Mag. María Alejandra Acuña Rojas

Programmed and tested Al-based software. Applied digital signal processing for audio and image applications. Documented software components. Performed system integration.

Implemented and integrated methods and algorithms for acoustic event recognition and machine learning applications on resource-constrained platforms. Developed further software-based tools to expand the existing tool chain for audio signal processing and acoustic event detection. Developed and maintained application-specific audio databases. Last project: Detection of motor failure through AI (Audio Event Detection)

Topics: Melody extraction, source separation, binary masking.

- Assistance to students in (MATLAB-based) sessions. - Topics: Theoretical principles of digital signals, Discrete Fourier Transform and Spectral Analysis, Adaptive Filters, Non-recursive Filters, Recursive Filters.

Evaluation of automatic melody extraction algorithms: YIN, version of MELODIA (salience-based), score-informed approach.

- Dynamic Simulation (DM) of geologic materials as MgSiO3 in perovskite and post-perovskite structures. - Publication: Pinilla, C., Acuña-Rojas, M., Seriani, N., Scandolo, S. An atomistic model of MgSiO3 perovskite and post-perovskite phases. Computational Materials Science 126 (2017) 351-359.

- Analyze optical properties of patterned Pt-based bulk metallic glasses (BMG) for low reflectance application - Creation of a 3D Model in CAD for a Pt-BMG sample with MATLAB.

- Research topic: “Dye-Sensitized Grätzel-type Solar Cells”. Poster at the 3 rd Physics Engineering Congress (Medellín, Colombia). - Publication: Perez, E., K. Montalvo, M. Acuña, T. Rada, F. Buchholz. Grätzel type-solar cells sensitized with some Colombian’s dyes. Rev. Acad. Colomb. Cienc. 37 (1):43-46, 2013.

- Support in error analysis of design patterns. - Evaluate the characterization for the design processes of automotive gyroscopes and accelerometers.

9-week full-time intensive coding bootcamp. Learned Data Science with Python; Data Analytics with SQL, BigQuery, Pandas, NumPy, and Matplotlib; Statistics with Scipy, Seaborn and Statsmodels; Machine Learning with Scikit-learn; Deep Learning with TensorFlow Keras. Worked on Data Products development with Google Cloud Platform (GCP) and MLFlow Collaborated in a team of 4 to deliver a project ("Pawparazzi") using AI.

Digital Signal Processing, Statistical Signal Processing, Information Theory, Audio Processing Analysis and Synthesis, Speech and Audio Signal Processing, Digital Communications, Mobile Communications, MIMO, Molecular Communications, Image and Video Compression.

Analog Circuits, Modern Physics of the Solid State, Electrical Machines I, Digital Circuits, Microprocessors, Microcontrollers, Electronics I, II and III, Signals and Systems, Communication Systems, Telematics.