Electrical Engineer Ph D
Resume:
Aldo Camargo
Ph.D. Electrical Engineering
# ****.*******@*****.***
Computer skills
Advanced: Python, R, C, C++, CUDA, MATLAB, Linux, Cloud Computing. Intermediate: Java, Spark
Imaging /AI skills
Image –
Video
Processing
Image and video processing using OpenCV, CUDA, OpenGL, OpenCL, DSP/FPGA Medical
Imaging
Ultrasound, Neuroimaging, FSL, Freesurfer, SPM5, SPM12, Dipy, Nilearn, Nibabel, etc Artificial
Intelligence
ML, DL, LLM, Generative AI, PyTorch, Tensorflow, Google Cloud, etc. Education
2017–2021 Ph.D. student Biomedical and Pharmaceutical Science, University of Liege, Liege – Belgium
Research focus: Development and Research of methods to study Disorder of Consciousness
(DOC) and SNPs (single-nucleotide polymorphism) interactions. 2015 Principles and Practices of Clinical Research, Harvard University - USA, 2006–2010 Ph.D. Electrical Engineer, University of North Dakota, Grand Forks – USA Research Focus: Development of real time algorithms for the computation of super-resolution video mosaicking from Unmanned Aircraft Systems (UAS). Experience
August
2023–pres
Senior Postdoctoral Fellow, University of Maryland, Baltimore,Maryland – USA Research focus:Alzheimer’s research using Arterial Spin Labeling MRI (ASL-MRI), PET-FDG, fMRI, MRI, cognitive scores using mathematical models, signal processing, Machine Learning and Deep Learning models. Study of sample entropy during resting and task fMRI for young adult subjects from HCP. Develop of new techniques to use ASL-MRI in the study of Alzheimer’s disease.
2012–pres Visitor Assistant Professor, UNI - Universidad Nacional de Ingenieria, Lima – Peru Courses Taught: Advanced Operative Systems, Real Time Systems with GPU, Open Source Coding, Computer Graphics, and Networking Programming, Machine Learning, Deep Learning, and Data Science.
February
2024–
November
2024
Researcher, Attune Neurosciences, Bel Air, Maryland – USA Develop GUI for the testing of Focused Ultrasound. Analyze MRI data from addiction and control subjects, write the manuscript for future publication. March
2023–July
2023
Senior Researcher, University of Maryland, Baltimore,Maryland – USA Research focus: Alzheimer’s research using Arterial Spin Labeling, sMRI, fMRI, rsfMRI, and Brain Entropy during resting and task fMRI for young adult subjects from HCP. Comparison of different 2D and 3D ASL sequences in the study of Alzheimer’s disease. Aug
2022–Feb
2023
Senior Machine Learning Scientist, Sonosa Medical Inc., Baltimore,Maryland – USA
Principal responsabilities:
Develop AI/ML/Statistical algorithms and pipelines for video and image processing of ultrasound data.
Develop digital signal processing algorithms.
Develop software applications.
Support design of preclinical and clinical studies.
Participate in the recruitment of new patients.
Collaborate on non-dilutive fundraising applications. 2019–2022 Postdoctoral fellow, University of Maryland, Baltimore,Maryland – USA Research focus: study of Alzheimer with Arterial Spin Labeling, PET-FDG, fMRI, MRI, cognitive scores using Mathematical models, signal processing, Machine Learning and Deep Learning. Study of sample entropy during resting and task fMRI for young adult subjects from HCP. Develop of new techniques to use ASL-MRI in the study of Alzheimer’s disease. 2017–2019 Researcher, University of Liege, Liege – Belgium Research focus: Research and development of methods to study Disorder of Consciousness
(DOC) and SNPs (single-nucleotide polymorphism) interactions. Detailed achievements:
Determine of the circadian and ultradian determination in DOC patients.
EEG data processing and analysis for DOC patients.
Participate in the multidisciplinary clinical discussion of patients.
DTI analysis for the DOC patients.
Insertion of functionalities on MBMDR software for the study of SNPs interactions based on multivariable statistics.
2015–2016 Researcher and CTO, Knotenloserin, Lima – Peru Research focus: Development and research of personalize technology for industrial applica- tions to include:.
Research in Deep learning (DL) and Convolution Neural Networks (CNN) for video surveillance applications.
Development of software for video surveillance using CNN and DL.
Development applications for the creation of panoramas based on images taken by small UAV (Unmanned Aircraft Vehicle).
2011–2015 Researcher - Engineer, I + T - Engineer and Technology, Lima – Peru Research Focus: Reseatch and development of customized technology for industry and consulting engineer to include:
Development of software for power systems ( Swap Smart)
Development of software for super-resolution of medical imaging (SuperRIVAM).
Development of software for compression of PDF files (20% - 90%)(ComprimePDF).
Development of several engineering studies for the industry in power systems, and power quality.
2010–2011 SQA - Software Quality Assurance Engineer, DTS, California – USA Testing and documentation of SDKs for audio processing for entertainment to include:
Development of automated test scripts for Windows and Linux.
Development of CMAKE files for the compilation of SDKs of audio processing.
Development of mobile applications for 5.1 effects using stereo input. 2006–2010 Graduate Research Assistant, University of North Dakota, Grand Forks – USA Computer Vision Researcher:
Development of real-time algorithms for computer vision in C/C++ and CUDA.
Development mathematical models for the computation of super-resolution mosaicking of video frames taken by UAS (Unmanned Aerial Systems)
Development of mathematical models for tracking of ground objects. Languages
English Advance level
French Intermediate level
Spanish Advance level - mother tongue
Publications
1. Camargo, Aldo, Gianpaolo Del Mauro, Wang, Ze. Cross Entropy Gradient Analysis for Alzheimer’s Disease. Preprint. Manuscript ready to submit to the Journal of Alzheimer’s Disease (JAD) December 2024.
2. Camargo, Aldo, Wang, Ze. ”Gradient Analysis for the Study of Alzheimer’s Disease”. Abstract for Alzheimer’s Association International Conference (AAIC) 2024. July 2024. 3. Camargo, Aldo, Del Mauro. Gianpaolo, Wang, Ze. ”Task-induced changes in brain entropy”. Journal of Neuroscience Research. Feb. 2024.
4. Hongli Fan, Henk J.M.M. Mutsaerts, Udunna Anazodo, Daniel Arteaga, Koen P.A. Baas, Charlotte Buchanan, Aldo Camargo, Vera C. Keil, Zixuan Lin, Thomas Lindner, Lydiane Hirschler, Jian Hu, Beatriz E. Padrela, Mohammad Taghvaei, David L. Thomas, Sudipto Dolui, Jan Petr ”The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): ASL Pipeline inventory”. April 2023.
5. Camargo, Aldo, Wang, Ze. ”Hypo- and Hyper-perfusion in MCI and AD Identified by Different ASL MRI Sequences”. Journal of Brain Imaging and Behavior. March 2023. 6. Camargo, Aldo, Wang, Ze. ”Estimating Arterial Transit Time (ATT) from ASL MRI Acquired at a Single Post-Labeling-Delay Time”. Accepted for virtual oral presentation on May 2022 ISMRM
(London, UK).
7. Zhang, Lei, Danfeng, Xie, Yiran, Li, Camargo, Aldo, Donhui, Song, Wang, Ze. ”Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer’s Disease Using Transfer Learning of Deep Learning-based ASL Denoising”. Journal accepted for the Journal of Magnetic Resonance Imaging. October 2021.
8. Camargo, Aldo, Wang, Ze. ”Longitudinal Cerebral Blood Flow Changes in Normal Aging and the Alzheimer’s Disease Continuum Identified by Arterial Spin Labeling MRI”. Journal of Alzheimer’s Disease. June 2021.
9. Camargo, Aldo, He, Qiang, Palaniapp, Kannappan. (2013). ”Performance Evaluations for Super-Resolution Mosaicking on UAS Surveillance Videos”. International Journal of Advanced Robotic Systems.
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