Western Mass Statistics and Data Science

Hi All,
The Amherst College Data Science Initiative (https://www.amherst.edu/about/science_at_amherst/data-science-initiative) is organizing a talk about a practical strategy for establishing enterprise-grade AI using open‑source software.

Speaker: Serdar Kadioglu (Fidelity)

Title: Building Scalable and Responsible Enterprise AI with Open‑Source Foundations

Abstract:
Artificial Intelligence is reshaping how organizations make decisions, serve customers, and build new products. Yet many enterprises still struggle to move from isolated experiments to AI systems that are reliable, scalable, and aligned with their values.
This talk outlines a practical strategy for establishing enterprise-grade AI using open‑source software. I’ll walk through five pillars that guide successful AI adoption: learning from historical data, improving systems through real‑time feedback, making intelligent decisions at scale, creating useful automated assistants, and ensuring responsible and transparent AI practices.
Through a suite of open-source tools, we’ll explore how modular and interoperable tools can help organizations innovate faster while maintaining fairness, accountability, and long‑term sustainability.

Bio:
Serdar Kadioglu is a Group Vice President in the AI Center of Excellence at Fidelity Investments and an Adjunct Associate Professor in the Department of Computer Science at Brown University. He previously led the Advanced Constraint Technology group at Oracle and worked at Adobe. He established strategic collaborations across industry and academia partnering with Amazon, Carnegie Mellon University, Harvard, and NVIDIA. Dr. Kadioglu's research is at the intersection of AI and Optimization with a focus on building robust and scalable products while contributing to the open-source ecosystem.

Light fancy refreshments will be served before the talk.

DataFest is a nationally-coordinated undergraduate competition in which teams of up to 5 students work over a weekend to extract insight from a rich and complex data set. Previous years’ data sets have included crime data from the LAPD, dating data from eHarmony, and energy use data from GridPoint. This year’s data set will be revealed at the opening of the event on Friday evening. At the conclusion of the competition, each team will have 5 minutes to make a presentation to a panel of judges. Each panel of judges will select a team for the “Best in Group” prize, and the entire group of judges will determine a “Best in Show” prize. Other additional prizes may be awarded.
The mission of DataFest is to expose undergraduate students to challenging questions with immediate real-world significance that can be addressed through data analysis. By working in teams, students with varying skill sets will combine their efforts and expand their collective data analysis horizons. Interaction among students, as well as with outside consultants will promote the sense that data analysis is a dynamic, engaging, and vibrant part of our society, as well as a realistic, practical, and fun career path.