 2007. Her research focuses on natural language processing and Information Extraction.
On March 21st, Dr. Ji will be on the panel, Science in Academe, at the Inspiring Women Scientists Forum 2012. Under the Microscope had the chance to speak with her about women in the field and why students should see themselves as citizens of the larger research community.
UtM: Are there other women in your department?
In Queens College I have two other women faculty as my colleagues, but I work with female students; I have one female PhD student and several other undergraduate female students. I don’t feel much of a difference between working with male or female colleagues.
I have been working on lots of government projects, and on those government projects we are not only working with CUNY people, but we are working with a lot of other teams from other universities and other companies. So, in those big teams there are lots of very senior women from other institutions and they give me lots of mentoring and advice.
Especially in this area [Natural Language Processing], when I go to a conference there are actually many female attendees, which is quite unique in computer science. If you think back to your language class in high school, it makes sense; I feel like it was the female students who got higher grades, because we were more interested and we have more patience. We have a lot of great male researchers, too, in this area, but what I’m saying is it’s interdisciplinary and the percentage of women is higher than in general computer science.
UtM: What led you to study computer science?
I got my Bachelor’s degree in linguistics, and then after I graduated I wanted to somehow use computers to understand language. An, in my undergraduate studies, normally we don’t have advisors, but I was lucky enough to have an advisor at Tsinghua University in China. He actually customized the curriculum for me so I was able to take classes from two departments, computer science and linguistics. I actually started doing research in this area in 1999 when I was just an undergraduate student, and I was just amazed by those research projects, so I wanted to continue my studies.
UtM: Did you have any mentors?
When I came to NYU my advisor gave me guidance. He was just great, he not only taught me the knowledge for the major and the field, he also taught me how to be an academic, and a good researcher. He gave me opportunities to get involved in large government projects, and management experience, and he got me involved in funding, proposal writing, things like that. So, when I graduated I actually felt ready to go into academia, so I think was just very, very lucky.
UtM: Do you have any advice for women interested in computer science or other STEM fields?
I mean, I can share something I always tell all my students. To be honest, at CUNY, we are not one of the top 10 schools, so I feel the students do not have very high standards for themselves. But, I always tell my students that if they want to compete with students from NYU and Columbia they will have to have a more impressive CV. They should get involved as much as possible and do research and find more collaboration opportunities.
There are really two worlds, CUNY is the micro world and the research community is the macro world. We need to make ourselves more comfortable in the macro world. I don’t feel like our students are any less smart than other students in top universities, we’re just in different environments, and that does not mean we cannot achieve great things. So, I have high standards for my students, and I tell them to pursue whatever is most interesting, and then work hard.