edudiaz92

Ramon Eduardo Diaz Ramos

I decided to follow my career goals with every decision I make, and I will proceed to enlightened it.

After spending five years as a Mechatronic undergraduate, I have developed and concrete my values and integrity as a person. Social Responsibility is part of my core values, innovation, collaborative work, leadership, and continuous learning have shaped my life.

In the last year of my undergraduate program, I began to work as an intern in Flextronics and re-discovered my passion to gather data and create machines focusing on a necessity. In my first semester as an intern, I developed a machine capable of reducing the workload of the operator and avoiding defects in plastic parts for an automotive client. I designed, manufactured, assembled, and programmed the machine capable of automating the process. In my second year, they put me in charge of a group of interns, which objective was to reduce the workload of 10 operators by half, this was successfully achieved.

My wife and I encourage ourselves to always seek for our personal and professional goals. I worked as a professor for students of elementary and middle school at my University. Teaching the basics of programming, mechanics, and electronic to middle school students thought me how to explain the complex terms of sciences and engineering in a simple manner. I participate in the logistics of a summer camp for kids and teenagers with intellectual and physical disabilities. Pursuing my objective of helping others, I became a Robotics Coach in FIRST Robotic competitions for a public school in my community.

With my background in Mechatronics and my technical experience, I wanted to develop my leadership and communication skills, so I looked for a job that could help me to achieve them. I worked at Bocar Group, an automotive supplier, where I develop optimizations of time and cost used in the production of metal parts. I created a predictive system to avoid failures in injection molding machines. A year later, I was offered to work at Nissan Mexicana, where I worked as a Buyer for raw materials products, responsible for purchasing all the paint and sealants that are applied in Nissan Mexico facilities, including cars for exportation. I improve my negotiation skills and work collaboratively with engineering departments to reduce raw material consumption and manufacturing cost.

Afterward, I started my master's in Computer Science (with a Machine Learning concentration) with a 100% scholarship from Tecnologico de Monterrey. During this year of research and studies, I have also obtained two certificates from MIT: one of them in Machine Learning and one for Digital Transformation, both of them funded by Santander’s scholarship awards. Also, I have gained two accepted conference papers on artificial intelligence and machine learning and currently working on three others. I had the opportunity to participate in HackatonMTY 2020, where we received a special mention for the data analytics project our team developed for predicting car crashes in my city.

I have the opportunity to demonstrate my presentation skills in two different international conferences (CSASE 2020, MCCSIS 2020), where my collaborators and I utilize machine learning algorithms to build predictive models and expose the discoveries in our work. The papers can be found on my ResearchGate account and are available upon request. I am currently working on developing a resilience to stress index, which is part of the variables to predict depression. I have another research on the disease SARS-COV-2 analysis and predictive model for Mexico currently reviewing with Cognitive Computation Journal. I was admitted to the master’s in computer science program with no formal background in the area, but I have demonstrated passion for the subject, and I will continue to increase my knowledge in the area.
I am enthusiastic about increasing my knowledge in computer science, developing research with people that share my passion for the subject, and helping others.

Projects

Stream.Bit

A full stack ML pipeline feeding an analytical dashboard that gives companies insight regarding the negative sentiment posted on tweets.Docker, GitHub, AWS, Twitter API, Apache Kafka, Python3.8, AWS SageMaker, ksqlDB, AWS Quicksight

Skills

Python
Machine Learning
Data Science
Natural Language Processing
Signal Processing