• 🔭 I’m currently working on Computer Vision [Event-Camera Based Vision (or Dynamic Vision Sensor, DVS)], utilizing technologies such as Pytorch, Pytorch Lightning, and Kubernetes (K8S)(private for now).

• 🌱 I specialize in data science, machine learning, and deep learning, with a passion for applying these disciplines to solve complex problems and extract meaningful insights from data.

• 📊 I've led and contributed to several impactful projects, including event camera data based Continuous Human Pose Estimation and Integrated Game Recommendation System utilizing modern databases within a Docker environment for efficient management of complex data and user profiles.

• 🛠 My technical skill set includes: Advanced Programming Languages: Python (with a focus on data science and ML/DL libraries), HTML for web development, and software engineering.

  Machine Learning/Deep Learning Frameworks: Proficient with PyTorch, TensorFlow, scikit-learn, and experienced in developing algorithms for computer vision and anomaly detection.

  Big Data Technologies: Hands-on experience with Apache Spark and Hadoop for scalable data processing, and Apache Hive for data warehousing.

  Database Management: Skilled in SQL databases with practical experience in MySQL, MongoDB, and Neo4j, enabling efficient data storage, manipulation, and complex query execution.

• 👨‍💻 All of my projects are available at https://github.com/j8chiu.

• 📫 Reach out to CHIU @ [email protected].

• ⚡ Fun fact I've got a Ph.D. in Dota 2—Piled Higher and Deeper in hero builds and last-minute saves!.

- Programming Languages

Python: Extensive experience for data science, ML, and DL applications, including libraries like Numpy, Pandas, Matplotlib, and frameworks such as PyTorch and TensorFlow.
HTML: Proficient in web development, creating user-friendly interfaces and integrating with backend services.

- Databases

MySQL & PostgreSQL: Strong foundation in relational database management systems, optimizing data structure and ensuring data integrity.

MongoDB: Experienced in NoSQL databases for handling large-scale, unstructured data.

Neo4j: Skilled in graph databases, enhancing data relationships and pattern recognition for complex queries and analytics.

- ML / DL / Big Data

Machine Learning Algorithms: Expertise in K-Nearest Neighbors (KNN), Decision Trees, SVM, and ensemble methods for predictive modeling and classification/clustering tasks.

Deep Learning: Proficient in GNNs, CNNs, RNNs, and GANs, applying them to computer vision, NLP, and generative tasks.

Topological Data Analysis: Skilled in topological deep learning, utilizing libraries and frameworks to integrate topological features into deep learning models for enhanced predictive capabilities.

Data Processing & Analysis: Experienced with big data frameworks like Apache Spark for real-time data processing and analytics, and Apache Hive for querying and managing large datasets.