Team Members

I have been always attracted by areas of knowledge that intersect more than one traditional discipline. My interests are centered on the development of digital signal processing, system modeling, and biomedical engineering tools that involve speech, audio, and acoustics.

My recent research efforts have revolved around developing quantitative models that describe nonlinear effects in human speech production, and applying these physiological descriptions for the development of communication and clinical technologies. I have a BS degree in Acoustical Engineering, and MS and PhD degrees in Electrical and Computer Engineering.

Juan Pablo is an Associate Researcher at the AC3E Research Center, where he works on signal processing, machine learning, and clinical voice applications. He earned his PhD in Electronic Engineering from the Universidad Técnica Federico Santa María in 2020 and previously completed his Bachelor’s and Master’s degrees at UCLA.

His experience includes a postdoctoral fellowship at Massachusetts General Hospital and work as a Scientist Researcher at Lanek SpA.

His research focuses on ambulatory voice monitoring, laryngeal modeling, and wearable technologies for vocal assessment.

Christian is a speech-language pathologist (SLP) and a PhD student in Science and Engineering for Health at the Universidad de Valparaíso (UV), Chile. He also is academic of the Departments of Voice and Speech at the Universidad de Valparaíso and Universidad Nacional Andrés Bello. He holds a background in the clinical assessment and treatment of voice disorders.

His research interests focus on voice and speech motor control, with particular emphasis on how auditory and somatosensory feedback shape vocal behavior in both healthy individuals and people with voice disorders. To understand these phenomena, he integrates electroencephalography (EEG), aerodynamic measurements, and acoustic analyses to characterize the neural and biomechanical bases of vocal adaptation and sensorimotor integration. Moreover, his interests include the application of engineering tools in clinical contexts, the use of voice parameters as biomarkers, and the implementation of signal processing techniques to better understand the physical and physiological mechanisms underlying human communication.

Emiro is a Postdoctoral Researcher at the Advanced Center for Electrical and Electronic Engineering (AC3E) at Universidad Técnica Federico Santa María (UTFSM), Chile. He received his Doctorate in Electrical Engineering from UTFSM, where his dissertation focused on integrating physiological modeling and machine learning to estimate vocal function parameters from neck-surface acceleration signals. Emiro’s expertise lies in biomedical signal and image processing, voice production modeling, and machine learning for physiological inference.

His research combines data-driven and model-based approaches to understand and quantify the biomechanical mechanisms of phonation. He has also contributed to the processing and quantitative analysis of high-speed videoendoscopy (HSV) for assessing glottal dynamics and developing objective measures of vocal fold behavior.

Currently, his postdoctoral work focuses on advancing domain adaptation of subject-specific modeling for the ambulatory assessment of laryngeal biomechanical components. Beyond research, Emiro is passionate about science communication and teaching, fostering interdisciplinary collaboration between biomedical engineering, clinical voice science, and digital health technologies for human-centered applications.

Jesús is a Postdoctoral Researcher at the Advanced Center for Electrical and Electronic Engineering (AC3E) at Universidad Técnica Federico Santa María (UTFSM), Chile. He earned his Bachelor of Science in Physics from Universidad Nacional de Colombia and his Ph.D. in Electronic Engineering from UTFSM.

His research lies at the intersection of physics, biomedical engineering, and machine learning, focusing on the development of computational models of voice production to understand the biomechanical and neurophysiological mechanisms underlying vocal behavior and disorders. He has specialized in lumped-element models of the vocal folds, which he integrates with clinical and ambulatory data to infer physiological parameters such as muscle activation and subglottal pressure. Beyond voice modeling, his interests include the propagation of waves in biological media and the modeling of complex physiological processes using data-driven and physics-based approaches. 

Cristobal was born in Viña del Mar, Chile, in 1993. He earned his degree in Mechanical Engineering from the Pontificia Universidad Católica de Valparaíso (PUCV) in 2019. In 2020, he began a joint Ph.D. program between the Universidad Técnica Federico Santa María (UTFSM) in Chile and the Université Bourgogne-Franche-Comté (UBFC) in France. He successfully completed this dual-degree program in December 2024, obtaining Ph.D. degrees in Electronic Engineering and Automatic Control, respectively.

He is currently a Postdoctoral Researcher at the Advanced Center for Electrical and Electronic Engineering (AC3E) in Chile, where he is working on the modeling of vocal fold dynamics, including contact interactions and tissue damage associated with swelling development. Since 2025, he has been a member of the IFAC Technical Committee on Distributed Parameter Systems (TC 2.6) and the IEEE Control Systems Society Technical Committee on Distributed Parameter Systems (DPS). His research interests include modeling, discretization, and control of multiphysics systems within the port-Hamiltonian framework, with a particular emphasis on energy-based and structure-preserving methods.

Josué was born in El Salvador in 1989. He completed his undergraduate studies in Biomedical Engineering at Universidad Don Bosco in 2013 and later obtained a master’s degree in engineering sciences with a specialization in Biomedical Engineering from Universidad de Valparaíso in 2017.

Since 2021, he has been pursuing a Ph.D. in Electronic Engineering at Universidad Técnica Federico Santa María (UTFSM), Chile. His doctoral research focuses on biomedical signal processing, particularly the analysis of laryngeal electromyography and its relation to voice production. He has also worked on the design of biomedical interfaces and the development of myoelectric prostheses, combining tools such as Arduino, MATLAB, and Python. 

Nicolás is a PhD student in Electronic Engineering at Universidad Técnica Federico Santa María (UTFSM) in Valparaíso, Chile. He holds a BS in Sound Engineering from Universidad de Chile and an MS in Acoustics and Vibrations from Universidad Austral de Chile.

His expertise spans electroacoustics, acoustic physics, and digital signal processing. His current research focuses on vocal motor control, particularly exploring the roles of somatosensory and auditory feedback in the context of vocal hyperfunction. Additionally, he serves as Lab Manager of the Health Technology Laboratory at the Advanced Center for Electrical and Electronic Engineering at UTFSM.

Rocío is a Master’s student in Electronic Engineering at Universidad Técnica Federico Santa María (UTFSM) in Valparaíso, Chile. She earned her Bachelor’s degree in Sound Engineering from Universidad de Chile in 2020.

Her current research focuses on vocal motor control, exploring how cognitive load and neurological conditions such as Parkinson’s disease influence the biomechanical and acoustic aspects of voice production through model-based approaches.

Her broader interests include the integration of control theory, voice science, and signal processing for the analysis of speech motor mechanisms.

Alondra is an MSc student in Electronic Engineering at Universidad Técnica Federico Santa María (UTFSM) in Valparaíso, Chile. She is also a research assistant at the Advanced Center for Electrical and Electronic Engineering (AC3E).

Her research focuses on the automatic segmentation of the glottis in high-speed laryngeal videoendoscopy using deep learning-based computer vision techniques. This work aims to enhance the robustness and reliability of glottal analysis under varying clinical conditions and imaging setups.

Her broader research interests include computer vision, image and video processing, and deep learning for biomedical applications.

Matías is a Master’s student in Electronic Engineering at Universidad Técnica Federico Santa María (UTFSM) in Valparaíso, Chile.

His research focuses on leveraging Deep Neural Networks to enhance existing High-Speed Videoendoscopy (HSV) processing and analysis methods, along with relevant feature analysis and selection.

His broader research interests include image and video processing, deep learning, and computer vision applications