Julio Ramirez Email & Phone Number

Chicago, IL, US

Co-leading a team of undergraduate and graduate students to compete in the 2024-25 NASA Lunabotics Challenge

• Co-led a team of eight undergraduate students to ideate, propose, and develop a stationary object recognition system using off-the-shelf hardware to assist search and rescue operations for the Artemis program
• Led hardware and software integration for an object detection model using the YOLO framework onboard an NVIDIA Jetson Nano using Linux OS and running test scripts with Python
• One of three national finalist teams selected for the NASA Micro-g NExT SPOTR Challenge to test our system in the summer of 2024 at the Neutral Buoyancy Lab in Houston, Texas

• Assisted in the selection of hardware components for power distribution of an autonomous watercraft to deliver emergency supplies to crewmembers upon returning to Earth from an Artemis mission
• Utilized KiCad to develop a preliminary schematic for the expected design using select electronic components and performed circuit analysis and design tests using LTspice

New York, NY, US

• Tutor students for ENGI 1006 - Intro to Computing in Python and COMS W1004 - Intro to CS and Programming in Java at the Berick Center for Student Advising
• Work with 2-4 students on a weekly basis to improve their understanding of course material with a focus on pattern recognition, critical thinking, and problem-solving through curated hands-on exercises
• Assist students in reviewing for exams, covering topics ranging from data types to introductory machine learning and data visualization

Dearborn, Michigan, US

• Vehicle Hardware Engineering - Body Electrical and Electronics Hardware
• Supported vehicle battery SoC testing, using the measured battery characteristics combined with datasheet specifications to develop a Simulink model to verify the strategy for an electronic module
• Developed a comprehensive strategy Stateflow model in Simulink to support the software development for a prototype PCB, using an Arduino to interface and verify the operation of the model
• Implemented the Stateflow model in a MATLAB App to allow for easier feature testing and provide a simple interface for future hardware testing. Presented a live technical demo to senior management, including the Chief.

Torrance, CA, US

• Performed hardware research in AR/VR environments, exploring opportunities to engage multiple parties while improving customer use case experiences
• Conducted IoT research targeting new connectivity standards for home and automotive solutions, created a virtual device using Python and Docker in a Linux environment, and presented a system implementation across.
• Initiated customer experience research for automotive VR solutions, exploring risks involving motion sickness

• Developed a leads sheet with nine potential transportation consulting role opportunities with metropolitan planning organizations and departments located in six states, including Illinois, Missouri, and New York
• Revised FHWA report topics from a global transportation scan to improve clarity and structure and researched new infrastructure projects to highlight the impacts of key technologies and innovations
• Updated the Cempel ITC website periodically using WordPress and HTML

Armonk, New York, NY, US

• Engaged in eight weekly lectures focused on professional and personal skills development, concurrent with completing online modules through the IBM SkillsBuild learning platform
• Explored areas of the hardware development cycle in IBM Systems, including topics such as Processor Design, Hardware and Firmware Development, and Systems Product Engineering
• Completed all necessary program requirements to earn the IBM Accelerate Hardware Developer badge

New York, NY, US

• Assisted a member of the Pasupathy Research Group in the construction of an annealing apparatus for scanning tunneling microscopy (STM) experiments
• Created 2-D material samples using silicon chips for graphene extraction

Chicago, IL, US

• Co-led the design of an evaluation study to examine the impact of using a Juypter Notebook plugin to help machine learning developers better understand the data they use for training and testing their models
• Set up a smart home environment with 10 devices and collected network packet capture data using Wireshark to test firewall rules for improving security and preserving the functionality of smart devices.

Chicago, IL, US

• Conducted qualitative coding of 502 survey respondents for a study to examine how people perceive the fairness of machine learning models, contextualized by their use in the criminal justice system
• Co-authored a research paper that was accepted to the ACM FAT* 2020 Conference

Bachelor Of Science - Bs, Electrical Engineering, Minor In Computer Science

High School Diploma