Devinder Kumar, NextAI SiR and Intel® Student Ambassador, chats about his work with machine learning for the healthcare and finance industries.
Tell us about your background.
I am a first year PhD student at Vision and Image Processing (VIP) lab, University of Waterloo and Machine Learning Research Group (MLRG), University of Guelph. Before this, I completed my Masters in WAVE lab & VIP lab at University of Waterloo, as well as, a research engineer in LIP-6 - UPMC-Sorbonne University, Paris. My research centers on deep learning and its application in Computer Vision. Specifically, the research problem I am currently focusing on is: How to make current deep models interpretable and compact enough to be scalable for real-time client side applications.
What got you started in technology?
I always wanted to create something that could reach and help millions of people in their daily lives. I saw technology and especially machine learning as a tool that can help me in achieving this dream.
What projects are you working on now?
Currently I am working on two projects, one is in the domain of Explainable AI – where I develop approaches for explaining the decision-making process of deep neural networks. I explain this project more in an articles published on University of Waterloo – Engineering’s website and also on VICE Motherboard site. The other project that I just started is related to semi-supervised learning where the aim is to efficiently learn the association between input and output using very few examples. You can follow along with my work on my personal blog.