Professional Bio
I am a software engineer with experience building automation, release infrastructure, and developer tooling for mobile engineering teams. Through both industry work and AI/ML coursework, I have developed a strong interest in the responsible use of AI and machine learning, especially where technical problem solving, communication, and practical system improvement come together.
Value Proposition and Audience
Personal Value Proposition
I bring a systems-minded, adaptable, and communication-aware approach to technical work. My background includes workflow automation, developer productivity, release engineering, and the ability to translate complex ideas into clear, useful explanations for different audiences.
Target Audience
Future employer, mentor, or academic reviewer seeking evidence of technical problem solving, practical impact, and continued growth in software engineering and AI/ML-related work.
Education
University of Illinois Urbana-Champaign
M.S. in Biological and Computer Engineering
Jan. 2021 – Dec. 2022 | Champaign, IL
Relevant coursework: Database Systems, Parallel Computer Architecture, Applied Parallel Programming, Artificial Intelligence, Programming Languages & Compilers, System Programming, Topics in Software Engineering.
Zhejiang University
B.S. in Biological Engineering
Sep. 2016 – Jun. 2020 | Zhejiang, China
Relevant coursework: Data Structures and Algorithms, Computer System Organization, Game Development, Statistics and Probability, Numerical Analysis.
Technical Skills
Languages
Python, Kotlin, JavaScript, SQL, C++, Objective-C
Tools
Jenkins, Harness, Docker, Git, Bash, AWS Device Farm
Areas
Automation, CI/CD, Release Engineering, Test Infrastructure, Developer Productivity
Experience
Software Engineer
PayPal
Feb. 2023 – Present | Chicago, IL
- Designed a consistent-hashing scheduler for CI workloads that reduced queue volume by 93% and cut average wait time by 99% to under 0.3 seconds.
- Led migration of 400+ iOS CI and release jobs from Jenkins to Harness and created reusable notification components later adopted across 800+ mobile pipelines.
- Consolidated template-based release workflows with parallel stages and standardized post-processing, improving runtime by 14%–47% across multiple pipelines and saving 47.4 engineering hours per week.
- Built developer-productivity tooling, including a WireMock-based Android test framework that reduced test execution time by 80% and AI-assisted test-case generation that cut manual authoring time by 50%.
Software Engineer Intern
Venmo
May. 2022 – Aug. 2022 | San Jose, CA
- Enhanced CI pipelines by correcting coding errors, improving CI speed and test accuracy. Reduced build times by 20%.
- Built automated end-to-end Android UI and API tests, improving app robustness and reducing user-reported bugs by 25%.
- Deployed tests on AWS Device Farm to automate and record tests across various devices.
iOS Software Engineer Intern
NetEase
May. 2021 – Aug. 2021 | Zhejiang, China
- Developed boosts UI with object-oriented Objective-C code, resulting in a 20% increase in customer frequency.
- Organized code into MVC format to make it more extensible and maintainable, reducing development time by 30%.
Artifacts
This portfolio includes selected artifacts that demonstrate my growth in leadership awareness, analytical reasoning, and applied understanding of machine learning concepts.
Leadership Growth in AI/ML and Change Management
This artifact highlights my reflective analysis of leadership readiness, communication, adaptability, and change management in AI/ML-related environments. It serves as a foundation for my professional identity and shows how I approach growth with intention and self-awareness.
Focus
Leadership development, communication, adaptability, and responsible change management.
Why It Matters
It shows that I understand AI/ML work as both a technical and human-centered field that requires judgment, reflection, and leadership.
Comparing Machine Learning and Deep Learning in Real-World Applications
This artifact explores the practical differences between machine learning and deep learning through real-world examples. It demonstrates my ability to compare AI approaches and evaluate which one is more suitable for a particular problem.
Focus
Conceptual comparison, real-world applications, and practical method selection.
Why It Matters
It shows analytical thinking, problem-solution matching, and the ability to communicate technical distinctions clearly.
Machine Learning Training Methods Guide
This artifact explains how machine learning models are trained and why different learning approaches are used in different situations. It organizes core concepts into a clear and practical guide for understanding model development.
Focus
Supervised learning, unsupervised learning, reinforcement learning, and the training process behind machine learning models.
Why It Matters
It shows my ability to turn technical learning into a polished, audience-friendly resource that connects theory with practice.
Communication Clarity and Leadership in Technical Teams
This artifact focuses on the role of communication in leadership, collaboration, and team alignment. It reframes a course reflection into a professional discussion of how clarity affects performance, trust, and execution in team-based environments.
Focus
Leadership communication, reducing confusion, audience awareness, and improving team understanding.
Why It Matters
It shows that I understand effective AI/ML and technical work as not only analytical, but also communication-driven and collaboration-dependent.
References
- Indiana Wesleyan University. (2026). Professional portfolio artifact template.
- Indiana Wesleyan University. (2026). AI/ML Integration Leadership Skills Self-Assessment Form.
- Indiana Wesleyan University. (2026). Change Management Skills Self-Assessment Form.
- Indiana Wesleyan University. (2026). Machine Learning vs. Deep Learning materials.
- Indiana Wesleyan University. (2026). Problems of confusion assignment materials.
- IBM Developer. (n.d.). A Beginner's Guide to Artificial Intelligence and Machine Learning. Link
- Center for Creative Leadership. (n.d.). How to be a successful change leader. Link
- Change Strategists. (n.d.). How to assess change management skills. Link
- Cleveland Clinic. (2022). Neuroplasticity: What it is, purpose, examples & how to improve it. Link
- BibleGateway. (n.d.). 1 Corinthians 14:8–9 (NIV). Link
- BibleGateway. (n.d.). Genesis 11:6–7 (NIV). Link