Webinars and Blogs
Seminar, Jan 2024: Guest lecture at the at the University of Toronto's Data Sciences Institute on Applied machine learning - Course link
In this online lecture at the University of Toronto's Data Sciences Institute course on ML, I presented an overview of applied machine learning techniques using examples of my research projects on payments and banking, and discussed the opportunities and challanges of using ML.
Seminar, Nov 2023: Guest lecture at the Indian Institute of Management Ahmedabad (IIMA) on Payments Data and Machine Learning: Opportunities and Challenges - Webinar link
In n the age of AI and Big Data, witness the profound impact on the payments ecosystem, accelerated by rapid digitization in the wake of COVID-19. This seismic shift generates a surplus of high-frequency payments data, aligning seamlessly with advancements in AI, ML, and Quantum Computing. This seminar provides a comprehensive overview, unveiling practical use cases spanning supervised, unsupervised, and reinforcement learning. Explore the promising synergy between payments data and advanced analytics
In the modern digital economy, transactions encompass the exchange of products, services, or money, which are settled through various electronic systems, including wholesale, retail, and instant payment systems. Quantum computing is emerging as a transformative tool for optimizing the efficiency of such payment systems, offering the potential to significantly enhance liquidity and settle transactions more effectively.
In this article, I talk about nowcasting, the process of predicting the present. It is an exciting practical application of supervised machine learning that has yet to be widely known. First, the article introduces where nowcasting is useful and then talks about how ML can be used, with a focus on macroeconomic applications.
Webinar, Mar 2023: Guest Lecture at University of Toronto's DSI on Payments Data and Machine Learning - Closed session - weblink
In this online guest lecture at the University of Toronto's Data Science Institute, I presented an overview of payments data and machine learning using some examples of my research projects, and discussed the opportunities and challanges of using ML for payments research.
Webinar, Feb 2023: Improving the Efficiency of Payments Systems Using Quantum Computing - Webinar link
In this Quantum FinTech Webinar series organized by Rethinc. Labs at University of North Carolina, Kenan-Flagler Business School, we present our paper in which, we test the potential of quantum computing for payments settlement optimization in high-value payments systems.
In this article, I summarize key lessons from 2023 AEA's continuing education session on ML and Big Data for Economic research and analysis with a focus on the following key questions: 1. when ML is useful in economics? 2. which ML models are recommended? and 3. how to use ML for your economic applications?
In this short article, I share my experience of learning AI/ML and building a career in data science. I also provide links to various resources I use to strengthen my knowledge and deepen my understanding of these topics.
In our conversation on his alternate data podcast show, Mark and I discuss how the Bank of Canada is using payments data in innovative ways to make macroeconomic predictions and the outlook for central banks using various other alternative data for economic policy and research.
Webinar, Oct 2021: Estimating policy functions in payments systems using reinforcement learning - Webinar link
In this webinar at the Economics of Payments X conference (EoP-X), I present our paper (joint with many coauthors) about using reinforcement learning to estimate the optimal liquidity management decisions of the banks participating in high-value payments systems.