Liz Aneth Jaramillo Henao - Ingeniera Electrónica

Liz Aneth
Jaramillo                                             C.C.1152684652
Henao                                   Calle 53 No.74 - 125 Apt 411
                                                  Medellín, Antioquia
                                                H (+57)316-413-2164
Ingeniera                                    B lianjahe27@gmail.com
Electrónica                      Matrícula profesional: CL206-141474

               Perfil Profesional
Ingeniera Electrónica de la Universidad Nacional de Colombia. Estoy muy interesada en
los campos de investigación de Robótica del Desarrollo Cognitivo, Neurociencia, Sistemas
Inteligentes e Inteligencia Artificial. Experiencia trabajando en Machine Learning,
Computer Vision y Reinforcement Learning. Conocimientos en diferentes lenguajes de
programación, diseño e implementación de sistemas electrónicos.

               Experiencia Laboral
 Mayo 2021 - Tutor Python, Misión Tic 2022, Universidad Sergio Arboleda, Colombia.
 Agosto 2021
               { Apoyar en el proceso de aprendizaje de los estudiantes en el curso de
                 Fundamentos de Python del programa Misión Tic 2022 ofrecido por el
                 Ministerio de Tecnologías de la Información y las Comunicaciones de
                 Colombia.

  Diciembre Machine Learning Engineer and Python Backend, Emobotics,
 2020 - Julio Logroño, España.
        2021
               { Desarrollar modelos de Deep Learning, NLP, Computer Vision, y Rein-
                 forcement Learning, en lenguaje de programción python, aplicados a
                 TTS, reconocimiento de emociones y generación de diálogo.
               { Desplegar y mantener modelos de IA en la nube.
               { Liderar el equipo de Backend y desarrollar Backend en Python.

Febrero 2020 Firmware and Machine Learning Engineer, Lantia SAS, Medellín,
- Noviembre Antioquia.
        2020
             { Participar en un proyecto tecnológico de investigación para la educación
               desarrollando modelos de machine learning y firmware para sistemas
               embebidos.
             { Desarrollo de Modelos Ocultos de Markov para series de tiempo en
               Python.
             { Desarrollo de firmware para capturar datos de sensores electromagnéti-
               cos mediante dispositivos IoT en lenguajes como Python y C++.

Octubre 2019 Freelance Software Engineer, Medellín, Antioquia, Colombia.
   - Febrero
        2020
             { Escribir un algoritmo de visión por computador en Python con OpenCV
               para medir distancias entre objetos.
             { Escribir algoritmos para resolver ecuaciones diferenciales con MATLAB.
             { Desarrollar proyectos programando microcontroladores PIC en lenguaje
               C.

             Educación

             Cursos
       2020 Fundamentals of Reinforcement Learning, University of Alberta,
            Coursera.
       2020 Deep Learning Specialization, deeplearning.ai, Coursera.

             Diplomados
       2019 Diplomado de Análisis de Datos y Machine Learing en Python.
            Curso 1, Universidad de Antioquia, Medellín, Antioquia.

             Pregrado
       2019 Ingeniera Electrónica, Universidad Nacional de Colombia, Manizales,
            Caldas.
             GPA:4.2/5

Tesis de Grado.
     "Evaluating the Influence of Crawling Experience on Depth Per-
     ception from Disparities Through a Computational Model", Hu-
     mans general intelligence allow us to face the dynamic nature of the real
     world. What are its underlying mechanisms and how does they emerge,
     have been the subject studied by cognitive science, a multidisciplinary field
     that have inspired the creation of artificial models of cognition, aiming to
     replicate human intelligence in artificial agents. Cognitive Developmental
     Robotics (CDR) has been proposed as a new paradigm in cognitive science
     based on both, embodiment through a robotic synthetic approach and
     key concepts from developmental psychology. It aims to provide a new
     understanding about ourselves and a new design theory for humanoid
     robots. Several studies conducted on infants, by means of behavioral ex-
     periments, have suggested a relation between motor and visual skills. For
     instance, perception of distance has been argued to show developmental
     improvements following the acquisition of locomotion, as visual attention
     is drawn to previously undetected or ignored depth specifying information.
     This study aims to evaluate such hypothesis through a computational
     model that estimate distances from binocular disparities. In a first stage,
     an image database is assembled obtaining binocular images from scenes
     that contains salient objects at different distances, in a random arrange-
     ment. Then, image preprocessing algorithms are implemented to prepare
     the images for a classification task. Finally, a Binocular Neural Network
     (BNN) algorithm is implemented to classify the input images in different
     distances by computing binocular disparities. Highlighting key aspects of
     locomotion experience, the BNN algorithm is trained from two different
     approaches: one standing for non-locomotor infants and one standing for
     locomotor infants. This training processes are conducted in the tasks of
     classifying two distances, three distances, and four distances. Validation
     and test error percentages show an improvement on the distance estima-
     tion tasks for the BNN trained with locomotor experience. Furthermore,
     sensitivity and specificity analysis prove its better performance. The re-
     sults add to previous evidence which supports that locomotion in infants
     is an important step in cognitive development..

     Secundaria
2007 Bachiller Académico, I.E. José María Campo Serrano, Aguachica,
     Cesar.

Idiomas
     Spanish, Nativo.
     English, TOEFL iBT, B2, 2019.
     Japanese, Limitado.
     Korean, Limitado.

     Lenguajes de Programación
     Assembler                       Python
     C, C++                          MATLAB

     Frameworks
     TensorFlow                      Pandas
     Keras                           Django
     PyTorch

     Conocimientos Específicos
     Machine Learning                Docker
     Deep Learning                   Linux
     Natural Language Processing     Git
     Computer Vision                 PostgreSQL

     Tecnología de Nube
     Google Cloud Platform
     Kubernetes

     Publicaciones
2019 "A Computational Model for Distance Perception Based on Vi-
     sual Attention Redeployment in Locomotor Infants", Communi-
     cations in Computer and Information Sciences (CCIS).
2019 "Influence of Locomotion Experience for Distance Estimation in
     Infants: A computational Model", 2nd IEEE Colombian Conference
     on Applications in Computational Intelligence, ColCACI 2019.

Referencias
{ Jaime Enrique Arango Ph.D
  Profesor Asociado DIEEyC
  Universidad Nacional de Colombia, Sede Manizales
  (+57)311-735-5022
  jearangoca@unal.edu.co

{ Ing. Marlon Estiben Bedoya
  Ingeniero de Desarrollo INTERTELCO
  (+57)319-696-0171
  marlon.bedoya@gmail.com