Raphael Azorin
I am a Machine Learning Engineer working in R&D, bridging the gap between research and product development. Currently, I work at Ubisoft, where my focus lies in fraud detection within games and transactions.
Prior to this, I served as a Data Scientist at Huawei Research, where I completed my PhD in Machine Learning for network measurements in collaboration with Sorbonne University. I have experience in several data-related roles across various company sizes, from startups to large enterprises. I received my academic education at PSL, where I was enrolled in work/study programs from BSc to MSc.
Before venturing into Computer Science, I worked in marketing and analytics. During that time, I played a pivotal role in the growth of Markentive, France’s leading marketing automation agency, contributing to its expansion from 5 to 30 employees.
news
| Sep 1, 2024 |  I started a new position as Senior Machine Learning Engineer at Ubisoft. |
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| Aug 26, 2024 |  Our paper Fine-grained Attention in Hierarchical Transformers for Tabular Time-series was presented at KDD’24 10th Mining and Learning from Time-Series Workshop. |
| Jul 20, 2024 |  I contributed to the Cuckoo hashing Wikipedia page. |
| Jun 18, 2024 |  I successfully defended my PhD thesis on Traffic Representations for Network Measurements. |
| May 23, 2024 |  Attended the IHES workshop on Mathematics for and by Large Language Models. |
| Apr 25, 2024 |  Took part in the HuggingFace x Mistral hackathon on LLMs for industry. |
| Mar 28, 2024 | Our paper Taming the Elephants: Affordable Flow Length Prediction in the Data Plane will be presented at CoNEXT 2024. |
| Dec 8, 2023 |  Volunteered at CoNEXT’23 @CNAM in Paris |
| Dec 6, 2023 |  Presented our poster Memory-Efficient Random Forests in FPGA SmartNICs at CoNEXT’23 |
| Dec 5, 2023 | Our paper SPADA: A Sparse Approximate Data Structure Representation for Data Plane Per-Flow Monitoring has been accepted in PACMNET |
| Aug 28, 2023 | Enrolled at the Mediterranean Machine Learning summer school in Thessaloniki (M2L 2023) |
| Feb 14, 2023 | Our workshop paper “It’s a Match” - A Benchmark of Task Affinity Scores for Joint Learning has been accepted at AAAI’23 2nd International Workshop on Practical Deep Learning. |
| Dec 9, 2022 | Our extended abstract Learned Data Structures for Per-Flow Measurements has been accepted at CoNEXT’22 student workshop. |
| Nov 15, 2022 | Our paper Towards a Systematic Multi-Modal Representation Learning for Network Data has been accepted at HotNets’22. |
| Dec 7, 2021 | Presented our extended abstract Towards a Generic Deep Learning Pipeline for Traffic Measurements at CoNEXT’21 student workshop |
| Aug 1, 2021 | Volunteered at SIGCOMM’21 |
| May 10, 2021 |  Gave a tutorial on link prediction at PSL executive MSc in Paris Graph Analytics lab. |