Leonardo Andrés Gongora Velandia
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Leonardo Andrés Gongora Velandia

Leonardo Andrés Gongora Velandia  new_releases

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Software quality engineer - MSc in Biomedical Engineering - Focused on Information Bioengineering
Milan, Italy

Contact Leonardo regarding: 
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Full-time jobs
Starting at USD2.5K/month
Flexible work
Starting at USD20/hour
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Résumé


Jobs verified_user 0% verified
  • Flex
    Software Quality Engineer
    Flex
    Sep 2022 - Feb 2024 (1 year 6 months)
    Conducted thorough exploratory analysis, including ad-hoc tests, to uncover potential bugs and errors impacting the functionality of the device, considering user experience, operational aspects, and expected behavior. Additionally, I meticulously verified BLE components and scrutinized the device's interaction with a smartphone app. Moreover, I led the development and execution of Verification and Validation (V&V) plans, overseeing the update, verification, and implementation of testing strategies for Automated Test Equipment (ATE) stations across multiple factories. This involved ensuring the traceability of requirements, updating protocols, accommodating changes in hardware and software components, and conducting various tests such as uni
  • Flex
    SW Quality engineer - Internship
    Flex
    Dec 2021 - Aug 2022 (9 months)
    I took charge of overseeing project verification processes, managing dry-run tests, and crafting detailed bug reports to ensure swift resolution. Alongside this, I conducted meticulous reviews of written tests, refining clarity, context, and coherence within protocols. My duties extended to implementing diverse verification strategies utilizing an array of laboratory instruments. Moreover, I actively contributed to Quality Assurance tasks, directing the verification strategies for new software features in a medical device interface, refining testing strategies, and automating manual tests. This collaboration with clients resulted in significant time savings, and strategic measures were introduced to optimize test definition and execution pr
  • Universidad Militar Nueva Granada
    Research assistant
    Universidad Militar Nueva Granada
    Feb 2015 - Nov 2017 (2 years 10 months)
    As a research assistant, I was part of the Virtual Applications Research Group of the mechatronics engineering program at Universidad Militar Nueva Granada (Nueva Granada Military University) where I developed different research projects mainly focused on advanced signal processing, data analysis, machine learning, and the development of silent speech interfaces (SSI). In my role, I spearheaded the signal analysis of Non-Audible Murmur (NAM) signals, managing the entire feature extraction process from design to testing, including sensor signal conditioning for NAM time series acquisition. I developed firmware for signal acquisition, processing, and classification of speech signals using an STMicroelectronics development board, employing Me
Education verified_user 0% verified
  • Politecnico Di Milano
    Master of Science - MSc, Information bioengineering
    Politecnico Di Milano
    Jan 2018 - Jun 2021 (3 years 6 months)
    Skills: EEG Signal processing · Algoritmos · Desarrollo de algoritmos · Matemáticas · Conceptos de estadística
  • Universidad  Piloto de Colombia
    Bachelor of Engineering - BE, Mechatronics engineering
    Universidad Piloto de Colombia
    Jan 2010 - Jan 2015 (5 years 1 month)
    Skills: EEG Signal processing · Algoritmos · Desarrollo de algoritmos · Matemáticas · Resolución creativa de problemas · Diseño de placas de circuito impreso (PCB) · Conceptos de estadística
Publications verified_user 0% verified
  • S
    A Novel Approach for Segment-Length Selection Based on Stationarity to Perform Effective Connectivity Analysis Applied t
    Sensors
    Jun 2022
    Connectivity among different areas within the brain is a topic that has been notably studied in the last decade. In particular, EEG-derived measures of effective connectivity examine the directionalities and the exerted influences raised from the interactions among neural sources that are masked out on EEG signals. This is usually performed by fitting multivariate autoregressive models that rely on the stationarity that is assumed to be maintained over shorter bits of the signals. However, despite being a central condition, the selection process of a segment length that guarantees stationary conditions has not been systematically addressed within the effective connectivity framework, and thus, plenty of works consider different window sizes
  • I
    Comparative Analysis of the Mel Frequency Cepstral Coefficients for Voiced and Silent Speech
    International Journal on Communications Antenna and Propagation IRECAP
    Dec 2016
  • I
    Pre-emphasis, windowing and spectral estimation of silent speech signals using embedded systems
    International Journal of Multimedia and Ubiquitous Engineering IJMUE
    Oct 2016
  • I
    Embedded Mel Frequency Cepstral Coefficient Feature Extraction System for Speech Processing
    International Review on Computers and Software IRECOS
    Mar 2016