Oscar Resendiz Artificial Intelligence Engineer
About Me
Senior at Texas State University. Majoring in Electrical and Computer Engineering. Currently deep diving into my passion for Artificial Intelligence. Always on the lookout for Research and industry opportunities in the realm of Software design and development.
Interests Include: Big Data, Machine Learning, General AI and Engineering design.
When I’m not studying you will probably find me working on a few of my personal projects, facilitating Club meetings as President of SHPE – TXST, Leading my Senior Design Team, or simply catching up on my reading backlog.
( currently reading; Human Compatible: Artificial Intelligence and the problem of control – Stuart Russel )
Experience Sub Heading
Fall/Spring 2022/23 – Autonomous Rover – Smart Firefighting
Project Manager – Lead Developer
- Senior Capstone Project at Texas State University, Leading a team of Computer Engineers with the tasks of integrating various I/O devices (Lidar, Depth Camera) into a ROS2 powered system. The Rover also will be powered by two AI Models (CNN, LSTM) that provide Human Classification in smoke and Scream Detection.
- Working towards developing an Autonomous Algorithm for the Rover.
Summer 2022 – MIT-IBM Watson AI Lab (Cambridge MA)
AI Software Engineer Intern
- Working alongside the Advanced Prototyping Team to scale up many of the Lab produced research for Industry specific frameworks and applications
Fall 2021 – TC Energy (Houston TX)
Business Process Analyst/Application Developer – Contractor
- Working Remotely for IS department at TC Energy
- Developed the foundational data infrastructure for a data sensitive project that will provide real time data updates on various Compressor/Meter stations for Infield Techs. (PI AF SYSTEMS)
- Full Stack Developed an application that will provide the Infield Technicians with a UI to access real time Compressor/Meter Stations Data. (JavaScript, Leaflet.js, React, AWS S3)
Summer 2021 – TC Energy (Houston TX)
Data Analyst and Application Developer – Intern
- Internship will focus on Application Development using Microsoft Power Apps.
- Data Analysis will be facilitated using Microsoft BI.
Summer 2020 – NASA
L’Space Alumni (NASA Proposal Writing and Evaluation Experience)
- Competed for a $10,000 grant with a a virtual team to develop a state of the art technology to aid in future NASA or Private Space Missions.
- Gained Inside Knowledge on successfully writing Proposals and what the scoring process is for the NASA review committee.
Spring 2020 – NCAS (NASA Community College Aerospace Scholars)
- Completed online course and was invited to NASA’S Langley Research space center for onsite competition.
Projects Sub Heading
AIGIS
Artificial Intelligence Assistant
AIGIS is my passion project, I continue to add functions to the Chatbot as I continue my self study of Artificial Intelligence.
As of Spring 2022, AIGIS is now powered through GPT – 3 API Calls.
Uses Amazon Polly for Voice Synthesis.
AIGIS is programed on Python and uses speech recognition libraries to communicate with the user.
Functions include:
- Speech Translation
- Sending Tweets
- Creating Due Dates for my personal calendar
- Idle Chatting
Most of my Software projects are added as functions to AIGIS’ main source code.
E-bike Conversion
Converted an Old Mountain Bike to a fully electric 30MPH capable electric bicycle.
- 48 V Battery
- 1000 W Controller
- Rear Hub Motor
- Odometer
City Search Tool
Data Science Project
Using Web scraping libraries (Selenium, BeautifulSoup) and Kaggle Databases. I mined several amounts of data to create a master file to be used for an algorithmic approach to finding the optimal city for the user, Given various constraints such as, Crime Rate, Rent cost, Traffic Rate, Happiness Factors, and LGBT friendliness. The data was cleaned and formatted using Numpy and Pandas in Python.
The data was normalized and attached a weight factor depending on the user inputs. The project was then added to AIGIS’ Main source code and the program is ran through its speech synthesis.
The user enters or says their desired preference for each factor mentioned above, The program then outputs a data frame containing 5 of the most relevant cities for the user.