Data Engineer, Data Analyst, Bioengineering, Python, MATLAB

Hsin-Yu (Ella) Shih

Willing to relocate **********@*****.*** +1-858-***-**** Linkedin: Ella Shih GitHub Skills

• Front-end Development: React, JavaScript/TypeScript, HTML, CSS

• Languages: Python, SQL, Go, C++, MATLAB

• Machine Learning: scikit-learn, CNNs, Transformers, fine-tuning, PCA, recommendation systems, Deep Learning, ETL pipelines, Pandas/Numpy, PostgreSQL, Git, Linux

• Tools & Infrastructure: Visual Studio, Git, Docker, Windows Server Relevant Coursework: Data Structure, Data Mining, Linear Algebra, Machine Learning, Deep Learning, Statistical Natural Language Processing(NLP), Recommender System & Web Mining Experience & Relevant Projects

Sentiment Analysis System Implementation – Python(OOP), PyTorch, NLP 2026.01

• Improved development accuracy from 0.798 to 0.806 by adjusting model architecture, tuning and training hyperparameters, achieving peak dev accuracy of 0.818 using pretrained GloVe embeddings, and systematically evaluated word-level vs. BPE tokenization (vocab size 2,000), analyzing convergence speed, overfitting behavior, and generalization trade-offs. Hygiea AI, Co-Founder – React.js, TypeScript, HTML, CSS, Full-stack, PostgreSQL, Git La Jolla,CA 2025.02 – 12

• Designed and implemented a front-end, real-time data-streaming web application using React, TypeScript, and HTML/CSS, processing 60 FPS webcam input with <20 ms end-to-end latency, achieving Core Web Vitals: LCP 0.24s, CLS 0.01

• Implemented high-performance UI components for live posture monitoring and feedback, leveraging React Hooks, memoization, and state optimization to ensure smooth rendering under continuous data streams.

• Integrated PostgreSQL (via Supabase) for user authentication, session storage, and structured activity data. Swartz Center for Computational Neuroscience, Graduate Research Assistant – Python, MATLAB, Git, Deep Learning, Modeling, Hyperparameter Tuning, ETL/ELT La Jolla, CA 2024.09 – now

• Benchmarked multiple Large EEG Models—including BIOT (3.3M parameters), ST-Transformer (3.4M parameters)—by fine-tuning each model across 12 hyperparameter configurations on our in-house dataset. Achieved reproducible performance comparisons, including BIOT’s 81.8% accuracy / 0.818 macro-F1 and ST-Transformer’s 78% accuracy / 0.780 macro-F1.

• Built ETL/ELT workflows for multi-modal time-series data in Python and MATLAB handling 10GB+ datasets from 20+ participants with sub-50ms synchronization constraints, improving signal quality by 30% through automated artifact detection and filtering with ASR, reducing manual preprocessing time by 50% Academia Sinica, Research Intern – Python, Data Analysis, Visualization, Reporting Taiwan 2023.07 – 08

• Developed Python-based data ingestion and transformation pipelines for 1,000+ time-series sensor signals from CMOS, converting raw binary streams into structured datasets

• Built data processing and visualization modules to support exploratory analysis and reporting, providing data-driven decision Neural Engineering Lab, NYCU, Undergraduate Research Assistance – Python, Automation Taiwan 2021.07 – 2023.07

• Built automated data preprocessing and transformation workflows for large-scale physiological datasets, standardizing outputs across 150+ experimental sessions. Enhanced clinical decision-making by creating standardized visualizations. Personalized Restaurant Rating Prediction – PyTorch, CNN 2025.09 – 2025.12

• Designed a personalized recommendation system modeling user–item interactions over 80k+ Google reviews, combining collaborative filtering and semantic text representations.

• Built a hybrid SBERT + MLP model to predict user ratings, addressing data sparsity through pretrained sentence embeddings.

• Implemented offline evaluation using RMSE and MAE; achieved RMSE = 0.86, outperforming Word2Vec+CNN baseline. AI Model Development for Motor-Imagery EEG – PyTorch, TensorFlow 2023.12

• Developed and trained SCCNet deep learning models achieving 75% classification accuracy Education

University of California San Diego (UCSD), MS. in Bioengineering 2024.09 – 2026.03(exp.) National Yang Ming Chiao Tung University (NYCU), BS in Biotechnology 2020.09 – 2024.06

• Minor in Artificial Intelligence; GPA: 3.54/4.0 (Class Rank: 6/54)

• Outstanding Outbound Exchange Student Scholarship, NYCU (Spring 2024); Academic Achievement Award, NYCU

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