Alexis Gassmann

Actively engaged in the CrunchDAO community, a Web3 collective intelligence decentralized protocol, enabling me to explore the intersection of Web3 and data science competition challenges.

1st place in the 50 000$ Autoimmune Disease 2025 Challenge #2 4th place in the 50 000$ Autoimmune Disease 2025 Challenge #1 2nd place in the 100 000$ Adia Lab 2024 Causal Discovery Challenge 3rd place in the 10 000$ VCs prediction CrunchDAO 2024 Challenge 1st place in the 100 000$ Adia Lab 2023 Challenge Kaggle competition Expert (global rank: 525): - 19th/1610: Coleridge Initiative (NLP: Question Answering (QA), NER, Topic modeling, classification) - 45th/1571: Google Quest Q&A Labeling (NLP: QA, classification) - 55th/825: NFL Health & Safety - Helmet Assignment (CV: tracking on videos, OCR) - 73th/1275: VinBigData Chest X-ray Abnormalities Detection (CV: object detection, classification) - Participated in 27 competitions, earning 10 medals along the way and learning from challenges by studying solution papers My research work has also included automating topic extraction, AutoML and AutoNLP. Currently working on the subject of “Autoimmune Disease - identify biomarkers of cancer initiation in patients with Inflammatory Bowel Disease” and “Detecting structural changes in time series“

Consultant managing full project cycles (including commercial proposals and outreach) and delivering data-driven solutions across diverse missions: - Developing a tool for comparing anomalies from inspection images of pipeline networks at a large scale (Computer vision and deployment of a Streamlit application) - Developing a sensory mapping application (Microsoft Azure database and deployment of a Django application) - Setting up an automatic client scoring pipeline on GCP & BigQueryML - Estimation of the DPE (Diagnostic de Performance Energétique) for all of France (POC) - Development of a large data acceptance application (terabyte size - Spark and deployment of a PyQT application)

NLP - Sentiment Analysis & creating an automated training and deployment of NLP models

NLP - Automatic topic extraction and labeling