Webinar Series
Introduction to Optimization: Practical Strategies for Solving Industry Use Cases
Webinar Overview
Date: Jul 8, 2026
Time: 11:00am CDT (4:00pm UTC)
Most optimization problems in industry don't show up looking like a textbook exercise. They show up as a logistics puzzle, a sensor reading that doesn't add up, or a routing problem that's too slow to solve in real time. In this Expert Spotlight Series session, ThinkOnward Community Member, Dr. Tien Dung Le, a 15-plus-year data scientist and Kaggle Grandmaster, walks through two representative case studies developed within the ThinkOnward community: building an algorithm to route workers across a map for maximum reward under time and budget constraints, and locating hidden heat sources from noisy sensor data using nonlinear optimization. Rather than just presenting the final answer, Tien Dung shows the actual process: how to analyze a problem, build a baseline, visualize what's going wrong, and iterate toward a faster, better solution when the first approach hits a wall. A grounded, practical look at how optimization gets solved in the real world approaches are developed in practical settings, not just in theory. The Expert Spotlight Series is ThinkOnward's recurring webinar program built around the expertise inside our community. Each session features a ThinkOnward Community Member presenting original work and hard-won knowledge across subsurface science, engineering, and AI. July 8, 2026 | 11:00 AM CT | 16:00 UTC
Registration
Speaker
Tien Dung Le is a Big Data & AI Scientist with 15+ years of experience in data integration, advanced analytics, and intelligent systems development. He is specialized in collecting and harmonizing data from diverse sources, and exposing it through scalable, high-performance channels. He currently focus on leveraging data analytics, NLP, multimodal, and generative AI to extract actionable insights and deliver competitive advantages for clients.
His recent work includes automating document and email processing, enhancing data related to correspondent banking and legal entities, optimizing vehicle routing for incident response, and developing AI-based Anti-Money Laundering (AML) systems. This includes building supervised AML foundation models, exploring anomaly detection for novel laundering schemes, and constructing diffusion-based social graphs to uncover suspicious networks.