Computer Scientist and Software Engineering enthusiast. I have more than 7 years of coding experience, 1.5 years of industry experience, and 2 years of research experience. I enjoy coding and facing new challenges every day. I'm also open to changes and I find it easy and fun to integrate into new projects. I'm not particularly attached to any technology or language as I enjoy learning new things but I'm more into mobile and web development.
Over my industry experience, I had worked as a Software Engineer Intern, Software Engineer, and DevOps. I worked with technologies such as MEAN stack from which I gained experience in JavaScript and MongoDB. I also worked with Amazon Web Services and Jenkins from which I learned about automatic release processes.
As part of my research at Texas A&M, I have developed an iOS app using Objective-c for HR estimation for which I applied DSP techniques and submitted the module to Apple's open-source ResearchKit library. I also developed an Android wearable app for sensor data collection and smart data annotation, then, used Machine Learning techniques on the collected data for activity recognition, in particular posture and eating moments recognition.
As a research assistant, I have developed Android applications and applied ML at the Systems and Technology for Medicine and IoT (STMI) Lab , mainly using Java, MATLAB, and Python.
I joined the company as a software engineer developing features in the innovation department using MEAN stack. However, I worked mostly on the back-end side and database management. When the time for deploying the new app arrived, I was requested to manage the process and then I became the DevOps of the team, however, I kept developing features. The company I was working for also worked with companies in the US. Three months before I left the company to pursue my Master's degree I was asked to join a team from Agralogics (CA, USA) to work remotely as a DevOps as their current DevOps had left the company.
While working at this company, I was part of the IT team that maintained the software that was used for their daily production tasks.
I designed an Objective-C module that captures heart rate information using an iOS device's camera, which I submitted to Apple's open-source ResearchKit library.
View ContributionCreated an Android app and a back-end service using Flask, a Python-based framework. The app determined email’s stressfulness through Google's sentiment analysis library. The app adapted its UI dynamically to show users which emails they should avoid based on current stress levels measured via a wearable sensor which measured their breathing rate.
View DemoBuilt relaxation app for Android to teach users slow, deep breathing by controlling a robot with breath patterns measured with a Bluetooth wearable sensor.
View DemoDeveloped a video testimonial recording and sharing web app using HTML5, Bootstrap, and Python (Flask).
View ProjectCreated a dynamic regression model in MATLAB based on accelerometer information to predict heart rate when exercising. Aimed to reduce energy consumption in smartwatches by alternating between measuring heart rate with dedicated sensor or prediction model.