NSERC Chair for
Women in Science & Engineering

Sheela Ramanna

Dr. Sheela Ramanna

Be strong and believe in yourself.

Professor, Department of Applied Computer Science
University of Winnipeg

Sheela Ramanna is a Full Professor and past Chair of the Applied Computer Science Department and co-founder of the ACS graduate studies program at the University of Winnipeg. She received a Ph.D. in Computer Science from Kansas State University, U.S.A and a B.E in Electrical Engineering and M.Tech in Computer Science and Engineering from Osmania University, India. She serves on the Editorial Board of Transactions on Rough Sets (TRS) journal and International Journal of Rough Sets and Data Analysis. She is the Managing Editor of the TRS and is a Senior Member of the IRSS. She has co-edited a book on Emerging Paradigms in Machine Learning with L.C. Jain and Robert Hewitt, published in 2013 by Springer. She was an invited speaker at MIWAI 2011 and has served as Program Co-Chair for MIWAI 2013, RSKT 2011, RSCTC 2010 and JRS2007. She has published over 34 articles in the past 6 years. She is the recipient of a TUBITAK Fellowship (Turkey) for 2015.

The focus of her research is in fundamental and applied research in machine learning and intelligent systems. Her current interests are in foundations of granular computing techniques (rough sets and near sets) with applications in social networks, text categorization and mining and analysis of perception-based image and audio information. Her research is supported by NSERC Discovery and Engage Grants.

As an academic, what is your favourite part of your job?

I love working with young minds. I enjoy teaching and mentoring them. I also love sharing my research interest in machine learning. I am happiest when I am in class. I love exploring solutions to new problems and taking my students with me along this journey.

What are you researching and what excites you about it?

My research is primarily in machine learning. Specifically, my focus is on fundamental and applied aspects of computational intelligence methods in machine learning. The explosion of large volumes of data have opened new and exciting research problems in areas such as natural language processing and social networks. This is a very challenging and exciting time to be a computer scientist.

What types of professions can students graduating in your field enter?

Students graduating with a computer science degree can find opportunities in many sectors of the economy. As we move into a digital economy, job opportunities for students in my field (with specialization in machine learning) look very promising.

Is your workplace male-dominated? If so, how do you negotiate being a woman in a male-dominated workplace and/or field?

Yes. I have always been confident in my abilities and have found colleagues who have been supportive.

How do you foster and encourage diversity in your workplace?

By accepting students from diverse countries and cultures in my research group.

What kinds of systemic support could institutions provide to help encourage girls and women to pursue careers in science and engineering?

Several studies have shown that it is very important to provide support for girls at the middle and high school level since the percentage of girls interested in STEM subjects falls dramatically. Also, scholarships at all levels will help retain young women at the university level.

What advice would you give to girls or young women who are interested in careers in science or engineering?

My advice is to be strong and believe in yourself. Let no one deter you from your aspirations. It is a wonderful and fulfilling career, if you make it so.

As a professional in science or engineering, who are your role models and mentors?

My role model has been my mother, who is a retired Professor in Mathematics, from College of Engineering, Osmania University, India.