Presented by: Anish Verma, 1QBit
An accessible overview of quantum computing highlighting recent advances in the industry will be given, with applied examples of how quantum algorithms can be used to solve applied problems in finance. In particular, a quantum machine learning framework to solve a credit scoring problem and a hybrid quantum-classical algorithm to solve a portfolio optimization problem are demonstrated. The talk will also feature an interactive Q&A session to answer any questions the audience has about quantum computing in general and its current and near-term applications.
Anish R. Verma is a quantum computing practitioner and enthusiast having worked for 3 years as a research scientist at 1QBit – a Vancouver-based quantum computing and artificial intelligence company – where I explored the applications of quantum computing and AI to finance. During that time, he was also selected for secondment at the Quantum Algorithms Institute, to advance the commercial adoption and broader outreach of quantum computing. Currently, Anish works at the Good Chemistry Company, advancing their products that combine modern high performance cloud computing, quantum computing, and machine learning for cutting edge molecular simulations.
Registration for the IMI BIGDataAIHUB Seminar Series is open to anyone that would like to attend. No prior knowledge is required.
To register for the event, visit the official registration page.
The IMI BIGDataAIHUB Seminar Series covers a range of topics related to big data and artificial intelligence. Students, staff, faculty, alumni and members of the broader community are welcome!
Seminars are offered from November until March and can be found listed below. Seminars are typically offered remotely via Zoom. Occasional sessions may be offered in person. See the full schedule for the Seminar Series here.
Students will have their participation added to their Co-Curricular Record (CCR).