I am an assistant professor at Web Information Systems (WIS) group of TU Delft. Before joining TU Delft, I received my Ph.D. degree with “summa cum laude” from Information Systems & Databases group of RWTH Aachen University, Germany. I received my BEng and MEng from Tsinghua University, China. My research focuses on data lakes, data management for machine learning, and quantum data management.

I am a postdoctoral researcher in the research group of Web Information Systems (WIS), TU Delft. My PhD study focuses on a Decentralized Virtual Research Environment (D-VRE) solution, which can bridge the gap between a Jupyter-based virtual research environment and a decentralized research ecosystem via leveraging workflow and blockchain technology to enable decentralized collaborations on secure data sharing, computing resource sharing, and collaborative learning. I am passionate about collaborative systems that can support decentralized artificial intelligence and science. I am also interested in real-life applications regarding distributed data processing, federated machine learning, and FAIRification process.

Wenbo Sun is a PhD candidate at WIS team. Prior to joining TUDelft, he worked as a software engineer, then received his master degree in computational science at University of Amsterdam. His research focuses on database system, machine learning system and performance engineering.

PhD candidate working on privacy preservation in machine learning on tabular data in the data lake setting.

I am a PhD candidate at Distributed Systems and Web Information Systems. My supervisors are Dr. Lydia Y. Chen, Dr. Rihan Hai, and Dr. Arie van Deursen. My research interests are distributed learning, privacy-preserving learning, and federated learning.

I am currently pursuing my PhD in the field of Quantum Data Management at TU Delft. My research is centered around the development of novel methods to classically simulate quantum computing systems. This work is pivotal in driving forward technological advancements in quantum computing, enabling more efficient and scalable quantum simulations that can contribute to both theoretical and practical quantum computing research.

I was a PhD student and Postdoc at the Web Information Systems group at Delft University of Technology. My research lies at the intersection of Machine Learning and data analysis. In particular, my reserach investigates how to apply metadata of different artifacts (e.g., model, data, hardware settings) to improve the effectiveness and efficiency of machine learning workflows. My personal website can be found here