Kumar Abhishek

Computing Science | doctoral degree | Faculty of Applied Sciences

Tell us a little about yourself, including what inspires you to learn and continue in your chosen field

I am a PhD student in the Medical Image Analysis Lab (MIAL), where I work on developing and applying computer vision and machine learning algorithms to interpret medical images, specifically skin images. What draws me to this field is that it sits right at the intersection of computer science and healthcare, and I get to work on technically interesting problems that also happen to have real clinical relevance.

Why did you choose to come to SFU?

During my undergraduate studies at IIT Guwahati in India as well as during my employment after that, I had worked in the areas of image processing and computer vision. I wanted to expand my knowledge in these areas and given SFU's stellar reputation in visual computing research, I chose to pursue graduate studies here. Professor Ghassan Hamarneh's research in medical image processing was particularly interesting to me because of its potential impact on healthcare in the real world, and therefore I joined SFU for an MSc degree in 2018. I obtained my MSc degree, and decided to pursue a PhD degree in the same lab under his supervision.

How would you describe your research or your program to a family member?

The primary focus of my research has been on medical image analysis for dermatological applications, particularly, skin cancer detection. My MSc thesis research was on novel algorithms for improved and robust skin lesion segmentation from images; think of it like teaching a computer to trace the exact boundary of a suspicious mole. I have continued to work on that during my PhD, in addition to a number of other problems involving other medical imaging modalities (such as X-Ray and PET) and I am presently working on analyzing and modelling multi-annotator data. This means that instead of working with images that have only one expert's annotations, I study images with multiple experts' annotations to analyze their (dis)agreement and model their preferences.

What three (3) keywords would you use to describe your research?

Medical image analysis, image segmentation, multi-annotator data

How have your courses, RA-ships, TA-ships, or non-academic school experiences contributed to your academic and/or professional development?

I have had the privilege of being a research assistant in the Medical Image Analysis Lab (MIAL), which has helped me better understand and identify interesting research directions, and develop a sharper sense for what problems are worth pursuing. I have also served as a teaching assistant for multiple offerings of two upper-division undergraduate courses in areas related to my research, which has provided me experience with mentoring students' projects and answering their questions about the course topics. Participating in the Three-Minute Thesis (3MT) competition was also a valuable experience, as it challenged me to communicate my research clearly and engagingly to a general audience. Beyond academic roles, I was recently fortunate enough to join the organizing committee of the Annual ISIC Skin Image Analysis Workshop, where I help coordinate the scientific program and get to work alongside leading experts in the field. Together, these experiences have helped me grow as a researcher while also shaping how I communicate, collaborate, and contribute to the broader research community.

Have you been the recipient of any major or donor-funded awards? If so, please tell us which ones and a little about how the awards have impacted your studies and/or research

Yes, I have received the Special Graduate Entrance Scholarship, the Computing Science Graduate Fellowship, the DBMiner Graduate Scholarship, the Helmut & Hugo Eppich Family Graduate Scholarship, the Borden Ladner Gervais Graduate Scholarship, and the Brian J. Blaha Memorial Graduate Scholarship in Computing Science. I am deeply grateful for these scholarships as they have been immensely helpful and have allowed me to focus more on my research.

What have been the most valuable lessons you've learned along your graduate student journey (or in becoming a graduate student)?

Everyone's research and career trajectory is different. Periods of rapid progress are often interleaved with stretches of slow, seemingly glacial progress, and that is alright as long as you keep pushing and actively seeking advice from your supervisor(s). Collaborative projects are an excellent way to learn to work with others and get feedback from a diverse set of sources. On a slightly lighter note, in terms of the big picture of what a graduate degree is, I really like Matt Might's "The Illustrated Guide to a Ph.D."

How do you approach networking and building connections in and outside of your academic community?

The members of MIAL are an amazing group of people to work with, and I am really appreciative of how supportive and helpful my supervisor and my colleagues from MIAL are, which makes seeking help and collaborating on projects from other areas a great experience. Our lab also has collaborations with hospitals and research centers outside SFU, which again helps with expertise from different domains. Beyond the lab, I attend conferences, seminars, other events to meet peers from both academia and industry who work in related research areas, and over time, some of these connections may turn into collaborations. For instance, the ISIC Skin Image Analysis Workshop started as a venue where I first presented my research at in 2020 and has since become a community I have been fortunate enough to help organize. And I think this has been the most rewarding pattern in my experience: showing up consistently, being genuinely curious about what others are working on, and then naturally letting connections develop from there.

Is there anything else you'd like to share?

I recently had the opportunity to present in the annual Three-Minute Thesis (3MT) competition. It was a fantastic opportunity to present to an audience not necessarily from my specialization, and the process of distilling and communicating my research in a manner that is accessible and engaging to the audience, was both challenging and rewarding. It gave me a deeper appreciation for the importance of being able to explain not just what I do, but also why it matters and its impact.

Contact Kumar:kabhishe@sfu.ca