As an engineer working on data science related problems, I have the responsibility to craft clever algorithms that work in the most ethical and effective way. I'm commited to work as much as possible on environmentally-responsible projects, that carry a high social impact. I have a passion for data visualization methods, as I believe that they have the potential to bring people from a whole range of backgrounds together to make the best decisions.
Senior Data Platform Engineer • March 2026 - Now •Remote
• Creating an onboard framework in Rust to synthesize only the data necessary for offload, with the goal of slashing sizes by 95%
Data Platform Engineer • September 2024 - February 2026 •Remote
• Developed efficient tools for data processing in Rust, slashing compute time and memory usage by 70% compared to Python version
• Developed and optimized data pipelines using Prefect, Airflow, and Snowflake to handle exponential data growth
• Maintained and developed features for our compute architecture with AWS and Kubernetes, with advanced monitoring and alerting
Data Scientist • November 2023 - August 2024 •Remote
• Implemented a ML model that predicts product loss on delivery, to improve packing decisions and guarantee critical delivery needs
• Contributed significantly to the redesign of the data platform using django+React, unlocking views that empower data-driven decisions
• Coordinated team of Columbia students to create a packing algorithm with MIO and heuristics, reducing number of packages by ~10%
• Developed novel data visualization tool in JavaScript with Plotly/AG Grid to give engineers easy access to review test flight data
Senior Data Scientist • November 2022 - September 2023 • Boston Area, USA
• Built and deployed emergency department nurse schedule optimization algorithms for Hartford Hospital
• Designed advanced data cleaning, analytics, and visualization tools to handle vast amounts of school districts data
• Created cutting-edge transportation optimization algorithms to improve school efficiency in large school districts in the US
• Led weekly trainings for data scientists and analysts to study data analytics packages, algorithms, coding practices, and more
Data Scientist • September 2020 - October 2022 • Boston Area, USA
• Developed and built transportation optimization algorithms for 6 large school districts in the US
• Created a new approach to street crossing restrictions and accessibility for students within US cities
• Deployed backend software serving an interface for school districts to manage their daily transportation operations
Visiting Researcher • April 2019 - August 2019 • Tsukuba, Japan
• Created a music composition tool using advanced Deep Learning techniques (LSTM-RNN) to improve interactive composition.
• Conducted studies to find essential features for user experience in assisted music composition.
Software Developer • June 2018 - August 2018 • Paris, France
Developed an open-source user python interface embedding ag-Grid, by using jupyter widgets. For more details, see the documentation site and this post on Medium.
Mathematics Teacher• March 2007 - February 2010 • Tianjin, China
Teaching Mathematics to 1st and 2nd year students from the Sino-European Institute of Aviation Engineering.
Master of Business Analytics (MBAn) • August 2020
Joint degree between MIT Sloan School of Management and the Operations Research Center. The program is focussing on a mix of Optimization Models and Machine Learning techniques, covering a broad range of Data Analytics methods.
See more about projects.
Engineer Degree - Master of Science in High Performance Computing • August 2019
• Coursework: Parallel/Distributed Computing, Computer Architecture, Operations Research, Machine Learning
French Classes Préparatoires in Mathematics• July 2016
Intense preparation school to competitive exams of the French Grandes écoles (see here for a more detailed explanation). The coursework focused on abstract Mathematics (algebra and analysis), as well as Physics and Computer Science.
Project developed during my position at AIST in Tsukuba, Japan. Includes a plugin for MuseScore3 to generate music for specific sections of the software/different parts automatically.
Artificial Intelligence, Software Development, UX Design
Python module that enables transparent access to ag-grid in a Jupyter Notebook, for simple data visualization, editing and retrieving. I developed it in 2018, maintained it until 2023, and it is now maintained by other contributors.
Data Visualization, Software Development
IpyHC is a package very similar in concept to IpyAgGrid, but implementing the highcharts library instead. It is not in active development anymore.
Data Visualization, Software Development
During our time at MIT, me and my team decided to see how easy it was to predict the outcome of a League of Legends game after the champion pick at the start of each game. We achieved good precision considering the randomness of the game, all details are available in this poster.
Machine learning
During our time at MIT, Yanchunni Guo and I took on the taxis demand predicition and deployment problem in NYC. Our goal was to first develop a prediction model to derive demand per neighborhood at different times of day, and then use that to run a robust optimization model to optimally deploy them all across the city.
All details are available in this report. Machine Learning, Robust Optimization.