Conference Schedule

The session schedule from the 2026 Applied Machine Learning Conference is available below. Video recordings for many sessions are available on the session detail pages, which are accessible by clicking or tapping the session name in the schedule.

Friday, April 17, 2026

Auditorium 5 Auditorium 4 Auditorium 3 Auditorium 2

8:00 am

Auditorium 5
8:00 am → 60 min

Registration

9:00 am

Auditorium 5
9:00 am → 60 min

Keynote: Graphics, AI, and the Quest for New Experiences at NVIDIA

10:00 am

Auditorium 5
10:00 am → 20 min

Break

10:20 am

Auditorium 5
10:20 am → 30 min

Ex Uno Plures: Agents for Everyone

Auditorium 4
10:20 am → 30 min

Digital Twins in Healthcare

Auditorium 3
10:20 am → 30 min

Auditorium 2
10:20 am → 30 min

Beyond A/B Testing: Practical Contextual Bandits for Dynamic Pricing in Production

10:55 am

Auditorium 5
10:55 am → 30 min

Pricing Intelligence: What AI economics means for leaders building and buying AI

Auditorium 4
10:55 am → 30 min

Lightweight Breast Cancer Detection Model: Parameter-Efficient Fine-Tuning & Knowledge Distillation

Auditorium 3
10:55 am → 30 min

Detecting AI-Driven Automation in E-Commerce Traffic Using Real-Time Behavioral Signals

Auditorium 2
10:55 am → 30 min

Teaching Sensors to Smell: Graphene Arrays, Time-Series Features, and ML

11:30 am

Auditorium 5
11:30 am → 30 min

Testing AI Agents: A Practical Framework for Reliability, Performance, and Governance

Auditorium 4
11:30 am → 30 min

Can Claude Code Save R?

Auditorium 3
11:30 am → 30 min

Pricing People into the Market: Combining Field Experiments and ML to Target Aid

Auditorium 2
11:30 am → 30 min

From Large-Scale Mobility Data to Behavioral Intelligence

12:00 pm

Auditorium 5
12:00 pm → 70 min

Lunch

1:10 pm

Auditorium 5
1:10 pm → 30 min

80% of ML Projects Fail - How to Let Them

Auditorium 4
1:10 pm → 30 min

Leveraging Taxonomic Structure in Classification on Large Label Sets

Auditorium 3
1:10 pm → 30 min

From Notebook to Pipeline: GPU Data Engineering at Startup Scale

Auditorium 2
1:10 pm → 30 min

From Data to Signals: A Journey Using AI and Agents

1:45 pm

Auditorium 5
1:45 pm → 30 min

The (Un)Reliability of Reasoning in Frontier Models

Auditorium 4
1:45 pm → 30 min

Leveraging a Hidden Forest to Improve the Prediction Accuracy of Random Forest Ensembles

Auditorium 3
1:45 pm → 30 min

It's Not Like The Movies: Managing Uncertainty When Tracking Objects in the Real World

Auditorium 2
1:45 pm → 30 min

Building Organizational Intelligence with Property Graphs, Agentic AI, and MCP

2:15 pm

Auditorium 5
2:15 pm → 20 min

Break

2:35 pm

Auditorium 5
2:35 pm → 30 min

Cognitive Memory for Coding Agents: Reusable Reasoning Across Platforms

Auditorium 4
2:35 pm → 30 min

Auditorium 3
2:35 pm → 30 min

Scaling Retrieval-Augmented Generation in Production using Semantic Caching

Auditorium 2
2:35 pm → 30 min

Modeling Research Organizations as Embedding Spaces

3:10 pm

Auditorium 5
3:10 pm → 30 min

Will We Hit Our Target? Real-Time Probabilistic Forecasting in Production

Auditorium 4
3:10 pm → 30 min

Human-Interpretable ML Explanations in High-Stakes Graph ML

Auditorium 3
3:10 pm → 30 min

The Future of OCR? Structured Text Extraction with LLMs

Auditorium 2
3:10 pm → 30 min

Examining Claude’s Constitution Through the Lens of the Value Chain of Ethical AI

3:40 pm

Auditorium 5
3:40 pm → 20 min

Break

4:00 pm

Auditorium 5
4:00 pm → 60 min

Keynote: Build Yourself Flowers

5:00 pm

Auditorium 5
5:00 pm → 90 min

Social Event at Vault Virginia

Saturday, April 18, 2026

Classroom 205 Classroom 206 Classroom 305 Capital One Hub

8:00 am

Capital One Hub
8:00 am → 60 min

Registration

9:00 am

Classroom 205
9:00 am → 90 min

Dimensionality Reduction in Action

Classroom 206
9:00 am → 90 min

Applications of Physics-Informed Neural Networks in Science: A Hands-On Tutorial

Classroom 305
9:00 am → 90 min

Systematic Development of Production Agents: An Evidence-Driven Approach

Capital One Hub
9:00 am → 90 min

10:30 am

Classroom 305
10:30 am → 30 min

Break

Capital One Hub
10:30 am → 30 min

Lightning Talks

11:00 am

Classroom 205
11:00 am → 90 min

Agentic Search: Rethinking Search Away From "Top 10 Results"

Classroom 206
11:00 am → 90 min

Catch What Your Model Misses: An Anticipatory Design Framework for Ethical AI Evaluation

Classroom 305
11:00 am → 90 min

When AI Joins the On-Call Rotation: Building an Incident Investigation Agent

Capital One Hub
11:00 am → 90 min

12:30 pm

Classroom 305
12:30 pm → 60 min

Lunch

Capital One Hub
12:30 pm → 60 min

Lightning Talks

1:30 pm

Classroom 205
1:30 pm → 90 min

Probabilistic Programming for Recommender Systems

Classroom 206
1:30 pm → 90 min

Best of Both Worlds: Combining Domain Knowledge with Deep Learning

Classroom 305
1:30 pm → 90 min

Real World MCP: Augmenting Model Context from Existing Data Sources

Capital One Hub
1:30 pm → 90 min

3:00 pm

Classroom 305
3:00 pm → 30 min

Break

Capital One Hub
3:00 pm → 30 min

Lightning Talks

3:30 pm

Classroom 205
3:30 pm → 90 min

DataEval: An End-to-End Data Analysis Tool for Machine Learning Development

Classroom 206
3:30 pm → 90 min

The Crisis in Science — and How to Defeat It

Classroom 305
3:30 pm → 90 min

From PDFs to Knowledge Graphs: Building Structured Document Intelligence with Docling-Graph

Capital One Hub
3:30 pm → 90 min

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Friday, April 17, 2026: Keynotes and Talks

Talks at the Violet Crown Cinema

The first day of the conference featured keynote presentations, four tracks of 30-minute talks, ample networking opportunities, and sponsor exhibitions at the Violet Crown Cinema in Downtown Charlottesville.

Saturday, April 18, 2026: Tutorials and Lightning Talks

Tutorials at UVA School of Data Science

The second day featured three tracks of practical, 90-minute tutorials that dove deeper into the latest tools and techniques used by modern data science and AI professionals, as well as ten lightning talks, at the University of Virginia’s School of Data Science.