Hi, I'm Michael Li.
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Curious, quick-learning, and passionate researcher who enjoys crafting creative solutions to complex real-world problems using cutting-edge technologies.
About
I am an undergraduate computer science student at the University of Washington. Thriving at the intersection between code and curiosity, I fuel my passion for learning by crafting technical solutions that tackle real-world challenges. My main interests are machine learning and cloud systems: specifically, interactive data analysis and reinforcement learning, as well as architecting and engineering large-scale big-data cloud systems.
- General Skills: Machine Learning, Cloud Computing, Full-Stack Development
- Languages: Java, Python, JavaScript, C++, C, HTML/CSS
- Data Science: PyTorch, NumPy, Scikit-Learn, SciPy, Matplotlib, Pandas
- Frameworks: Spring Boot, Express.js, Flask, Next.js, Ionic Capacitor, React.js, Vue.js, jQuery, EJS, Bootstrap, Material UI, Junit, Jest, Gatling, Cypress
- Services: Azure Kubernetes Service, HashiCorp Consul, Redis, NGINX, Apache Kafka, Keycloak, HashiCorp Terraform, Helm, GitHub Actions
- Databases: MongoDB, PostgreSQL, H2
I'm always looking for opportunities to collaborate and innovate. Let's get in touch and build something amazing!
Experience
- Led project on improving robustness on the traveling salesman problem, published at NeurIPS MATH-AI 2024
- Currently working on new project seeking to improve robustness of robotic manipulation via use of an adversarial curriculum
- Skills: Adversarial Robustness, Machine Learning, Reinforcement Learning, Robotics, Python, PyTorch, NumPy, Isaac Lab
- Designed and implemented a scalable architecture for machine learning microservices within an AKS cluster, with efficiency and fault-tolerance in mind
- Developed an innovative study plan system, using bandits-based algorithms to optimize educational outcomes
- Engineered an adaptive reading recommendation system which personalizes readings based on difficulty, using aggregate user data tracked in up to 8 different ways
- Exposed 3 groups of Flask RESTful APIs for seamless communication between services
- Skills: Machine Learning, Python, PyTorch, NumPy, Matplotlib, Flask, Pandas
Projects
Designed a genetic curriculum for improving TSP model robustness on distributions of practical interest.
- Proposed TSPLib50 dataset for measuring performance on "realistic" distributions
- Improved robustness of neural models on the travelling salesman problem
- Presented at NeurIPS MATH-AI 2024
A free, adaptive, open-source natural science (physics / bio / chem) trainer for motivated secondary school students.
- Adaptively recommend questions appropriate for each students' level
- Database of 4000+ questions, differentiated by 400+ unique tags
- Live at mutorials.org
Education
Seattle, Washington, USA
Degree: B.S. in Computer Science
Cumulative GPA: 3.96/4.0
Relevant Coursework: Reinforcement Learning (579), Social Reinforcement Learning (599J), Interactive Learning (541), Deep Learning (493G), Machine Learning (446), Distributed Systems (452), Modern Algorithms (422), Computer Vision (455)
Friends
Check out my friends!
Rico Qi ● Joshua Jung ● Rich Chen ● Eric Bae ● Alex Niu ● Derek Zhu ● Ryan Huang ● Ved Thiru