Duke & Chen Institute Joint AI Boot Camp 2025 Concludes Successfully

Events
Published

May 31, 2025

Duke & Chen Institute Joint AI Boot Camp 2025 Concludes Successfully

Duke & Chen Institute Joint AI Boot Camp 2025 Concludes Successfully

Five-day intensive program explores cutting-edge applications of AI in healthcare and medical research

May 12-16, 2025 ยท Duke University

Event Overview

The Duke & Chen Institute Joint Boot Camp for AI & AI Accelerated Medical Research concluded successfully on May 16, 2025, after five intensive days of cutting-edge presentations and discussions. The program, hosted by Prof. Jian Pei, brought together distinguished faculty and participants to explore the latest developments in medical artificial intelligence.

Daily Program Schedule

Day 1 (May 12)
Challenges & Opportunities in Translating AI to Healthcare
Prof. May Dongmei Wang (Georgia Tech) on pHealth paradigm and foundation models; Prof. Wei Wang (UCLA) on medical information retrieval in the LLM era, CliBench benchmarking, and medical information extraction models.
Day 2 (May 13)
Causal Generalist Medical Artificial Intelligence (CGM-AI)
Prof. Hongtu Zhu on CGM-AI integration and biomedical knowledge graphs; Prof. Huaxiu Yao on CGM-LLMs and multi-agent systems; Prof. Qiao Liu on omics foundation models; Prof. Xin Wang on medical imaging foundation models.
Day 3 (May 14)
Harnessing Real World Evidence for Better Clinical Trials with AI
Prof. Fei Wang (Weill Cornell) on real-world evidence, target-trial emulation, and federated learning; Prof. Bang Liu (University of Montreal) on intelligent medical agents and multi-agent system design.
Day 4 (May 15)
Scalable and Responsible Natural Language Processing to Transform Healthcare
Prof. Monica Agrawal (Duke) on LLMs in healthcare, EHR information extraction, and responsible AI deployment; Additional sessions on advanced machine learning for imaging-omics analysis and federated learning.
Day 5 (May 16)
Foundation Models and Knowledge Graphs for Human Genome and Multi-Modal Data
Comprehensive sessions on foundation models for human genome research, knowledge graphs for multi-modal biomedical data, 3D chromatin organization, and causal inference using large-scale datasets.
50+
Participants
10+
Faculty Members
10+
Technical Talks

Key Research Insights

The program highlighted several groundbreaking research directions, including the evolution from traditional Generalist Medical AI to Causal Generalist Medical AI (CGM-AI), which incorporates causal inference capabilities for more robust medical decision-making. Topics covered advanced areas such as federated learning, target trial emulation, and multimodal integration techniques.

๐Ÿ“š Course Materials & Resources

Comprehensive Course Notes: Detailed notes by Patricia Xiao provide insights into presentations and discussions.

Official Program: ai-bootcamp.cs.duke.edu

Note: Participant notes reflect personal understanding and should not be considered an official record of the event.

Looking Forward

The success of this boot camp demonstrates the growing importance of interdisciplinary collaboration in advancing medical AI. The program's focus on both technical innovation and practical implementation challenges positions participants to contribute meaningfully to the evolving landscape of healthcare technology.