Hi, I'm Brandon Carone.
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I am a PhD student specializing in computational cognitive science and machine learning with extensive experience in multimodal data processing and perceptual modeling. My research -- focused on fine-tuning foundation models to emulate human sensory perception -- has honed my skills in deep learning, model prototyping, and end-to-end system development. With a deep passion for music, 15+ years of experience in composition, production, and performance, and strong skills in Python, MATLAB, and R, I am eager to apply these transferable skills to advanced challenges in industry.
About
As a fourth-year PhD student at New York University, my work with Dr. Pablo Ripollés and Dr. Iran Roman focuses on modeling human auditory perception through fine-tuning foundation models to "listen" just as humans do, combining cognitive science with machine learning to create innovative audio applications. In the past, I have developed projects like SoundSignature, an app that integrates music information retrieval and AI to provide personalized insights into users' favorite songs. Moreover, my early research focused on how reward and novelty interact to influence memory for music. I’m experienced in developing deep learning models, computational models of music perception, audio feature extraction pipelines, and real-time music generation applications.
- Programming: Advanced: Python, Matlab, R | Intermediate: C++, JavaScript, HTML
- Machine Learning: PyTorch, TensorFlow, Keras, scikit-learn, NLP, probabilistic modeling, Hugging Face Transformers
- Multimodal Research: torchaudio, Librosa, CLIP, ImageBind, CLAP, SpeechRecognition, A/B Testing, MIRToolbox, madmom, music21, mido
- Tools & Technologies: Git, AWS, HPC, Logic Pro X, JIRA
My current focus is on leveraging technology to deepen our understanding of music’s role in cognitive processes and creating applications that make music-related data accessible and insightful.
Education
New York, NY
Degree: Doctor of Philosophy (PhD) in Cognition and Perception
Expected Graduation: May 2026
- Advisor: Professor Pablo Ripollès, Music and Audio Research Lab (MARL)
- Fellowship: Dean’s Doctoral Fellowship
- Relevant Coursework: Deep Learning, Computational Cognitive Modeling, Music Information Retrieval, Auditory Perception, Time Series Analysis
University of California, Los Angeles
Los Angeles, CA
Degree: Bachelor of Science (BS) in Cognitive Science
Graduation: June 2019
- Specialization: Computing
- Honors: Graduated with Honors
- Thesis: Clinically studied or clinically proven? Memory for claims in print advertisements
Projects
Developed an app that integrates MIR with AI to analyze users' favorite songs.
Developed and optimized LSTM networks to analyze fMRI data.
Modified CREMA model to explore alignment of human perception with the model's deep features.
- Implemented to assess how human perception of chord similarity aligns with the CREMA model's deep feature representations.
- Collected and analyzed human similarity judgments on ii-V-I chord variations.
- Tools: Python, Machine Learning, Tensorflow, Keras, Audio Analysis, Chord Recognition
Experience
- Developing a Multimodal LLM for music perception that leverages Variational Autoencoders (VAEs) to model hierarchical and latent structures in music by integrating insights from human auditory perception and curriculum learning to advance AI’s capacity for nuanced music understanding and reasoning.
- Exploring the neural mechanisms supporting music memory (i.e., what makes a song memorable?) using both behavioral and fMRI data. Using ratings of pleasure and a computational model of music novelty, we show that songs are better remembered when they are highly pleasurable to listen to and novel at the same time.
- Guiding improvements in software that reads signals from a consumer EEG headset and feeds them to an adaptive ML algorithm to create meditative music from real-time brain activity.
- Advising on research strategy for clinical studies exploring the psychological benefits of adaptive music generation.
- Conducted research using neuroimaging (MRI, fMRI, DTI, ASL), audiology, eye-tracking, and neuropsychological assessments to evaluate cognition, perception, and brain health.
- Operated structural MRI and multi-band functional MRI scans with children aged 8-12 to study reward sensitivity and obesity risk.
- Processed neuroimaging data using HCP Pipelines, Freesurfer, FSL, and AFNI.
- Conducted medical assessments and patient interviews for protocol management.
- Led a team of five in supporting the Founder/Director with operations, fundraising, research, and legal tasks for a nonprofit creating musical support groups for patients with neurodegeneration.
- Implemented the Public Education and Awareness Platform and launched the “Meet the Expert” Podcast, now with 19 episodes.
- Designed the website and managed Google Ads campaigns, securing a $10,000/month in-kind ads grant.
- Completed an honors thesis examining false memories for print advertisements with a sample of 500+ participants from the local community and Amazon Mechanical Turk.
- Received grant to conduct an independent research study investigating the effects of listening to different musical genres on memory formation.
- Coded the experiment and analyzed data using JASP.
Publications
- Carone, B. J., & Ripollés, P. (2024). SoundSignature: What Type of Music Do You Like? IEEE International Symposium on the Internet of Sounds (IEEE IS2 2024).
- Murphy, D. H., Schwartz, S. T., Alberts, K. O., Siegel, A. L. M., Carone, B. J., Castel, A. D., & Drolet, A. (2023). Clinically studied or clinically proven? Memory for claims in print advertisements. Applied Cognitive Psychology, 37(5), 1085–1093.
- Groves, K., Farbood, M., Carone, B. J., Ripollés, P.*, Zuanazzi, A.* (2024). Through the lens of music: Imagining movie scenes through soundtrack listening. (Scientific Reports, under review).
- Rodríguez-Vázquez, R., Carone, B. J., Groves, K., Namballa, R., Zuanazzi, A. R., Ripollés, P. (2024). Identification of Basic Emotions Through Language Rhythms (in preparation).
- Carone, B. J., & Ripollés, P. (2024). Striking a Chord: The Neural Mechanisms of Novelty and Abstract Reward in Musical Memory (in preparation).
- Carone, B. J., & Ripollés, P. (2024). The Effects of Novelty and Abstract Reward on Memory Performance (in preparation).
Talks & Media
Selected Presentations
- Carone, B. J. (2024, October). Music and AI: Theoretical and Practical Perspectives. Guest Lecturer at Queen Mary University of London.
- Carone, B. J. & Ripollés, P. (2024, October). SoundSignature: What Type of Music Do You Like? Paper presented at IEEE IS2 2024, Erlangen, Germany.
- Carone, B. J. (2024, July). SoundSignature: What Type of Music Do You Like? Guest Lecturer at Stanford CCRMA.
- Carone, B. J., Abrams, E. B., & Ripollés, P. (2023, November). The Effects of Novelty and Abstract Reward on Memory Performance. Poster at Society for Neuroscience, Washington D.C.
- Carone, B. J., Merritt, V. C., Jurick, S. M., & Jak, A. J. (2021, February). Effects of Major Depressive Disorder on Veterans. Poster at the International Neuropsychological Society, San Diego, CA.
- Carone, B. J., Siegel, A. L. M., Castel, A. D., & Drolet, A. (2019, May). False memory for print advertisements. Poster presented at multiple conferences.
Media
- Carone, B. J., Zatorre, R.J., (Interviewees) & Zhu, X. (Host). (2022, October 6). Cognitive Neuroscience of Music and Memory [Audio Podcast]. Research Journey Initiative.
- Carone, B. J. (Interviewee) & Bowes, P. (Host). (2019, April 4). Why music helps us age better [Audio Podcast]. Live Long and Master Aging Podcast.
- Carone, B. J., Rosenstein, C.P., (Interviewees) & Sharp, R. (Producer). (2018, October 10). Music Mends Minds [Radio Show]. BBC Radio 5 Live’s Up All Night with Rhod Sharp.
Skills
Programming
Python
MATLAB
R
C++
JavaScript
HTML
Libraries
NumPy
Pandas
Librosa
scikit-learn
matplotlib
Essentia
Frameworks and Deep Learning
PyTorch
TensorFlow
Keras
Other Tools and Technologies
Git
Logic Pro X
Streamlit
PsychoPy
Honors & Awards
2024 – Awarded $650 to attend the IEEE International Symposium on the Internet of Sounds (IS2 2024).
2022 – Received $4000 grant for research in fMRI studies.
2021 – Fellowship awarded for doctoral research excellence.
2018 – Recognized for research experience and academic performance.
2018 – Awarded $6500 for summer research in neuroscience.
2017 – Received $2000 for academic achievement and research potential.
2016 – Awarded $10,000 for resilience and determination in overcoming adversity.
2016 – Recognized for outstanding academic performance and service.
2015 – Awarded $40,000 for academic excellence in STEM.
2015 – Received $4000 and inducted into the Alumni Scholars Club.
2015 – Awarded $2500 for academic success and community service.
2015 – Awarded $1000 for exemplary performance in high school.