Mirek Riedewald
Research Interests
- Databases
- Data mining
Education
- PhD in Computer Science, University of California, Santa Barbara
- BS in Computer Science, Saarland University – Germany
Biography
Mirek Riedewald is a professor at the Khoury College of Computer Sciences. His research interests are in databases and data science, with an emphasis on designing novel data management and analysis techniques that scale in size, velocity, and dimensionality of data. Riedewald has collaborated successfully with scientists from various domains, including ornithology, physics, mechanical and aerospace engineering, and astronomy. This work resulted in novel approaches for data warehousing, data stream processing, prediction, and parallel data processing using computer clusters.
He is now focusing on distributed big-data analytics, ranked enumeration, exploratory analysis of massive observational datasets, query visualization, and techniques for automated reconstruction of structure and dynamics of neural circuits, a crucial step toward understanding the functionality of the brain.
Prior to joining Northeastern University, Riedewald was a research associate at Cornell University. He also held visiting research positions at Microsoft Research in Redmond, Washington and at the Max Planck Institute for Informatics in Germany. His work has been published in the premier peer-reviewed data management research venues and in domain-science journals. He has received awards for Best Student Paper at ECML’07, Best Poster at ICDE’14, Best Paper at EDBT’21, as well as “best-of-conference” mentions at ICDE’14, DaWaK’17, and ICDE’19.
Research Interests
- Databases
- Data mining
Education
- PhD in Computer Science, University of California, Santa Barbara
- BS in Computer Science, Saarland University – Germany
Biography
Mirek Riedewald is a professor at the Khoury College of Computer Sciences. His research interests are in databases and data science, with an emphasis on designing novel data management and analysis techniques that scale in size, velocity, and dimensionality of data. Riedewald has collaborated successfully with scientists from various domains, including ornithology, physics, mechanical and aerospace engineering, and astronomy. This work resulted in novel approaches for data warehousing, data stream processing, prediction, and parallel data processing using computer clusters.
He is now focusing on distributed big-data analytics, ranked enumeration, exploratory analysis of massive observational datasets, query visualization, and techniques for automated reconstruction of structure and dynamics of neural circuits, a crucial step toward understanding the functionality of the brain.
Prior to joining Northeastern University, Riedewald was a research associate at Cornell University. He also held visiting research positions at Microsoft Research in Redmond, Washington and at the Max Planck Institute for Informatics in Germany. His work has been published in the premier peer-reviewed data management research venues and in domain-science journals. He has received awards for Best Student Paper at ECML’07, Best Poster at ICDE’14, Best Paper at EDBT’21, as well as “best-of-conference” mentions at ICDE’14, DaWaK’17, and ICDE’19.