Edmon Begoli

Edmon Begoli

Executive Director, Center for AI Security Research (CAISER)

Contact

865.576.0599 | BEGOLIE@ORNL.GOV

All Publications

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

The Effects of Compounded Model Size Reductions on Adversarial Robustness

Lantern: An Interactive Adversarial AI Workbench

DOME: Directional medical embedding vectors from Electronic Health Records

A Compound Data Poisoning Technique with Significant Adversarial Effects on Transformer-based Sentiment Classification Tasks

Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models

Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program

Question-answering system extracts information on injection drug use from clinical notes...

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

Multimodal representation learning for predicting molecule–disease relations...

cpgQA: A Benchmark Dataset for Machine Reading Comprehension Tasks on Clinical Practice Guidelines and a Case Study Using Tra...

BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Task

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

A Lakehouse Architecture for the Management and Analysis of Heterogeneous Data for Biomedical Research and Mega-biobanks

2021 GeoAI Workshop Report: The Trillion Pixel Challenge

Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data

Hospice Landscape Report

Watermarks in stream processing systems: semantics and comparative analysis of Apache Flink and Google cloud dataflow

What Clinical Trials Can Teach Us About the Development of More Resilient AI for Cybersecurity

Pharmacoepidemiology, Machine Learning and COVID-19: An intent-to-treat analysis of hydroxychloroquine, with or without azithromycin, and COVID-19 outcomes amongst hospitalized US Veterans

Solving Hard Problems with AI: Dramatically Accelerating Drug Discovery Through A Unique Public-Private Partnership

Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization

Standardized Architecture for a Mega-Biobank Phenomic Library: The Million Veteran Program (MVP)