John Anderson Garcia Henao

John Anderson García

Computer Scientist and Biomedical Engineer 🤖🩻🚀

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Projects

AssessNet

AssessNet-19 is a 2-stage pipeline for assessing COVID-19 severity from CT scans. First, 2D U-Net models segment lungs and lesions from CT slices. Then, 3D volumes are created and radiomics features are extracted, selected, and input into an XGBoost classifier for severity assessment.

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DiagnoseNet

DiagnoseNET is an open source framework for tailoring deep neural networks into different computational architectures from CPU-GPU implementation to multi-GPU and multi-nodes with an efficient ratio between accuracy and energy consumption.

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enerGyPU

enerGyPU is an open source monitor-tool, designed to automate the capture, storage and modelling the causal factors that determine an energy efficient execution while the target application is processing on heterogeneous platforms.

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Sepsis Risk Predictor Proj.

Sepsis Risk Predictor Project: An Open Source Platform for Clinical Data Integration and AI-driven Sepsis Detection ...

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Professional Experience

2024-

Visiting Researcher

Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Switzerland.

2023-

Visiting Researcher

Computational Intelligence to Predict Health and Environmental Risks Center (CIPHER), University of North Carolina at Charlotte, USA.

2020- 2023

Postdoctoral Researcher

Medical Image Analysis Group (MIA), ARTORG Center for Biomedical Engineering Research, University of Bern, Switzerland.

2016- 2020

Research Assistant

Models and Algorithms for Artificial Intelligence Group (MAASAI), Inria Centre of Sophia-Antipolis, University of Côte d’Azur, France.

2014- 2016

Research Assistant

High Performance and Scientific Computing Unit, Industrial University of Santander, Colombia.

2015- 2015

Master Internship

Parallel and Distributed Processing Group (GPPD), Institute of Informatics, Federal University of Rio Grande do Sul, Brazil.

2011- 2013

Computer Systems Analyst

Investment Fund Castilla Riopaila Colombina, Cali, Colombia.

Education

University of Bern

Master of Advanced Studies in Translational Medicine and Biomedical Engineering

2022 - 2024

M.A.S. Thesis: AI-Powered Clinical Decision Support Platform for Interstitial Lung Disease

Advisors: Prof. Dr. med. Alexander Pöllinger and mba. Mark Illi

Sitem-Insel School for Translation and Entrepreneurship in Medicine, Switzerland

University of Côte d'Azur

Doctor in Computer Science

2017 - 2021

Ph.D. Thesis: Green Artificial Intelligence to Automate Medical Diagnosis with Low Energy Consumption

Advisors: Prof. Dr. Michel Riveill and Prof. Dr. med. Pascal Staccini

Doctoral School of Computer Science and Technology, France

Industrial University of Santander

Master of Science in Systems and Computer Engineering

2014 - 2016

M.Sc. Thesis: Energy-Aware to Scale Large Scientific Applications on Heterogeneous Architectures

Advisors: Prof. Dr. Carlos J. Barrios H. and Prof. Dr. Philippe O. A. Navaux

School of Systems and Computer Engineering, Colombia

Central University of Valle del Cauca

Bachelor of Science in Systems Engineering (with distinction)

2007 - 2012

B.Sc. Thesis: Implementation of a Grid Computing to Support Research Projects

Advisor: Prof. M.Sc. Vivian M. Orejuela R.

School of Systems and Computer Engineering, Colombia

Publications and Presentations

2023

John A. García H., Arno Depotter, Danielle V. Bower, Herkus Bajercius, et al. A Multi-class Radiomics Method-based WHO Severity Scale for Improving COVID-19 Patient Assessment and Disease Characterization from CT Scans. Investigative Radiology Journal, 2023.

2022

Cristian Toro, Erick Villarreal, Vivian Orejuela, John A. García H. A Machine Learning-based Missing Data Imputation with FHIR Interoperability Approach in Sepsis Prediction. Latin American High-Performance Computing Conference, CARLA2022. Porto Alegre, Brazil.

2021

Herkus Bajercius, John A. García H., Arno Depotter, Maria Barroso, et al. Clinical Evaluation And Multi-Class Delineation Of A Multi-Centric COVID-19 AI-Based Segmentation Study. Conference on Clinical Translation of Medical Image Computing & Computer Assisted Intervention (CLINICCAI) 2021. Strasbourg, France.

2020

John A. García H., Good Practices on Parallel and Distributed Programming for Training Neural Networks. 11th International SuperComputing Camp (SC-CAMP) 2020. Virtual.

John A. García H., Frédéric Precioso, Pascal Staccini and Michel Riveill. DiagnoseNET: Automatic Framework to Scale Neural Networks on Heterogeneous Systems Applied to Medical Diagnosis. International Conference on IT Convergence and Security (ICITCS) 2020. Nha Trang, Vietnam.

2018

John A. García H., Frédéric Precioso, Pascal Staccini and Michel Riveill. Scalability Analysis of Mini-Cluster Jetson TX2 for Training DNN Applied to Healthcare. Nvidia GPU Technology Conference (GTC) Europe 2018. Munich, Germany.

John A. García H., Frédéric Precioso, Pascal Staccini and Michel Riveill. Parallel and Distributed Processing for Unsupervised Patient Phenotype Representation. Latin American High-Performance Computing Conference, CARLA2018. Bucaramanga, Colombia.

2016

John A. García H., Esteban Hernández, Philippe O. A. Navaux and Carlos J. Barrios H. Energy-awareness to Accelerate Large-scale Scientific Applications in Heterogeneous Architectures. The International Conference for High Performance Computing, Networking, Storage, and Analysis (Supercomputing Conference) SC16. Salt Lake City, Utah, USA.

John A. García H., Esteban Hernández, Philippe O. A. Navaux and Carlos J. Barrios H. enerGyPU and enerGyPhi Monitor for Power Consumption and Performance Evaluation on Nvidia Tesla GPU and Intel Xeon Phi. IEEE/ACM 16th International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2016, Cartagena, Colombia.

John A. García H., Philippe O. A. Navaux and Carlos J. Barrios H. enerGyPU for Monitoring Performance and Power Consumption on Multi-GPUs. NIvidia GPU Technology Conference (GTC) 2016. San Jose, USA.