Curriculum Vitae
Education
The University Of Queensland (Feb, 2019 - June, 2023)
I received a Bachelor of Information Technology degree from the University of Queensland, within the Faculty of Engineering, Architecture, and Information Technology (EAIT), and the School of Electrical Engineering and Computer Science (EECS).
During the studies, I completed several courses related to Information Technology and Computer Science, including front-end development, functional programming, advanced mathmatics, machine learning, computer systems principles and programming, computer OS architecture and network development, and etc.
Here are the key features details of the courses:
• Reasoning About Programs (Feb 2023 - June 2023) (Grade: 6/7)
Dafny functional programming, Behavior Specification, Formal Methods, Correctness Proofs, Weakest Precondition Reasoning, Algorithm Implementation
• Artificial Intelligence (July 2022 - Oct 2022) (A2 MDP: 87.7/100, A3 RL: 89.3/100)
Reinforcement Learning algorithms and principles, Graph Traversal Algorithms: BFS, DFS, IDDFS, Shortest Path Algorithms: Dijkstra, UCS, A*, Bellman-Ford, Floyd-Warshall, reasoning and planning with certainty, decision-making under uncertainty, Markov Decision Process(MDP), Q-learning,State-Action-Reward-State-Action(SARSA), Multi-Armed Bandit
• Calculus & Linear Algebra II (Nov 2021 - Feb 2022)
Multi-dimensional calculus, Linear algebra, Taylor series, Maxima, minima, and saddle points, Method of least squares, Vector spaces, norms, and inner products, Gram-Schmidt orthogonalisation and orthogonal matrices
• Operating Systems Architecture (July 2021 - Oct 2021)
OS design and implementation based on FreeBSD, Reverse engineering, Binary files analysis, Disassembly and Coredump debugging, Kernel-level programming, Device driver programming, Principles and programming of operating system support for distributed and real-time computing
• Algorithms and Data Structures (July 2021 - Oct 2021)
Analysis of time and space complexity of algorithms. Sequences. Lists. Stacks. Queues. Sets, multisets, tables. Trees. Sorting. Hash tables. Priority queues. Graphs. String algorithms.
• Numerical Methods in Computational Science (July 2021 - Oct 2021)
MATLAB, Curve-fitting, Numerical differentiation and integration, Bisection, Fixed-point iteration, Gaussian elimination. Ordinary differential equations, Monte Carlo methods, Numerical integration and optimisation.
• Computer systems principles and programming (Feb 2021 - June 2021) (Grade: 6/7, Rank: 65/290)
Systems Programming in C, Linux OS Bash Programming, GDB debugging, Processes and threads, Interprocess communication, Network programming
The foundation year of University Of Queensland (Feb, 2018 - Nov, 2018)
Enrolled in an interdisciplinary program, I successfully completed courses in Physics, Business Management, Mathematics, English Literature and Essay Writing, and Information Technology. Through the information technology course, I acquired fundamental skills in HTML and CSS, and gained a solid understanding of web design principles. This experience cultivated my logical thinking, basic coding abilities, and self-learning skills.
Certificates
• AWS Knowledge: Cloud Essentials, AWS, Feb. 2024 - March 2024
• Use Machine Learning APIs on Google Cloud, GCP, May 2024 - June 2024
• Build a natural language processing solution with Azure AI Language, Microsoft Azure, June 2024 - July 2024
• Machine Learning and Deep Learning Algorithms, MLOps, NLP, CV, Sequence models and other fields related to Deep Learning and Data Science from Coursera(mainly), Kaggle, IBM, Cisco
These certificates mentioned above can be accessed from my personal website and LinkedIn Page
Skill set
(Machine Learning and Deep Learning)
• Environments: Conda, Jupyter Notebook
• Packages: Numpy, Pandas, Scikit-learn
• Visualization: Seaborn, Pillow, Matplotlib
• Frameworks: Tensorflow, Keras, Pytorch
• Databases: AWS S3, MinIO, GCP bigQuery
• Cloud Services: AWS, GCP, Azure
• ML Lifecycle Management tool: MLflow
• Image Containerisation: Docker, AWS ECR
• Image Orchestration: Kubernetes (AWS EC2, EKS)
• ML Cloud Platforms: AWS SageMaker, Kubeflow
• CI/CD: Argo Workflow, Tekton, GitHub Actions
• Repo: GitHub, DagsHub, HuggingFace