About this event
Can We Trust Our Forecasts?
We all want to know the future—especially in industry, where every decision hinges on a prediction. Sales forecasts. Financial forecasts. Supply chain forecasts. In many ways, data science is the business of forecasting. Yet, despite our best models, our predictions often fail when we need them most. Why do our forecasts break down, and how can we make them more reliable?
Join us for a talk with Dr. Aditya Prakash (Georgia Tech) as he shares cutting-edge research on AI-driven time series forecasting—techniques already used by Walmart, Facebook, and other industry leaders to improve accuracy, handle uncertainty, and build more robust predictive models. 🚀
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B. Aditya Prakash is an Associate Professor at Georgia Tech and CSE Associate Chair for Academic Affairs. He holds a Ph.D. from Carnegie Mellon and a B.Tech from IIT Bombay. A leading researcher in AI, machine learning, and big-data analytics, he has published 100+ papers, holds two U.S. patents, and has received multiple best-paper awards. His work has been used by ORNL, the CDC, and Walmart and has won industry challenges like the Catalyst COVID-19 Symptom Challenge. Recognized as one of IEEE’s “AI Ten to Watch”, he has also received NSF CAREER and Facebook Faculty Awards. His research focuses on large-scale networks, time-series forecasting, and uncertainty modeling, with applications in health, urban computing, and security.
