Dr Cătălina Cangea

Staff Research Scientist

Google DeepMind

Biography

I am a Staff Research Scientist and former co-lead of Generative Music at Google DeepMind. I have a decade of ML experience and an extensive background in computer science and competitive programming.

I like to solve problems in the real world using my ML expertise and thrive in collaborative environments where everyone works towards a shared agenda. Music is my lifelong passion - I’ve brought essential contributions to AI tools that support the creative process of making music. I was part of the core Lyria and Music AI Sandbox teams and GDM tech lead for the YouTube Dream Track quality workstream.

My PhD at King’s College, University of Cambridge was awarded with no thesis corrections. I also earned a First Class BA and an MPhil with Distinction from Cambridge. During my studies, I interned at Big Tech and startup companies, top research labs in academia and industry. Since graduate years, I’ve mentored and taught for 100s of hours. I love giving demos, talks or lectures and always get positive energy from a room full of people!

Outside work, I love rowing, travelling, playing rock/jazz guitar and chasing bands on tour. 🎼 I sometimes write poetry and lyrics for future songs :)

Interests

ML tools for music creativity
Long-range generation and reasoning

Education

PhD in Machine Learning, 2021
University of Cambridge
MPhil in Advanced Computer Science, 2017
University of Cambridge
BA in Computer Science, 2016
University of Cambridge

News

Miles beyond thrilled to announce our work on music generative models - Lyria, Dream Track and Music AI tools. Happy to have contributed to both fan engagement and creative exploration avenues, as (1) GDM tech lead for the model quality workstream leading up to the Dream Track launch and (2) core contributor to Lyria and Music AI tools, via identifying useful data signals, adding model capabilities and assessing them via human evaluation studies. Humbled by the fantastic artists who are supporting the Dream Track experiment in YouTube Shorts - check out what shorts they and the 100 creators have uploaded here - and immensely grateful for the Artist Incubator participants, who have been giving us plenty of insights and feedback for developing the Music AI tools!

Launch Nov 2023

Our intern’s project got published in TMLR - congratulations Jannik Kossen for leading this and for a successful internship in summer 2022 at DeepMind!

Publication Jun 2023

After 1 year and 7 months at DeepMind, I am now a Senior Research Scientist! Grateful for the support of my manager and for all my bright collaborators!

Promotion May 2023

Recent Publications

Experience

Staff Research Scientist

Google DeepMind

Apr 2025 – Present London, UK

Generative Media. Responsible development of AI tools for musicians.

Quantitative Researcher

Qube Research & Technologies

Oct 2024 – Apr 2025 London, UK

Senior Research Scientist

Google DeepMind

May 2023 – Jun 2024 London, UK

2024: One of 3 research leads for the generative music effort, working with the other leads to solicit research ideas, plan workstreams, ensure communication between leadership and team members, maintain momentum, and run recurring team meetings. IC work on model controls and finetuning for product use-cases. Regularly delivered demos of our music AI tech to industry stakeholders. The work of our team was presented at various events including Google I/O 2024.

2023: I was a core contributor to Lyria and Music AI Tools (Sandbox), and GDM tech lead for one of the Youtube Shorts Dream Track workstreams, where I coordinated with several YouTube teams to help our research team hit the quality launch bar and inform leadership product decisions.

Research Scientist

DeepMind

Oct 2021 – Apr 2023 London, UK

Part of the Deep Learning team, working on multimodal learning and generative methods for long-range sequential data. Have so far co-led several research projects, published at ICML 2022 and hosted an RS intern whose work got accepted to the Foundation Models for Decision Making Workshop (NeurIPS 2022). External mentoring at EEML 2022 and LOGML 2022.

Research Scientist Intern

DeepMind

Jul 2020 – Nov 2020 Cambridge, UK (remote)

Hosted by Piotr Mirowski, in the Robotics, Embodied Agents and Lifelong learning (REAL) team.

Consultant

Relation Therapeutics

Jun 2020 – Jul 2020 Cambridge, UK (remote)

Developing (graph-)ML solutions to aid in drug development and repurposing efforts.

AI Resident

X, the moonshot factory

May 2019 – Aug 2019 Mountain View, California

Worked on a real-world challenging problem - accurately tracking changes in code across different versions - using and adapting state-of-the-art ML techniques. Patent “Code change graph node matching with machine learning“ now available.

Reviewer

Conferences and workshops

Nov 2018 – Sep 2021

Reviewer for ICML 2020 (was awarded a Top Reviewer Certificate of Appreciation), NeurIPS 2020, BMVC 2020 and WiML 2018, RLGM 2019, LRGR 2019, GRL 2019, ViGIL 2019, GRL+ 2020, ViGIL 2021 (also co-organising).

Research Intern

Mila

Jul 2018 – Sep 2018 Montréal, Canada

Collaboration with Aaron Courville on a visual reasoning project involving a novel benchmark and alternative perspective on EQA-style tasks. Work published at BMVC 2019 and presented as a spotlight talk at the ViGIL NeurIPS workshop.

Machine Learning Teaching Fellow

Cambridge Spark

May 2018 – May 2021 Cambridge, UK

Teaching the Neural Networks module from the Applied Data Science London Bootcamp to industry professionals.

Admissions Interviewer

University of Cambridge

Dec 2016 – Dec 2017 Cambridge, UK

Undergraduate admissions interviews for the Computer Science Tripos, in Murray Edwards College (Dec 2016) and King’s College (Dec 2017).

Supervisor

University of Cambridge

Oct 2016 – Jun 2021 Cambridge, UK

Master’s research projects: Structure-aware Generation of Molecules in Protein Pockets (Pavol Drotar, 2020-21) (⁹²⁄₁₀₀) (presented at NeurIPS MLSB), Machine Unlearning (Mukul Rathi, 2020-21) (⁹¹⁄₁₀₀), Goal-Conditioned Reinforcement Learning in the Presence of an Adversary (Carlos Purves, 2019-20) (⁸⁷⁄₁₀₀), Representation Learning for Spatio-Temporal Graphs (Felix Opolka, 2018-19) (⁸⁵⁄₁₀₀) (presented at ICLR RLGM), Dynamic Temporal Analysis for Graph Structured Data (Aaron Solomon, 2018-19) (presented at ICLR RLGM)

Computer Science Tripos Part II projects: Benchmarking Graph Neural Networks using Wikipedia (Péter Mernyei, 2019-20, Novel Applications spotlight talk at ICML GRL+), Multimodal Relational Reasoning for Visual Question Answering (Aaron Tjandra, 2019-20), The PlayStation Reinforcement Learning Environment (Carlos Purves, 2018-19) (⁸⁰⁄₁₀₀) (presented at NeurIPS Deep RL), Deep Learning for Music Recommendation (Andrew Wells, 2017-18) (⁷⁶⁄₁₀₀).

Undergraduate courses for Murray Edwards, King’s, and Queens’ Colleges: AI, Databases, Discrete Mathematics, Foundations of Computer Science, Logic and Proof, Machine Learning and Real-world Data.

Software Engineer Intern

Facebook

Jun 2016 – Sep 2016 London, UK

LogDevice team. I optimised client operations on a RocksDB database and implemented a new API required by another team in Facebook.

Software Engineer Intern

Facebook

Jul 2015 – Sep 2015 New York, USA

iOS Product Infrastructure Team. I worked towards delivering a better experience for users of the Facebook iOS app. My project aimed to reduce the time taken to load content close to the area currently being viewed on screen, by improving the prioritization system for network requests.

STEP Intern

Google

Jun 2014 – Sep 2014 Zurich, Switzerland

YouTube Uploads team. I added processing progress for video uploads on several YouTube pages, as the Upload page was the only one displaying this information.

Recent & Upcoming Talks

Text-and-audio methods

An overview of text-and-audio methods that supports the Multimodal Learning module in R255.

Jan 30, 2024 1:00 PM — 2:00 PM Lecture Theatre 2, Computer Laboratory, William Gates Building

Music AI Tools @ NeurIPS

A live demo of our ongoing work on Music AI tools; more info here.

Dec 13, 2023 12:00 PM — 1:30 PM New Orleans Ernest N. Morial Convention Center

Autoregressive long-context music generation with Perceiver AR

A talk on our recently-published general-purpose architecture, Perceiver AR, and why long context matters when processing real-world …

Oct 4, 2022 4:00 PM — 5:00 PM Virtual

Video Follow

See all talks

Accomplishments

Promotion

DeepMind May 2023

After 1 year and 7 months at DeepMind, I am officially a Senior Research Scientist (now at Google DeepMind!) - grateful for the support of my manager and my bright collaborators!

Top Reviewer Certificate of Appreciation

Thirty-seventh International Conference on Machine Learning Sep 2020

The Top Reviewer Certificate of Appreciation acknowledges ‘excellent service as a reviewer for ICML 2020’, awarded by the Program and General chairs.

Wiseman Award

Department of Computer Science and Technology, University of Cambridge Oct 2019

The award acknowledges those who make a commendable contribution to the work of the Department, going above and beyond the requirements of their course or project.

Travel Grant

Machine Learning for Health Nov 2018

Travel award to attend the Machine Learning for Health (ML4H) Workshop at NeurIPS 2018.

Travel Grant

Women in Machine Learning Oct 2018

Partial funding for travelling to NeurIPS 2018 and presenting my poster at the WiML workshop.

MPhil Graduation Prize

Darwin College, University of Cambridge Oct 2017

Awarded for obtaining a Distinction in the MPhil degree.

Master of Philosophy in Advanced Computer Science

Department of Computer Science and Technology, University of Cambridge Jul 2017

Graduated with Distinction.

Bronze Medal

Hack Cambridge Recurse Jan 2017

Won 3rd place at the Hack Cambridge MLH hackathon, as part of team facejack.

Rosemary Murray Scholarship

Murray Edwards College, University of Cambridge Jun 2016

Awarded for obtaining a First Class result in Part II of the Computer Science Tripos.

Bachelor of Arts in Computer Science

Department of Computer Science and Technology, University of Cambridge Jun 2016

First Class honours in final year.

Paula Browne Scholarship

Murray Edwards College, University of Cambridge Oct 2013

Received the scholarship every year during my undergraduate degree. The scholarship was given to only one other student in my year.

Silver Medal

National Competitive Programming Olympiad Apr 2011

Awarded for obtaining 10th place at the National phase of the Olympiad during 10th grade.

Special Prize for Best Writing Style

National English Language Olympiad Apr 2011

Awarded for obtaining the highest score on the essay that was part of the written task.