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Hi, I'm Peter, a passionate Cognitive Science student specializing in Machine Learning and Neural Computation at UC San Diego. I've been deeply involved in healthcare data analysis with a focus on EEG data from schizophrenia patients, working to improve biomarker analysis and clinical AI tools. I enjoy creating efficient data pipelines and interactive dashboards to support scientific research. I've gained hands-on experience as a Machine Learning Engineer Intern and Data Science Intern, where I optimized model training, enhanced clinical data processing, and developed AI systems integrating state-of-the-art language models. I'm always eager to collaborate on innovative projects that blend data science and AI to make meaningful impacts in healthcare and technology.…Hi, I'm Peter, a passionate Cognitive Science student specializing in Machine Learning and Neural Computation at UC San Diego. I've been deeply involved in healthcare data analysis with a focus on EEG data from schizophrenia patients, working to improve biomarker analysis and clinical AI tools. I enjoy creating efficient data pipelines and interactive dashboards to support scientific research. I've gained hands-on experience as a Machine Learning Engineer Intern and Data Science Intern, where I optimized model training, enhanced clinical data processing, and developed AI systems integrating state-of-the-art language models. I'm always eager to collaborate on innovative projects that blend data science and AI to make meaningful impacts in healthcare and technology.

Mu-en Hsu (Peter)

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Hi, I'm Peter, a passionate Cognitive Science student specializing in Machine Learning and Neural Computation at UC San Diego. I've been deeply involved in healthcare data analysis with a focus on EEG data from schizophrenia patients, working to improve biomarker analysis and clinical AI tools. I enjoy creating efficient data pipelines and interactive dashboards to support scientific research. I've gained hands-on experience as a Machine Learning Engineer Intern and Data Science Intern, where I optimized model training, enhanced clinical data processing, and developed AI systems integrating state-of-the-art language models. I'm always eager to collaborate on innovative projects that blend data science and AI to make meaningful impacts in healthcare and technology.…Hi, I'm Peter, a passionate Cognitive Science student specializing in Machine Learning and Neural Computation at UC San Diego. I've been deeply involved in healthcare data analysis with a focus on EEG data from schizophrenia patients, working to improve biomarker analysis and clinical AI tools. I enjoy creating efficient data pipelines and interactive dashboards to support scientific research. I've gained hands-on experience as a Machine Learning Engineer Intern and Data Science Intern, where I optimized model training, enhanced clinical data processing, and developed AI systems integrating state-of-the-art language models. I'm always eager to collaborate on innovative projects that blend data science and AI to make meaningful impacts in healthcare and technology.

Available to hire

Hi, I’m Peter, a passionate Cognitive Science student specializing in Machine Learning and Neural Computation at UC San Diego. I’ve been deeply involved in healthcare data analysis with a focus on EEG data from schizophrenia patients, working to improve biomarker analysis and clinical AI tools. I enjoy creating efficient data pipelines and interactive dashboards to support scientific research.

I’ve gained hands-on experience as a Machine Learning Engineer Intern and Data Science Intern, where I optimized model training, enhanced clinical data processing, and developed AI systems integrating state-of-the-art language models. I’m always eager to collaborate on innovative projects that blend data science and AI to make meaningful impacts in healthcare and technology.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Advanced

Chinese

Advanced

Work Experience

Data Analysis at Hillcrest Medical Center at UC San Diego Health and NTU Hospital

May 1, 2024 - Present

Designed and implemented a Python-based ETL pipeline using MNE Python to automate EEG data preprocessing from schizophrenia patients, reducing manual workload by 50% and ensuring consistent data quality. Removed over 80% ocular and muscle artifacts using EEGLABICA, notch/band-stop filters, and bad-channel interpolation, enhancing EEG accuracy for downstream schizophrenia biomarker analysis. Built interactive signal visualization dashboards in MATLAB, highlighting frequency bands and temporal patterns across patient groups; facilitated researcher collaboration and reduced analysis iteration time by 38%. Applied statistical time-series modeling to assess if EEG abnormalities statistically regressed toward normal cognitive levels post-treatment, using measures like z-scores and confidence intervals to track mean reversion over time.

Machine Learning Engineer Intern at Industrial Technology Research Institute

September 30, 2024 - July 18, 2025

Constructed optimized SQL queries and pipelines to extract clinical image-text datasets such as X-ray SOAP notes, reducing query latency by 20% and enabling real-time data retrieval for AI models. Implemented systematic hyperparameter tuning and evaluation pipelines (F1 score, ROC-AUC), improving model accuracy by 12% for patient risk stratification tools. Integrated a Retrieval-Augmented Generation (RAG) pipeline with LangChain and large language models (ChatGPT-4, Claude, Gemini), increasing context relevance and clinical-QA accuracy by 15%, simplifying chart lookup for doctors, and reducing cognitive load during patient reviews. Developed a CLIP model linking X-ray images with SOAP notes, boosting disease diagnosis efficiency; designed an Agent system using LangGraph to enhance model interpretability and structured decision-making.

Applied engineer at Chinese Computer Community at UCSD

March 31, 2024 - July 18, 2025

Built Chain-of-Thought (CoT) prompts and guardrails, boosting answer accuracy by 18%, user satisfaction by 20%, and reducing hallucinations by 30%. Wrote efficient instructions for ChatGPT, ported them to proprietary models, trimming tokens by 12%. Edited ChatGPT/Quivr code and indexed over 500 slides, quizzes, and exams. Co-created an Electrical and Computer Engineering tutor that auto-detects course context, raising first-try correctness by 25%.

Data Science Intern Lead at JelloX

September 30, 2023 - July 18, 2025

Led a team to optimize AI model training efficiency, achieving a 63% speed improvement on CPU/GPU platforms. Applied bfloat16 conversion to reduce computational cost while maintaining model accuracy. Conducted A/B experiments across architecture variants and hyperparameter sets, selecting configurations balancing accuracy (+4%) and latency (-25%) for clinical deployment readiness. Developed image-based data augmentation techniques (rotation, contrast enhancement, zoom crop), increasing dataset diversity and improving model generalization by 10%. Deployed automated CI/CD workflows for model deployment, reducing integration time by 30%.