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Hello! I'm Valen, currently a graduate student at UCLA studying Artificial Intelligence, previously majored in Data Science at Claremont McKenna College. I have experience in using various tools and frameworks to handle complex data sets and build machine learning models. I am passionate about transforming data into actionable insights and exploring new domains.

• Data Analysis: Cleaning and transforming data to perform analysis, extracting meaningful information from diverse datasets.
• Machine Learning: Applying various algorithms and models to train predictive models and make accurate predictions.
• Data Visualization: Presenting data in an engaging and informative manner using charts, graphs, and interactive dashboards.
• Statistical Analysis: Leveraging statistical methods to uncover patterns, validate hypotheses, and derive actionable insights.
• Methodologies: Machine Learning, Deep Learning, Reinforcement Learning, Data Mining, Big Data Analytics, Exploratory Data Analysis, Data Preprocessing
• Languages: Python (Pandas, NumPy, Scikit-Learn, Seaborn, Matplotlib, Pytorch, Tensorflow), R (Dplyr, Ggplot2), SQL, C++, Java
• Tools: Jupyter Notebook, Tableau, Power BI, Git, MS Excel, VS Code, R Studio, Eclipse, Postgres SQL, Docker

Check out some of my projects:

1. (In Progress) Neural robotic arm: Brain-machine interfaces (BMIs) that have been successful in controlling robotic arms largely depend on invasive brain implants. They pose surgical risks and are unaffordable to many patients. Therefore, we combine our research in robotics and EEG-based BMI to develop an affordable non-invasive robotic arm. Currently we implementing C++ libraries to ensure smooth communication between our software and the robotic arm.
2. Evalute and compare CNN, CRMM, and Transoformer when classifying EEG data
3. Game development using Rust: 2D, 3D
4. My first IOS app for my high school CS class