Chris Peng

Engineering Science (Year One)

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Opus CII:
Engineering Design Portfolio

Accompaniment: View Musical Program

and no, I did not play this

Effective engineering design is about rescoping an overall goal towards the highest-value objectives and validating the remainder through empirical data. My practice is grounded in the three core values: Efficiency, Safety, and Accountability. These principles directly dictate the selection of Concepts, Tools, Models, and Frameworks (CTMFs) utilized throughout my work.

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The Position

The Iterative Investigator

The Engineer

My name is Chris. I am a first-year undergraduate in the Engineering Science Program at the University of Toronto. My career aspirations are focused on systems architecture, real-time computer vision, and high-performance hardware integration. My approach involves utilizing mathematical frameworks with practical, empirical execution.

View Technical Profile
Act I: Foundational Frameworks Fall 2025
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Rigid Pipe Faucet Attachment
Movement I. • Sep 2025 to Dec 2025

Rigid Pipe Faucet Attachment (Praxis I)

Designed a fluid redirection system solving severe spatial constraints in dormitory sinks through iterative proxy testing.

  • Frame: NGO Framework
  • Diverge: Morphological Charts
  • Converge: Proxy Testing for Validation
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CIV102 Bridge Project
Movement II. • Nov 2025 to Dec 2025

High-Load Truss Bridge (CIV102)

Optimized a matboard structure utilizing custom Python simulations to achieve a 1250 N dynamic load capacity.

  • Frame: Requirements Framework
  • Represent: Detailed Design (FBDs)
  • Process: Spiral Model of Design
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Act II: Systems and Intelligence Winter 2026
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Autonomous Game Bot
Movement III. • Dec 2025 to Present

Autonomous Game Bot (Personal)

Engineered a real-time AI agent using YOLOv8 ONNX models, multithreaded Python, and multivariate kinematics.

Python YOLOv8 OpenCV
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Hardware Reclaimer Prototype
Movement IV. • Jan 2026 to Apr 2026

Automated Hardware Reclaimer (Praxis II)

Engineered a computer vision and mechanical sorting system to reclaim displaced Robertson screws.

  • Frame: Design for X (Sustainability)
  • Converge: Pairwise Comparison Matrix
  • Represent: Prototyping with Purpose
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Biometric Emotion Tracker
Movement V. • Feb 2026

Biometric Emotion Tracker (MakeUofT)

Designed a complex system using GSR skin sensors, ESP8266 microcontrollers, and OpenCV to quantify gift gratification.

C++ Python Arduino OpenCV
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Technical Capabilities

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Software Intelligence

  • Python and Multithreading +
    Engineered an asynchronous pipeline for the Clash Royale bot, running YOLO and OCR on background threads to ensure the main decision loop executes with superhuman reaction times without frame drops.
  • Computer Vision (YOLOv8) +
    Trained custom ONNX models for real-time spatial awareness and utilized Canny Edge detection to bypass dynamic lighting constraints in visual recognition systems.
  • Machine Learning +
    Implemented Random Forest models and OpenCV DeepFace facial landmark analysis to correlate biometric user inputs with optimized gift recommendations at MakeUofT.
  • C++ and Hardware Integration +
    Programmed low-level hardware interactions to process live electrical impulses into quantifiable data structures using Arduino microcontrollers.

Physical Engineering

  • Statics and Shear Analysis +
    Mathematically simulated shear force envelopes and calculated all three forms of plate buckling to optimize load paths for a 1250 N matboard bridge in CIV102.
  • Kinematic Modeling +
    Developed multivariate physics engines to calculate estimated time of arrival based on velocity vectors to dictate predictive spell aiming and troop kiting.
  • CAD and Iterative Prototyping +
    Rendered precise cross-sectional geometry in OnShape and rapidly constructed proxy prototypes to validate spatial redirection mechanisms in Praxis I.
  • Sensor Interfacing +
    Integrated Galvanic Skin Response modules with ESP8266 Wi-Fi chips to create live biometric feedback loops capable of quantifying human emotion.

Design and CTMFs

  • Requirements Frameworks +
    Utilized the NGO Framework to map implicit stakeholder needs to explicit design objectives, successfully bounding the scope of complex engineering problems.
  • Decision Matrices +
    Employed Pairwise and Pugh charts to objectively measure divergent concepts against baseline reference designs using empirical proxy test data to remove subjective bias.
  • Morphological Charting +
    Prevented cognitive fixation by breaking systems into distinct sub-functions and systematically brainstorming combinations to force structural divergence.
  • Spiral Design Methodology +
    Executed complex structural optimization through continuous, multi-stage mathematical iterations, constantly evaluating theoretical maximum strength against practical manufacturability.