Forecasting Impact
Forecasting Impact is a bimonthly podcast that aims to disseminate the science and practice of forecasting by introducing prominent academics, practitioners, and visionaries in the forecasting domain. Our vision is to help grow the forecasting community, foster collaboration between academia, industry, and governments, and promote scientific forecasting and good practices.
We will discuss a range of forecasting topics in economics, supply chain, energy, social goods, AI, machine learning, data analytics, education, healthcare, and more.
Forecasting Impact episodes are also available on the IIF YouTube Channel @IIForecasters.
Podcast Team
Chair and Co-host: Dr. Laila Ahadi-Akhlaghi, Senior Technical Advisor at JSI.
Additional co-hosts:
- Dr. Mahdi Abolghasemi, Lecturer in Data Science at The University of Queensland,
- George Boretos, Founder & CEO at FutureUP,
- Dr. Faranak Golestaneh, Data Science Senior Manager at Commonwealth Bank of Australia,
- Mariana Menchero, Senior Forecaster at Nixtla, and
- Arian Sultan Khan, Data Analyst at VAN
Co-hosts in the past have included: Michał Chojnowski, Shari De Baets, Elaine Deschamps, Dr. Sevvandi Kandanaarachchi, Bahman Rostami-Tabar, Anna Sroginis, and Sarah Van der Auweraer.
We welcome your feedback, questions, and suggestions. Please contact us at forecastingimpact@forecasters.org
Forecasting Impact
David Schmitt, on Transportation Forecasting
In this episode, we delved into the dynamic realm of transportation forecasting, exploring a wide array of ideas and questions.
Our discussion with David began by examining the primary data sources and methodologies that drive modern transportation forecasting. We continued by highlighting the pivotal role of real-time data, GPS technology, and advanced algorithms in providing accurate insights into traffic patterns, public transit ridership, and the trajectory of mobility trends. We also discussed the integration of emerging technologies like autonomous and electric vehicles, showcasing their transformative potential in shaping transportation models and infrastructure.
From a consulting and practical perspective, we explored the challenges of ensuring the accuracy and reliability of transportation forecasts and contemplated the influence of AI and machine learning on the future of transportation forecasting.