Scholar
John Paparrizos
Google Scholar ID: CmxltbUAAAAJ
The Ohio State University, USA & Aristotle University of Thessaloniki, Greece
Citations & Impact
Citations
3,161
H-index
26
i10-index
40
Publications
20
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- 2019 ACM SIGKDD Doctoral Dissertation Award
- NetApp Faculty Award
- Inaugural ACM SIGMOD Research Highlight Award
- 2023 IEEE TCDE Rising Star Award for breakthroughs in time-series data management and contributions to adaptive methodologies for data-intensive and ML applications
- 2025 ACM SIGMOD Test-of-Time Award for advancing time-series clustering via a shape-based approach with high accuracy, efficiency, and broad applicability
- Research featured in major media including The New York Times (front page), Washington Post, Forbes, Guardian, Fortune, and MIT Technology Review
- Open-source tools downloaded over 100,000 times and integrated into widely-used third-party libraries
- Methods adopted in curricula at Brown, Columbia, Purdue, and University of Chicago
- Techniques applied across disciplines (CS, biology, medicine, social science, neuroscience) and by Fortune 500 companies (e.g., Exelon, Nokia) and the European Space Agency
- Active service on program/organizing committees of top conferences: ACM SIGMOD, VLDB, IEEE ICDE, ACM SIGKDD, IEEE ICDM, ICML, NeurIPS, AAAI, IJCAI
- Lifetime Member of ACM and AAAI; Member of IEEE and ELLIS
Background
- Assistant Professor of Computer Science and Engineering at The Ohio State University
- Director of The DATUM Lab (Data Analytics, Understanding, Mining, and Management Lab)
- Assistant Professor (Adjunct) at the School of Informatics, Aristotle University of Thessaloniki, Greece
- Research focuses on foundational technologies for data-intensive and machine learning applications
- Expertise spans databases, data science, machine learning, and artificial intelligence
- Develops adaptive, effective, and scalable solutions for analyzing structured and unstructured data, including relational, time-series, multimedia, text, graph, web, and IoT data
