Rihan Hai

Rihan Hai

Assistant professor

Biography

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.

Opening:

On the topic of Quantum Data Management, we currently have available openings for PhD, MSc thesis, and research software engineer. To apply, please send me an email including your CV, academic transcripts, and any other relevant documents.

PC: VLDB, ICDE, EDBT, WebConf

Journal reviewer: TKDE, VLDBJ, SIGMOD Reocrd, Information Systems, JMLR, TPDS

Grants

NWO VENI Grant 2022. Project: Understanding Implicit Dataset Relationships for Machine Learning. Awarded. (2024-)

ExtremeXP – EXPerimentation driven and user eXPerience-oriented analytics for eXtremely Precise outcomes and decisions. HORIZON-CL4-2022-DATA-01. Awarded. (01 Jan 2023-)

Award

EDBT 2023 Best Demonstration Award

Research Interests

AI in data lakes

Multimodal data & GPU acceleration

Federated Learning

Data privacy and security

Quantum Data Management

Data Management for Quantum Computing and Quantum Internet

Recent Posts

Join our tutorial on Quantum Data Management
Join our tutorial at ICDE 2024 Tutorial 5: Quantum data management: from theory to opportunities Full paper on Arxiv Abstract: Quantum computing has emerged as a transformative tool for future data management.
Last updated on Mar 18, 2024 2 min read
Full design of our model lake Amalur accepted at TKDE 2024
Extended from our vision paper at ICDE 2024, the full version of Amalur is now available at TKDE! Amalur: The Convergence of Data Integration and Machine Learning By Ziyu Li, Wenbo Sun, Danning Zhan, Yan Kang, Lydia Chen, Alessandro Bozzon, and Rihan Hai
Last updated on Mar 18, 2024 1 min read
Our paper on transfer learning accepted at ICDE2024
Model Selection with Model Zoo via Graph Learning By Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla, Alessandro Bozzon, Rihan Hai Abstract—Pre-trained deep learning (DL) models are increasingly accessible in public repositories, i.
Last updated on Mar 18, 2024 1 min read
Check out our data lake survey -- TKDE poster
Join us at the TKDE poster session at ICDE24 Data Lakes: A Survey of Functions and Systems (Extended abstract) Rihan Hai (TU Delft); Christos Koutras (TU Delft); Christoph Quix (Hochule Niederrhein University of Applied Sciences); Matthias Jarke (RWTH Aachen University) Full paper
Last updated on Mar 18, 2024 2 min read
Our paper on Federated Learning accepted at ICDE2024
SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models by Aditya Shankar, Hans Brouwer, Rihan Hai, Lydia Chen Abstract—Synthetic tabular data is crucial for sharing and augmenting data across silos, especially for enterprises with proprietary data.
Last updated on Mar 18, 2024 1 min read
See all posts

Projects

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All Deep Learning Other
Amalur: Next-generation Data Integration in Data Lakes
Support ML/DL models in heterogeneous data lakes

Recent & Upcoming Talks

Presentation at ICDE'23
The data needed for machine learning (ML) model training, can reside in different separate sites often termed data silos. For …
Apr 6, 2023 11:00 AM — 10:00 PM Anaheim, California, USA at the Marriott Anaheim
Data Integration in Data Lakes
Although big data is being discussed for some years, it still has many research challenges, such as the variety of data. The diversity …
Jun 27, 2022 2:53 PM — Jun 28, 2022 10:00 PM Basel, Switzerland (HYBRID EVENT)
CIDR2022 short presentation on Amalur

Data science workflows require extracting, preparing and integrating data from multiple data sources. Due to the lack of proper tooling …
Jan 11, 2022 3:30 AM — 4:30 AM ZOOM

Recent Publications

Quickly discover relevant content by filtering publications.
Andra Ionescu, Rihan Hai, Marios Fragkoulis, Asterios Katsifodimos (2023). Join Path Based Data Augmentation for Decision Trees . DBML'22 workshop.

Rihan Hai, Christos Koutras, Andra Ionescu, Ziyu Li, Wenbo Sun, Jessie van Schijndel, Yan Kang, Asterios Katsifodimos (2023). Amalur: Data Integration Meets Machine Learning.

Wenbo Sun, Asterios Katsifodimos, Rihan Hai (2023). An Empirical Performance Comparison between Matrix Multiplication Join and Hash Join on GPUs. HardBD & Active'23 @ICDE.

Ziyu Li, Rihan Hai, Alessandro Bozzon, Asterios Katsifodimos (2023). Metadata Representations for Queryable ML Model Zoos. Workshop on Benchmarking Data for Data-Centric AI (DataPerf) @ICML 2022.

Rihan Hai, Christos Koutras, Andra Ionescu, Asterios Katsifodimos (2021). Amalur: Next-generation Data Integration in Data Lakes. CIDR'22, Abstract.

Popular Topics

Data integration Data lake Deep learning Machine learning Workshop

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