USF Data Science & Artificial Intelligence Speaker Series

We are excited to welcome Sagar Jadhav to the USF Data Science Speaker Series.

About the Speaker
Sagar is a Principal AI Architect at Rubrik, where he builds AI agent frameworks, conversational intelligence platforms, and enterprise governance systems. With more than 20 years of experience, he has designed production-grade AI systems across retail, healthcare, and enterprise software, including platforms processing billions of transactions each month. He is also an active mentor to early-career engineers focused on building trustworthy AI at scale.

Talk: Your AI Agent Is Probably Wrong — How to Build Ones That Aren’t
Everyone is building AI agents. Few are rigorously testing them.

Production AI agents often operate at 70 to 90 percent accuracy. That may sound acceptable, but the remaining gap can mean missed security alerts, incorrect recommendations, or misleading customer interactions. Many teams rely on informal testing instead of structured evaluation and therefore do not truly know how reliable their systems are.
In this session, Sagar shares a practical framework for building AI agents that businesses can trust. He will introduce structured evaluation strategies used at Rubrik, explain when an agent is actually the right solution, and show how production systems combine deterministic guardrails with language model reasoning. The session includes a live walkthrough of a Service Desk Triage Agent and a look at a real evaluation pipeline.
You will leave with a practical playbook for evaluating, testing, and improving AI agents at production scale.

We hope you can join us.

#DataScience #ArtificialIntelligence #AIEngineering #AIAgents #LLM #MachineLearning #USFCA #USFMSDSAI #DataInstitute #TechTalk #AIInProduction

We’re thrilled to welcome back Josh Starmer back to the USF Data Science Speaker Series!

Description: Although Large Language Models and AI are known to generate false and misleading responses to prompts, relatively little effort has gone into understanding how we can quantify the confidence we should have in the output from these models. In this seminar, I will illustrate the problem using a simple neural network and then demonstrate two methods for quantifying our confidence in the model outputs. I will then show how these methods can be applied to Large Language Models and AI.

About the Speaker: Josh Starmer is the person behind the popular YouTube channel, “StatQuest with Josh Starmer.” Since 2016, Josh has used an innovative and unique visual style to clearly explain Statistics, Data Science and Machine Learning concepts and algorithms to curious people all over the world. Rather than dumb down the material, Josh brings people up with simple examples worked through, step-by-step, using pictures to make sure every main idea is easy to understand and remember. By breaking down even the most complicated algorithms into bite sized pieces, StatQuest has helped people, all over the world, win data science competitions, pass exams, graduate from school, and get jobs and promotions.

RSVP now to secure your spot!

#USFCA #USFMSDSAI #DataInstitute #DataScience #MachineLearning #ArtificialIntelligence #LLM #StatQuest #TechTalk

We are excited to welcome David Schoeller-Diaz, USF Class of 2006 alumnus and global program leader, for a special session on practical ethics in data science and artificial intelligence. This talk complements our cohort’s ethics module and the USF Data Science Speaker Series.

Talk Description: Most ethical decisions in data science are not dramatic dilemmas. Rather, they are embedded in everyday choices about how we formulate problems, what we include or exclude from our data, and who bears the consequences of our models. In this interactive session, David will share a practitioner's framework for ethical reasoning drawn from 20 years of building data-driven systems in complex, high-stakes environments, from cybersecurity operations protecting hospitals and NGOs to geospatial intelligence analysis and data systems that informed a national peace process. The session will explore how these experiences connect to the ethical challenges data scientists face today: AI governance and accountability, the concentration of power in the AI ecosystem, and the question of how to build technology that serves broad human flourishing. Rather than treating ethics as a constraint on technical work, this talk argues that ethical judgment is a dimension of professional craft, making data scientists more effective, more trusted, and more durable in their careers. Expect an interactive format with live polls, real-world scenarios, and open discussion throughout.

About the Speaker: David Schoeller-Diaz is a global program leader and systems builder with 20 years of experience leading data-driven operations across humanitarian, security, and technology sectors. His career spans intelligence analysis for U.S. Southern Command, humanitarian information management with iMMAP and the United Nations, cybersecurity partnerships at the CyberPeace Institute, academic research at the Harvard Humanitarian Initiative, and co-founding a social enterprise in Colombia. He holds a Master of Arts in Law and Diplomacy from The Fletcher School at Tufts University, an Executive Master in International Business from ESCP Business School, a PMP certification, an Executive Data Science Certificate from Johns Hopkins University, and a BA in Political Science from USF, where he was a McCarthy Fellow. David is based in the San Francisco Bay Area.

This talk is especially relevant for students interested in responsible artificial intelligence, trust and safety, policy, and governance.

We hope you can join us.
#DataScience #ResponsibleAI #AIEthics #AIGovernance #TrustAndSafety #USFCA #USFMSDSAI #DataInstitute #TechForGood #Cybersecurity #DataScienceSpeakerSeries