Adrien Carrel

About me

I am an experienced quantitative researcher with advanced degrees in mathematics and computing, and a solid foundation in machine learning, physics, and engineering. My professional journey in quantitative finance and machine learning includes significant roles at esteemed institutions like Blockchain.com and Schonfeld, where I have designed and implemented innovative trading strategies and developed robust mid-frequency trading signals.

My academic and research background is equally distinguished, with a master's degree in Advanced Computing from Imperial College London and a master’s degree in Applied Mathematics from CentraleSupélec, both earned with distinction and first-class honours. This academic path led me to conduct research at MIT, where I applied data science techniques to global health challenges. Additionally, my teaching roles at Harvard T.H. Chan School of Public Health, CentraleSupélec, Lycée Hoche, and numerous international conferences have enabled me to share my expertise in machine learning and computer science, mentoring students through rigorous programming and data analysis projects.

I am proficient in a wide array of programming languages and tools, and have utilized these skills in various research and professional projects. My personal projects, including the development of an AutoML Python package and the creation of a cryptocurrency trading bot, highlight my ability to leverage machine learning for practical solutions. My multilingual capabilities and leadership in extracurricular activities further illustrate my versatility and dedication to excellence in both professional and personal endeavours.

Connect with me

You can reach out to me via any of these links!

Professional Experience

Blockchain.com - Quantitative Researcher

August 2024 - Present. London, United Kingdom.

Design and implement new crypto trading strategies.

Schonfeld - Quantitative Researcher

October 2023 - August 2024. London, United Kingdom.

(Work for Farringdon Capital, a quant team of Schonfeld.)

Developed 15 mid-freq signals on US and EU equities with Sharpe ratios ranging from 1 to 3, using statistics and NLP.

Co-responsible of a book ≈ 150M$ AUM.

Devised, implemented and monitored intraday arbitrage strategies across multiple assets.

Created monitoring and risk management tools for the team.

Massachusetts Institute of Technology (MIT) - Research Intern

March 2022 - September 2022. Cambridge, United States.

Analyzed the relationship between social vulnerabilities, political leaning and mortality (all-causes, COVID-19, excess mortality) across U.S. counties (Python, R, PyTorch).

Mentoring of 8 students for HST.936: Leveraging Data Science in Global Health. Design of 4 assignments for HST.936 & HST.953: Clinical Data Learning, Visualization, and Deployments.

Harvard T.H. Chan School of Public Health - Teaching Fellow

July 2022 & 2023. Boston, United States.

Mentoring of 15 students for three different Machine Learning in Healthcare courses.

Melanion Capital - Crypto Research Analyst Intern

August 2021 - November 2021. Paris, France.

Implemented the back-end algorithms behind the Melanion BTC Equities Universe UCITS ETF: AUM: 2.4M€.

Conducted quantitative research on how to replicate a volatile index (whitepaper written: Maximum Benchmark Exposure).

Enhanced ML models to predict up and down surprises on futures on dividends (balanced accuracy increased by 5%).

Lycée Hoche - Oral Examiner in Mathematics and Physics (Khôlleur)

March 2021 - June 2021. Versailles, France.

Assessing 33 MP* and MPSI (STEM) students' Mathematics & Physics skills and preparedness for taking the entrance examinations for the most selective French engineering "Grandes Ecoles".

CentraleSupélec - Teaching Assistant in Computer Science

November 2020. Gif-sur-Yvette, France.

Assisted Professor during the "Coding Weeks": a 2-week intensive programming bootcamp. Mentored and graded 6 projects teams (31 students) about the use of TensorFlow and Open-cv Python libraries.

LCsys - Machine Learning Engineering Intern

July 2020. Longjumeau, France.

Improved Google's Tesseract OCR algorithm to detect printing defaults on French identity cards using deep learning and machine learning (accuracy evaluated on 12000 id cards increased from 96% to 99.6%).

Education

Imperial College London - MSc Advanced Computing

October 2022 - October 2023. London, United Kingdom.

Grade: Distinction.

Thesis: Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential Equations.

Relevant courses: Deep Learning, Probabilistic Inference, Computer Vision, Reinforcement Learning, NLP, Computational Finance, Mathematics for Machine Learning.

CentraleSupélec - MEng (Diplôme d'ingénieur)

September 2019 - Expected October 2023. Paris, France.

GPA: 3.91/4. First Class Honours. Course representative.

Relevant courses: Machine Learning, Advanced Probabilities, Algebra and Cryptology, Advanced Statistics, Algorithmics & Complexity, Optimization, Partial Differential Equations.

BSc in Engineering also obtained with First Class Honours during the curriculum.

Lycée Hoche - Classes Préparatoires - MP*

September 2018 - August 2019. Versailles, France.

GPA: 4/4. Mathematics and Physics (Option: Computer Science). Student representative for 39 classmates.

Université de Versailles Saint-Quentin-en-Yvelines (UVSQ) - BSc Applied Mathematics

September 2018 - June 2019. Versailles, France.

BSc in Applied Mathematics obtained while also attending Classes Préparatoires.

Lycée Corneille - Classes Préparatoires - MPSI/MP*

September 2016 - August 2018. Rouen, France.

Mathematics and Physics (Option: Computer Science).

Research

Papers

*: equal contributions

Thesis

Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential Equations

Adrien Carrel.

September 2023.

Publications

Going beyond the means: Exploring the role of bias from digital determinants of health in technologies

Marie-Laure Charpignon*, Adrien Carrel*, et al..

October 2023.

Preprints

Neural Laplace for learning Stochastic Differential Equations

Adrien Carrel.

December 2022.

NeurML : From an automated EEG preprocessing pipeline with source reconstruction to ML models predicting gender and brain age

Thomas Segré*, Adrien Carrel*, Ugo Muhieddine.

June 2021.

Whitepapers

Maximum Benchmark Exposure

Adrien Carrel, Jérémie Besson, Ghali Laraqui.

September 2021.

Technical Supporting File

Dossier Justificatif Technique pour Crédit d'Impôt Recherche (CIR) (Technical Supporting File for Research Tax Credit)

L'exposition à un benchmark et sa réplication avec des actifs traditionnels (Exposure to a benchmark and its replication with traditional assets)

Adrien Carrel, Jérémie Besson, Ghali Laraqui.

October 2021.

Review

KDD 2022 Workshop epiDAMIK.

KDD 2024 Workshop epiDAMIK.

Talks

3rd Tokyo Health Datathon, Tokyo Medical and Dental University (September 2023) - Mentor.

Society of Critical Care Medicine - New York Datathon (August 2023) - Mentor.

MIT Health Datathon (May 2023) - Mentor.

Make Health Chile (January 2023) - Workshop & Mentor.

Critical Care Data Analysis Summit and Tarragona Datathon (November 2022) - Mentor.

Eitri Medical Datathon (September 2022) - 2 Workshops. EHR data and Machine Learning implementation pitfall. Leveraging alternative data sources (e.g. google trends, media data) for Machine Learning in Healthcare.

Make Health Colombia (August 2022) - Introductory Training, Classification and Regression using Python on COVID-19 and Media data in Latin America.

Women in Data Science (WiDS) Datathon 2022. Excellence in Research Award (Phase II). MIT Critical Data: CDC county level COVID data. Presentation of a dataset & office hours.

Teaching

Harvard T.H. Chan School of Public Health - Teaching Fellow

2022 - 2023. Boston, United States.

Mentoring of 4 students for HST.956: Machine Learning for Healthcare (Spring 2023)

Designed 2 assignments for HST.953: Clinical Data Learning, Visualization, and Deployments (Fall 2022)

Mentoring of 3 students for BST.209: Machine Learning in Healthcare (July 2022)

Mentoring of 8 students for HST.936: Leveraging Data Science in Global Health (Spring 2022)

University of Massachusetts Chan Medical School - Teaching

2022. Boston, United States.

N707 BioInformatics Course - The importance of domain knowledge in AI in healthcare

NSF Data Science and Machine Learning. Preparation of materials for the course