Ph.D. in Smart Systems, Universidad de las Américas Puebla: August 2018 - May 2023
Thesis Project: “Automatic detection of Parkinson's disease using voice analysis and structural Magnetic Resonance Imaging voxel-based analysis”.
Bachelor of Science in Mechatronics Engineering, Universidad Iberoamericana de Puebla. August 2013 - June 2018
Additional Courses:
Artificial Intelligence in Medicine, Institute of Medical Science, University of Toronto.
Biomedical Signal and Image Processing, IEEE SPS-University of Chile.
Fundamental Neuroscience for Neuroimaging, Johns Hopkins University/Coursera.
More C# Programming and Unity, University of Colorado/Coursera.
Introduction to C# Programming and Unity, University of Colorado/Coursera.
Mathematics for Machine Learning: Multivariate calculus, Imperial College London/Coursera.
Mathematics for Machine Learning: Linear Algebra, Imperial College London/Coursera.
Machine learning, Stanford Online/Coursera.
Programando con Java para aplicaciones Android, Universidad Nacional Autónoma de México/Coursera.
Fundamentos de Android, Universidad Nacional Autónoma de México/Coursera.
Design of mechanical elements by software, Universidad Iberoamericana/CYDY.
Software Engineer AI, at Claritas Healthech
International visiting Graduate Student at the Institute of Medical Science at the University of Toronto:
Researcher in signal processing and fMRI analysis with Machine Learning and Causal Forest in collaboration with the Department of Statistical Science of the University of Toronto, and medical professionals from St Michael’s Hospital, Unity Health, Toronto.
Professor Tyrrell Lab: https://www.tyrrell4innovation.ca/people/
Innovation Campus - Volkswagen Puebla:
Researcher in the project "Development of hat box mold for hatchback cars of the Volkswagen company, for a prototype with recycled materials"
Co-founder of the startup Autenilum, head of research and product development:
Development of the product "Solaris", Research in "Li-Fi" technology using solar cells.
Beca Tesis del Consejo de Ciencia y Tecnología del estado de Puebla.
Magna Cum Laude Recognition for outstanding academic performance during Smart Systems Ph.D. studies, Universidad de las Américas Puebla.
First place in the “3rd Doctoral Colloquium: Science Technology and Culture a Global Vision” video contest at Universidad de las Americas Puebla.
First place in the “IEEE Summer SPS School on Biomedical Signal and Image Processing” 3-minute video contest, at the University of Chile.
“National Scholarship”, Consejo Nacional de Ciencia y Tecnología.
“Academic Research Scholarship UDLAP”, Universidad de las Américas Puebla.
“Outstanding performance in the general exam for bachelor's degrees in science” CENEVAL.
“Jesuit Merit” Scholarship, Universidad Iberoamericana Puebla.
G. Solana-Lavalle, J. C. Galán-Hernández, R. Rosas-Romero, "Automatic Parkinson disease detection at early stages as pre-diagnosis tool by using classifiers and a small set of vocal features", Biocybernetics and Biomedical Engineering, vol. 40, no 1, pp. 505-516 , 2020 , https://doi.org/10.1016/j.bbe.2020.01.003
G. Solana-Lavalle, R. Rosas-Romero, "Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinson's disease", Computer Methods and Programs in Biomedicine, 2020, https://doi.org/10.1016/j.cmpb.2020.105793
G. Solana-Lavalle, R. Rosas-Romero, "Analysis of Voice and Magnetic Resonance Images to Assist Diagnosis of Parkinson’s Disease with Machine Learning", Technology, Science and Culture: A Global Vision, Volume III, 121 (book chapter)
Metri-Ojeda, J., Solana-Lavalle, G., Rosas-Romero, R. et al. Rapid screening of mayonnaise quality using computer vision and machine learning. Food Measure (2023). https://doi.org/10.1007/s11694-023-01814-x
Solana-Lavalle, G.; Cusimano, M.D.; Steeves, T.; Rosas-Romero, R.; Tyrrell, P.N. Causal Forest Machine Learning Analysis of Parkinson’s Disease in Resting-State Functional Magnetic Resonance Imaging. Tomography 2024, 10, 894-911. https://doi.org/10.3390/tomography10060068
Guevara, E., Solana-Lavalle, G., & Rosas-Romero, R. (2024). Integrating fNIRS and machine learning: shedding light on Parkinson's disease detection. EXCLI journal, 23, 763–771. https://doi.org/10.17179/excli2024-7151
Solana-Lavalle, G., & Rosas-Romero, R, (2022). “Adaptive multiple-time-step forecast of long-term trends with decomposition and ensemble applied to Covid-19 and stock prices”.
Solana-Lavalle,G. "Procesamiento de señales e Inteligencia Artificial para el diagnóstico de la enfermedad de Parkinson, Biomethon 2.0"
EEE Access, “Parkinson’s-Specific Featureset Under Read Speech Experiment” 06-2022
Scientific Reports, “Classification of Parkinson’s Disease and Its Stages Using Machine Learning” 05-2022
Decomposition and ensemble architectures for Long Term Forecast of time series and classification.
Detection of Parkinson's disease with fNIRS.
Longitudinal analysis of Magnetic Resonance Imaging of Parkinson's disease patients.
Microcalcification detection through image processing.
Montecarlo Simulation of photon interaction with tumoral tissue.
Medical Images
Numerai Tournament: https://numer.ai/~gsc
Computer Vision
Microcontrollers
Music Composition
Classic Science fiction novels
https://github.com/GabrielSolana29