معرفی
Yanlei Diao is a Professor of Computer Science at Ecole Polytechnique in France and also holds a professorship at the University of Massachusetts Amherst. She joined Ecole Polytechnique in September 2015 and leads the CEDAR research team focusing on Rich Data Exploration at Cloud Scale. Her work bridges theoretical computer science with practical big data systems that address real-world challenges in data analytics.
Professor Diao's research spans big data analytics, scalable intelligent information systems, and cloud data processing infrastructure. Her work emphasizes practical solutions for explainable anomaly detection, interactive data exploration, and uncertain data management. She has pioneered systems like UDAO (a next-generation optimizer for cloud analytics), EXAD (explainable anomaly detection), AIDEme (interactive data exploration), and GESALL (genomic scalable analysis) that have influenced both academia and industry.
Her recent publications reveal a strong focus on making big data analytics more explainable, efficient, and accessible. She has developed frameworks for unsupervised anomaly detection across heterogeneous domains, created benchmarks like Exathlon for evaluating explainable anomaly detection systems, and advanced human-in-the-loop approaches for interactive database exploration. Her work consistently bridges theoretical foundations with practical implementations in distributed systems.
Selected Awards:
- ERC Consolidator Award (2017-2023) for "Charting a New Horizon of Big and Fast Data Analysis through Integrated Algorithm Design"
- CRA-W Borg Early Career Award (2013)
- NSF CAREER Award (2008)
- IBM Innovation Award on Scalable Data Analytics (2010)
Professor Diao actively mentors PhD and Master's students, with former students now holding positions at top technology companies including Google, Facebook, Amazon, Netflix, and Huawei. Her research is supported by diverse funding sources including the European Research Council, National Science Foundation, ANR, and industry partners like Google, IBM, and Alibaba. She serves as PC Co-Chair of PVLDB 2025-2026 and has delivered keynotes at major industry events including Amazon Machine Learning Workshop (2024), SWIFT AI Forum (2023), and Berlin Institute for the Foundations of Learning and Data (2022).
Her CEDAR research team at Inria/LIX develops cutting-edge technologies for big data analytics, with current projects focusing on foundation models for big data, explainable AI for anomaly detection, and genomic data analysis at scale. The team maintains strong collaborations with industry partners including Alibaba Cloud, where joint work has led to significant publications at top database conferences.
