Data Science | Music Information Retrieval
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Assessing your cultural and operational fit
gdocs-forensics
June 5, 2026 – Present
Per-character, per-tab contribution analytics for Google Docs — reconstruct a document's revision history into an interactive dashboard and report.
View Projectvlm
May 10, 2026 – Present
Multi-model video understanding experiments with Gemma 4, SmolVLM 2, and MLX-VLM — structured OCR data extraction from video
View Projectmicroreminder
May 10, 2026 – Present
Context-aware, local-first reminder engine powered by on-device LLMs, vision models, and speech-to-text
View Projectliquiprism
February 23, 2026 – Present
Implementation of Liquiprism - Cellular Automata for the Generation of Rhythmic Structure
View ProjectFinetuning-MusicGen-Underrepresented-Genres
February 23, 2026 – Present
Finetuning-MusicGen-Underrepresented-Genres — GitHub repository
View ProjectSonicTouch
June 11, 2025 – June 20, 2025
A repository for Sound Communication Project using OSC
View Projectspeech-recognition
July 13, 2021 – September 3, 2021
Deploy a CNN model for simple Speech Recognition on AWS.
View ProjectCultural Fit Analysis
The candidate's projects show a strong interest in cutting-edge AI/ML applications, particularly in audio processing, natural language processing, and computer vision. This aligns well with an innovative and research-oriented data science culture. However, the projects are all personal and lack team collaboration context, making it difficult to fully assess cultural fit in a collaborative professional environment. The candidate's experience level is listed as 0, which suggests a junior profile, potentially impacting fit for senior roles requiring extensive industry experience.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.