I lead the ML team at Onfido. We use computer vision and deep learning for online identity verification. From 2015 to 2021, I led the machine learning team for recommendation at Criteo. From 2010 to 2014, I led the computer vision team at Thales Optronics in France.
I graduated with a PhD at MIT in 2010 under the supervision of Prof. Seth Teller. I was a core member the MIT team at the DARPA Urban Challenge in 2007. My work was published at CVPR, ICCV, ICRA and IJFR. I teach the deep learning class at ENSAE Paris.
Posts
- Sept 2024, The Handbook of Applied AI teams
- Jan 2023, AI has crossed the Rubicon. Now what?
- Dec 2022, Building a recommendation engine from scratch
- Sept 2022, Building without Bias at Onfido
- Aug 2022, Where self-driving is headed
- Jan 2022, Lightweight Representation Learning For Efficient And Scalable Recommendation
- Dec 2021, The high road of performance review
- May 2020, The tradeoffs of large-scale machine learning: the price of time
- Feb 2020, Your first 90 days as a tech lead
- June 2019, Making your company machine learning-centric
Featured talks
- 2024, Oct 17th: Fraud Prevention with Computer Vision in the GenAI age, AIAI Boston, slides
- 2023, June 4th: ML Prague, Bringing automation and fairness to identity verification on the internet with deep learning - slides
- 2023, June 21st: An introduction to ChatGPT and generative AI, Point Nine CTO Meetup, Paris - slides
- 2023, March 30th: ChatGPT: have we crossed the Rubicon? Invited talk at BPCE DigiPay Tech+ Event
- 2022, IFTTD podcast: Large-scale AI (in french), youtube video
- 2020, Job interview talk at Onfido, Scalable representation learning and retrieval for online advertising
- 2018, 7th RecSys London Meetup, Acquisition: Recommending Products From a Retailer That the User Never Visited Before
- 2017, Criteo RecSys London, Product recommendation beyond collaborative filtering, welcome to the twilight zone!
- 2016, ICML: Online Advertising Systems Workshop, New challenges for scalable machine learning in online advertising
- Oct 2014, ICIP, Image and Video Processing for Defense, Transportation, Homeland Security, and Observation from Space: Industrial Expectations and Technological Challenges
Publications
- Lightweight representation learning for efficient and scalable recommendation, arxiv:2101.00870v2, Nov 2021
- Ground robot navigation using uncalibrated cameras, ICRA 2010
- PhD Thesis, 2010
- Body-relative navigation guidance using uncalibrated cameras, ICCV 2009
- A perception-driven autonomous urban vehicle, IJFR 2008
- Wide-area egomotion estimation from known 3d structure, CVPR 2007
- SLYK: A Transparent Fault-Tolerant Migration Platform, MIT Technical Report, 2005
- The City Scanning Project: Validation and Algorithms, MIT Technical Report, 2002
Teaching
- Teaching the Deep Learning class at Master Level (3rd-year) at ENSAE, since Spring 2024
- Teacher at M2 level at Paris Dauphine University with Criteo, IASD, 2019-2020
- Teacher at the Workshop on Recommendation, Ecole Polytechnique Data Science Summer School, June 2018 & 2019
- Back in 2008, I taught Java at MIT over IAP. This was one of the first courses to end up on opencourseware the following years!
Misc
- Book recommendations for tech leaders.
- I co-founded Reveal, the RecSys workshop for causal recommendation with Microsoft, Netflix and Cornell University. The workshop ran from 2018 to 2020 and now continues as the Consequences workshop.
- In 2015, I won the Criteo 2015 Hackathon (16 teams) with image-based similarity using deep networks: developed an end-to-end pipeline with Python/caffe/cuDNN/protobuf on AWS processing 400K images per hour and shipped to AB test
- Google Hashcode: 5/65 in 2015 Finale Round, 76/1054 in 2016, 300/2815 in 2017
- Finishing Advent of Code 2023 - blog post - github