How can we use computer algorithms to find multiple sclerosis earlier, more accurately, and more confidently? In his talk, Grey will demonstrate how a machine learning technique called dictionary learning can help doctors find scar tissue in patient brain scans in order to better detect this degenerative disease. Yet, as Grey has found, even though the math may seem complicated at first, the simplest solutions often work best. Grey Kuling is a mathematician and physicist, originally from Saint John, New Brunswick.

He completed his undergraduate at University of New Brunswick in physics and recently completed a Masters in Mathematics at York University. He is currently enrolled in the two year Master’s program of Medical Biophysics at University of Toronto. Kuling originally planned to be a professional dancer from childhood before finding a talent in mathematics. His passion for performing arts has enriched his experience to be an enthusiastic teacher of mathematics. He believes everyone is capable of understanding complex math with the proper guide. He is pursuing research currently in automatic segmentation of medical images and radiation modelling for cancer treatment.