Portfolio Requirements

NYU Music Technology Master's Degree Artistic & Academic Portfolio Requirements

The graduate portfolio provides an opportunity to showcase your previous professional, artistic, and academic work in music, technology, and related fields.

You are required to submit up to three work samples that demonstrate the breadth and depth of your background, alongside a Portfolio Description & Provenance Disclosure document.

You should make your portfolio work samples available online (e.g., as streamed media via a reliable service like SoundCloud, Vimeo, or YouTube; Google Drive for files and documents; GitHub for code repositories; or a personal portfolio website). Please ensure that your media does not contain advertisements for ease of access by the Admissions Committee. If password protection is necessary for any of your links, you must include the password(s) in your uploaded Portfolio Description document.

"To submit these works, you must create a separate PDF document on which you list the link(s) and any related notes (e.g., specific cue points). Password-protected folders and sites are not accepted. Technical notes and work descriptions must be provided on separate PDF(s). All PDFs should be uploaded via the portfolio upload link in your application portal.

If you have any questions about the portfolio requirements, contact: music.technology@nyu.edu.

Important Notice Regarding AI-Assisted Tools And Authorship

As part of the NYU Music Technology graduate application process, applicants are expected to demonstrate their individual creativity, musicality, technical proficiency, and academic integrity.

If any AI-assisted, algorithmic, or automated production tools were used in the creation of your portfolio materials, you must disclose them in your Portfolio Description & Provenance Disclosure document. Before preparing your submissions, please carefully review the Academic Integrity, Production Standards, & AI Policy and Portfolio Glossary below.

Please note that assistive tools (such as smart mixing, analysis, workflow utilities, or basic syntax/grammar checkers) are treated differently from generative systems that create complete music, code, or written content on your behalf.

Failure to accurately disclose the use of third-party assets, AI-assisted tools, or generative media may adversely affect the evaluation of your application.

PART 1: Portfolio Samples

For your graduate portfolio, you may submit up to three examples of your best work. You are welcome to submit performance samples if they best represent your background.

Examples of acceptable work samples include, but are not limited to:

• Scientific Publications or Academic Papers: Maximum of 8 pages per paper.
• Audiovisual Materials: Works you have composed, performed, recorded, mixed, and/or produced.
• Software, Hardware, or Technical Projects: Code repositories, circuit designs, or demonstrations of technical tools you have built.
• Personal Websites: Direct links to specific pages hosting your tracks or projects. (This should not be a landing page of your website.)

Note on Range: We strongly encourage you to demonstrate the breadth of your skills by submitting diverse works or projects rather than multiple variations of the same piece. For example, if you have multidisciplinary experience, you might consider submitting a combination of academic research, software development, and audio production rather than three highly similar recordings.

File Naming Rules: When referencing your works in your documentation, please use the following naming convention: NYU Music Technology Graduate Sample #[number]: your name, date (Example: NYU Music Technology Graduate Sample #1: Jane Smith, 1/1/2026)

PART 2: Statement of Musical and Technical Background

In the application, you will provide a brief statement that explains your background and prior studies in music and technology, whether pursued formally or informally.

In this statement, please detail your experience if you have studied—either formally (e.g., through academic degrees, school coursework, private lessons, or certifications) or informally (e.g., through self-study, online tutorials, workshops, or hands-on practical projects)—music theory, music history, music performance, audio engineering, digital signal processing (DSP), or any other technical fields (such as physics, acoustics, electronic, electrical, and/or computer engineering, computer science, programming languages, etc.).

PART 3: Required Other Portfolio-Related Documents

To formally submit your portfolio, you must upload the following distinct items via the portfolio upload link in your graduate application:

Links & Review Notes (PDF) 

Create a single PDF document dedicated strictly to accessing your up to 3 works. This document must include:

• Clickable URLs to your hosted work samples.
• Passwords clearly listed next to the URLs, if password protection is necessary.
• Specific instructions for the Admissions Committee (e.g., identifying which specific sample to review, or specific cue points/timestamps to focus on within a longer audio or video file).

Portfolio Description & Provenance Disclosure (Separate PDF/PDFs)

Any technical notes, work descriptions, and provenance disclosures must be uploaded as separate PDF(s) from your links document. For each sample, provide the following context:

• For audio/video recordings: Specify your exact role(s), such as composer, performer, producer, or engineer.
• For software/hardware: Explain what the project does and identify the programming languages, circuits, or tools utilized.
• For academic papers: Summarize the core thesis and your specific research methodology.
• Provenance Disclosure: You must thoroughly address the Academic Integrity, Production Standards, & AI Policy requirements described in Part 3 for every sample, detailing your third-party assets, AI-assisted tools, and authorship.

PART 4: Academic Integrity, Production Standards, & AI Policy

Our program evaluates your individual potential and foundational skills. Admissions decisions are based on your personal ability to research, code, write, sequence, synthesize, compose, and mix. Whether you are submitting a research paper, a software project, or a music production, you must fully disclose the use of third-party assets, open-source code, and AI-assisted tools. Failure to accurately disclose these tools may adversely affect the evaluation of your application.

To ensure a fair evaluation, you must explicitly address the following four pillars in your written descriptions for each submitted sample:

Source Materials & Asset Attribution

Explicitly state if you have reused any commercially available audio samples, open-source code repositories (e.g., GitHub libraries), or third-party datasets. You must name the source library, platform, or authors where these materials were legally obtained.

Transformative Originality

Describe how you manipulated, edited, or recontextualized any third-party source materials. Detail your manual decisions—whether that involves specific audio chopping, custom plugin routings, modifying open-source code for a new application, or synthesizing existing literature into a novel academic argument.

AI-Assisted Tools and Generative Media

We distinguish between assistive utility tools and generative automation.

• Assistive Tools: If you utilize algorithmic mixing assistants, smart equalizers, code-completion and debugging utilities, or grammar-checking software, you must clearly disclose them and explain your workflow.
• Generative Media Prohibited: Systems that generate complete works on your behalf—such as prompt-based text-to-music generators, or Large Language Models (like ChatGPT) used to write the bulk of your academic papers or code—are strictly prohibited. Generated outputs cannot be submitted as original creative or academic work.
• Statement of Authorship: Explicitly define what constitutes your original work versus a third-party asset, ensuring there is absolute clarity regarding intellectual authorship.

PART 5: Portfolio Glossary

To help you complete your Portfolio Description & Provenance Disclosure accurately, please review how our program defines these essential terms:

• Transformative Originality: The act of taking an existing asset (a commercial audio loop, open-source code block, or dataset) and significantly altering its characteristics, structure, or context through manual techniques. The final work is completely distinct from the stock source material.
• Asset Attribution: The mandatory practice of identifying the exact origin of any third-party materials used in your work that you did not record, synthesize, code, or write from scratch.
• Assistive Utility Tools: Software utilities that use algorithms or machine learning to analyze data and provide automated technical feedback, optimization, or workflow shortcuts (e.g., smart equalizers, automated mastering processors, or basic syntax auto-completion).
• Generative Media (Strictly Prohibited): Automated systems or platforms that generate complete, complex audio files, melodies, essays, or code blocks based on text prompts or algorithmic seeding (e.g., text-to-music generators or Large Language Models). Because these tools make the foundational creative, technical, or analytical choices for you, they bypass the core sequencing, synthesis, coding, and writing skills we evaluate for admission.
• Misrepresentation of Authorship (Plagiarism): Claiming full, unaided creative or academic ownership over elements that were created by someone else or by an automated generative system.