Talks, posters & workshops
Presentations of our work at research meetings, and the hands-on workshops I have taught or helped teach, from NVIDIA Deep Learning Institute courses to a SIIM learning lab on running local LLMs behind institutional firewalls.
Talks & presentations
Multimodal AI for Precision Oncology: From Data Integration to CDS
Waqas A, Tripathi A
Co-presenter
Image: Stanford MedAI video thumbnail
Watch the talk →Clinically Integrated Multi-Agent Artificial Intelligence System for Automated Extraction of Neuro-Oncology Biomarkers from Pathology Reports
Elzaafarany O, Tripathi A, Mokhtari S, Rasool G
Coauthor
CLeVER Multi-Agent AI Orchestration for Temporal-Aware Clinical Variable Extraction from Unstructured Medical Records
Tripathi A, Waqas A, Rasool G
AI-Driven Extraction of Key Clinical Data from Pathology Reports to Enhance Cancer Registries
Tripathi A, Waqas A, Venkatesan K, Ullah E, Schabath MB, Bui MM, Rasool G
Image: results from the follow-on consensus study, Tripathi et al. (2026), Laboratory Investigation, © 2025 USCAP, published by Elsevier
Accelerate Cancer Research With AI-Driven Multimodal Data Integration
Tripathi A, Waqas A, Yilmaz Y, Rasool G
Image: the poster PDF from the GTC session page, titled "HoneyBee: Developing Multimodal AI-Ready Datasets from Public Cancer Repositories"
View the poster →
Extraction of Discrete Information from Pathology Reports Using Local and Private LLMs
Rasool G, Tripathi A, Waqas A, Ullah E, Bui MM
Coauthor
Image: example from the later consensus-study preprint, Tripathi et al. (2025), medRxiv, CC BY-NC-ND 4.0
Advancing Cancer Research Through Integrated Multimodal Data Analysis: A Comprehensive Framework for Precision Oncology
Tripathi A, Waqas A, Yilmaz Y, Rasool G
Pan-cancer Learning for Survival Prediction
Waqas A, Tripathi A, Mukund A, Stewart P, Naeini M, Rasool G
Teaching & workshops
Running Local LLMs Behind Institutional Firewalls: Hands-On Guide for Secure Clinical AI
Speaker and co-presenter, Learning Lab LL4022, with Ghulam Rasool and Asim Waqas. Instruction covered model selection, deployment behind institutional firewalls, and LLM workflows for imaging and pathology.
Image: speaker headshot
Speaker profile →
Scalable Multimodal AI in Oncology Using HONeYBEE: From Embeddings to Clinical Impact
Teaching assistant
Image: HONeYBEE patch-extraction output, lab-rasool/HoneyBee, CC BY-NC-ND 4.0
Workshop →Building Transformer-based Natural Language Processing
Teaching assistant for two student workshops
Workshop →