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37 changes: 37 additions & 0 deletions README-imichel.md
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## **Introduction**
Hello! My name is Isabel and I am a CS Master's student specializing in AI. As a first-generation low-income student in CS with a non-traditional background, I am looking forward to committting to this course and going far with my assigned project! Below are my technical skills and projects/experiences.

## **Technical Skills**
- **Languages & Tools:** Python, C++, Java, PyTorch, Google Cloud Platform, AWS, Linux, Git.
- **Technical Skills:** Deep Learning for Computer Vision, Spoken & Natural Language Processing, Decision Making Under Uncertainty, Data Mining & Analysis.

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## **Projects**
### **Cortex-Level Brain MRI Generation Using Diffusion Models**
*Spring 2024*
- Collaborated with a mentor and team at Stanford's Computational Neuroscience Lab to develop a two-stage ML pipeline for generating high-fidelity synthetic brain MRIs.
- Preprocessed 3060 MRIs through denoising, bias correction, skull stripping, affine registration, normalization, and data augmentation.
- Employed unsupervised deformable image registration with diffusion models to learn deformation fields, achieving strong performance relative to baseline models.
- Project report publicly available [here](https://cs231n.stanford.edu/2024/papers/cortex-level-brain-mri-generation-using-diffusion-models.pdf).

### **Cercano: A Parking Spot Near You**
- Developed a decision-making system leveraging reinforcement learning techniques to recommend the closest parking spot. The decision-making policy outperformed random-action by 50% in major urban centers.
- Refined the policy based on simulated parking dynamics, integrating 34,000+ parking structures from public data.
- Used random sampling techniques to position cars within geographic boundaries and optimized parking recommendations based on driving distance and time retrieved via the Google Maps API.
- Project report publicly available [here](https://aa228.stanford.edu/old-projects/).

### **Humor Me!: Detecting Humor in Stand-up Comedy**
- Built a humor detection tool for binary classification on audio input using fine-tuned foundational models (Wav2Vec 2.0, Hubert, Conformer).
- Analyzed ~40 hours of multi-modal, humor-annotated data. Addressed class imbalance and evaluated robustness in misclassification cases.
- Conducted comparative analysis between audio-based and text-based classifiers (DistilBERT).

### **Automated Hate Speech Detection Bot**
- Developed a Discord bot targeting hate speech against women using OpenAI's GPT-4 API and prompt engineering for improved accuracy.
- Presented the project to 15+ industry representatives, showcasing real-time content evaluation and automated actions to enhance user safety.

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## **Research Experience**
### **Research Assistant**
*Esfahani Lab at Stanford University*
- Conducting research on early cancer detection using computer vision to identify potential cancer biomarkers.