Dong Payton Pei
Software engineer building local-first AI systems, developer tools, and production mobile applications.
About
Software engineer building local-first AI systems, developer tools, and production mobile applications. Former Nokia and Ford co-op developer/tester and current master's student in Systems Science and Engineering at the University of Ottawa, with hands-on experience in Rust/Tauri, TypeScript/React, Python, SwiftUI, Kotlin/Jetpack Compose, and LLM tool calling.
Projects
pipi-shrimp-agent
Conveyor
Resume Generator
Focus Mint
Work Experience
Nokia Canada
Software Tester Co-op
Ford Motor Canada
Software Developer Co-op
Education
University of Ottawa
Carleton University
Research
Low-Light RAW Image Restoration with Bridge U-Net and DDBM
Skills
Selected Coursework
Completed graduate coursework at the University of Ottawa.
Cyber Security Systems and Strategies
Security principles and risk frameworks for protecting users, data, and networks, covering authentication, access control, encryption, public-key infrastructure, and security in wireless, cloud, and IoT environments.
Official course descriptionFoundation of Modelling and Simulation
System modelling and the simulation process, including continuous and discrete-event simulation, numerical solution of ordinary differential equations, random variates, validation, quality assurance, and simulation languages.
Official course descriptionSystems Optimization and Management
User-requirements analysis, model design, data mining, optimization software, and systems thinking applied to the modelling, simulation, optimization, and management of economic and hierarchical systems.
Official course descriptionEconomic System Design
Systems thinking for economic and complex systems, covering hierarchical systems, simulation and behaviour, soft systems thinking, and interdisciplinary applications.
Official course descriptionMobile Commerce Technologies
Architectures and applications for wireless and mobile commerce, including electronic banking, digital cash, wireless exchanges, business models, mobile networks and routing, content presentation, security, standards, protocols, and case studies.
Official course descriptionAffective and Persuasive Computing
Human affect models, AI-based affect estimation, multimodal fusion, persuasive technologies, persuasion design, serious games, and open challenges in affective and persuasive computing.
Official course descriptionSystems Integration
Planning and design of complex systems across continuous and discrete time, with systems-methodology synthesis, state estimation, parameter identification, discretization, stochastic effects, dynamic and logic control, and discrete-event simulation.
Official course descriptionFoundations and Applications of Machine Learning
Machine-learning capabilities and limitations, problem formulation, supervised and unsupervised techniques, model deployment, monitoring and evaluation, communicating results, and current applications across business, law, arts, social sciences, and education.
Official course description