Equivariant KAM Theory (and some other things, too!)
Speaker: Nicholas Faulkner (PhD candidate, Ontario Tech U), Room: UA 4170, Abstract: If you are a graduate student studying in MCSC program, the topic of KAM will probably not be that important to you. My thesis is two very long math proofs, that rely on tools from analysis, abstract algebra, linear algebra and topology. […]
Affective Data Science
Speaker: Steven Livingstone (Ontario Tech U), Room: SHA 249, Abstract: Affective Data Science lies at the intersection of statistics, machine learning, and psychology, and seeks to answer fundamental questions about human emotion using big data techniques. In my talk I will look at three of my recent projects in the field: data provisioning for […]
Digital Medicine and Digital Biomarkers
Speaker: Yan Fossat (Klick Labs), Room: SHA 249, Abstract: This talk will showcase recent developments in the field of non-invasive digital biomarkers and digital medicine. Case studies will be presented for medical devices, digital interventions, and real world examples of data analysis and modeling. Medical science relies on data to diagnose, prognose, and monitor […]
Algorithms for Queueing Systems with Reneging and Priorities Modeled as Quasi-Birth-Death Processes
Speaker: Dr. Amir Rastpour (FBIT, Ontario Tech U), Room: UA4170, Abstract: We consider a Markovian multiserver queueing system with two customer classes, preemptive priorities, and reneging. We formulate this system as an infinite level- dependent quasi-birth-death process (LDQBD). We introduce an algorithm that endogenously truncates the level and calculates lower and upper bounds on […]