Curriculum Vitae

Download my latest resume or view it below

Loading PDF...

Error loading PDF. Click here to view PDF directly

My Projects

A collection of engineering projects spanning autonomous systems, control theory, embedded programming, and digital design

General Purpose Adjustable Bipolar DC Voltage Supply

Overview

This power supply is designed for delivering variable current while maintaining high stability. It uses 3-terminal linear voltage regulators and half-wave rectifiers to provide reliable performance, making it ideal for a variety of electronic projects requiring bipolar power supplies.

Wiring Diagram

The diagram illustrates the wiring setup for the breadboard, featuring pin numbers and component values to facilitate easy assembly and testing. The transformer shown as T1 steps down the input AC voltage from 120V AC to 18V RMS (1000 mA capacity). The transformer provides two AC outputs which will be used to generate both positive and negative voltage rails. D1 and D2 are 1N4001 diodes, which act as rectifiers in a half-wave configuration. D1 handles the positive half-cycles, and D2 handles the negative half-cycles of the AC signal from the transformer. This setup ensures that the AC signal is converted into pulsating DC signals for further regulation. C1 and C2 are 1000 µF electrolytic capacitors they smooth the pulsating DC signals to produce a more stable DC voltage. They reduce the ripple voltage before it reaches the regulators. C3 and C4 are 1 µF capacitors, these capacitors are placed at the output of the LM317 and LM337 regulators to improve stability and reduce high-frequency noise. TI recommends that the input terminal be bypassed to ground with a bypass capacitor, optimum placement is closest to the input terminal of the device and the system GND. TI recommends a 0.1 µF capacitor for high frequency and 10 µF for high capacity thus 1 µF was chosen for a balance of both. LM317 is an adjustable positive voltage regulator, it regulates the positive voltage side of the circuit. It has three pins: IN, OUT, and ADJ (adjustment pin for controlling the output voltage). LM337 is the counterpart for the negative rail, an adjustable negative voltage regulator. For the positive voltage rail, R1 and R2 create a voltage divider. R1 is a fixed resistor, while R2 is a 5k potentiometer that adjusts the output voltage. R7, which is in parallel with R2, fine-tunes the adjustment range of R2. This simple addition allows finer control over the output voltage. For LM337 (negative voltage rail), R4 and R3 create a similar voltage divider with R5 for finer control. R6 sets the lower bound for the negative rail at about -3V. The final output of this power supply can be fine-tuned to provide adjustable voltages in the range of approximately +/- 3V to +/- 16V

Projects

Event Service Framework for an Autonomous Robot

This project involved developing an event service framework for an autonomous roach. The system, programmed in C, supports asynchronous event processing and a straightforward implementation of Hierarchical State Machines (HSMs). The objective of the autonomous bot was to use its onboard Light Dependent Resistor (LDR) sensors to find out dark areas, mimicking the behavior of a real cockroach. Once the roach finds darkness, it pauses its search algorithm until one of its side bump sensors is triggered, simulating a human disturbance. When disturbed, the robot performs a frantic evasive maneuver until it finds another dark spot to hide. The video demonstrates the bot hiding under chairs and scurrying away to find another desk or chair to conceal itself beneath.

Return to Projects

Rock Climbing Tracker

This project involved development and testing of an activity classification system designed to track rock climbing routes by measuring displacement throughout the route using a 9-DOF IMU sensor, the BNO055. The sensor's acceleration data was double-integrated to derive the displacement over time, with a state machine implemented for data collection in Calibration, Recording, and Waiting states. Calibration mode ensured accuracy by requiring all sensor types to be fully calibrated before data recording began. Data was recorded using CoolTerm and analyzed in MATLAB, where preprocessing included debouncing, bias removal, and applying both low-pass and high-pass filters to get human movement and eliminate the random spikes from the sensor. Velocity and displacement were calculated by integrating the acceleration data, and their visualizations provided insights into the movements captured by the sensor. Initial trials along each axis produced some measurable error rates, which increased during real-world climbing due to the complexities of motion and noise sensitivity. The best results from climbing trials demonstrated increased error with longer climbs, highlighting the difficulties in filtering noise and accurately capturing complex movements. While the device showed potential, the results emphasized the limitations of using cheap IMUs for precise activity tracking in dynamic environments.

Return to Projects

Project Title 4

Details of project 4 go here...

Return to Projects

Autonomous Ball-Collecting Robot

Under the guidance of Professor Gabriel Hugh Elkaim, our team, including Ana Elizabeth Villa and Rafael Delwart, developed an autonomous robot as part of the final lab in Mechatronics (ECE-118). Tasked with navigating a game field, the robot locates, traps, and deposits 25mm chrome balls either within itself or onto the opponent's field. Our design, "The Roller," utilized tape sensors and bumpers for navigation and employed an efficient ball collection mechanism to meet the challenge of collecting and depositing at least 30 balls within a two-minute round. This project showcased a blend of mechanical design, electrical system integration, and software strategy, culminating in a successful demonstration at the final competition.

Return to Projects

Relevant Coursework

Electrical Engineering

• ECE101/L – Intro to linear systems and signals, with lab work.
• ECE103/L – Analysis of electrical circuits and components, includes lab work.
• ECE118 – A project-based course on designing and integrating mechanical, electrical, and computer systems into functional automated systems using sensors and microcontrollers.
• ECE121 – Design and use of microcontroller-based systems and interfacing with analog and digital systems.
• ECE129A – Capstone Project I: First of a three-course sequence where students apply knowledge and skills to complete a major design project. Covers engineering design cycle, team practices, and project specification and planning.
• ECE129B – Capstone Project II: Continuation of the capstone project sequence focusing on implementation and development of the design project.
• ECE129C – Capstone Project III: Final course in the capstone sequence, emphasizing project completion, testing, and presentation.
• ECE141 – Feedback Control Systems: Analysis and design of continuous linear feedback control systems. Covers design by root locus, frequency response, and state space methods with practical applications.
• ECE167/L – Use of sensors for temperature, motion, sound, and light, focusing on digital integration.
• ECE171/L – Amplifiers, oscillators, and signal processing with hands-on lab work.
• ECE242 – Applied Feedback Control: Advanced control design course that explores state space control, discrete time control, and case studies. Students design and implement feedback controllers on real experiments like inverted pendulum systems.

Computer Science

• ECE13 – C programming with a focus on embedded systems, using the Microchip PIC32 microcontroller.
• CSE12 – Introduction to computer systems, digital logic, and assembly language programming.
• CSE16/L – Study of discrete structures including sets, graphs, and combinatorics applied to computer science.
• CSE20 – Mathematical foundations of computer science.
• CSE30 – Software development in Python with a focus on object-oriented design.
• CSE100/L – Advanced data structures and algorithm design, includes lab work.
• CSE101 – Study of advanced algorithms.
• CSE107 – Probability theory and statistics for computer science.

Mathematics

• MATH19A – Calculus for science, engineering, and mathematics.
• MATH19B – Continuation of calculus with applications in engineering.
• MATH21A – Linear algebra and matrix theory.
• MATH23A – Vector calculus and its applications.

Physics/Mechanics

• ECE9 – Fundamentals of statics and mechanics, focusing on the behavior of materials under various forces.
• ECE10 – Application of mathematical models to analyze the kinematics and dynamics of robot mechanisms.
• PHYS5A/L – Mechanics and wave motion, with lab component.
• PHYS5B/L – Study of electricity and magnetism, includes lab work.