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SUMMARY:Exploiting Heterogeneity in Modern Data Systems
DTSTART:20251216T130000
DTEND:20251216T140000
DTSTAMP:20260404T084853Z
UID:dcfbfa44ed58682fefbdb831c4f6ec389f14aa9ae61f80621b134e5a
CATEGORIES:Conferences - Seminars
DESCRIPTION:Eleni Tzirita Zacharatou\, W2 Assistant Professor at the Hass
 o Plattner Institute (HPI) and the University of Potsdam\nModern data syst
 ems increasingly operate in heterogeneous environments—spanning edge dev
 ices to cloud servers\, leveraging diverse compute architectures\, integra
 ting multiple data platforms\, and processing multi-modal data. Traditiona
 l approaches that assume homogeneity limit both system performance and use
 r accessibility. \nIn this talk\, I will present work across two research
  threads that explore how to intelligently exploit different dimensions of
  heterogeneity to make data processing more efficient and user-friendly. F
 irst\, I will introduce NEMO (VLDB 2024)\, a scalable approach for placing
  decomposable aggregation operators in geo-distributed stream processing s
 ystems. NEMO efficiently handles millions of heterogeneous nodes across ed
 ge-fog-cloud topologies\, achieving up to 6x lower latency while preventin
 g node overload. Second\, I will discuss ongoing work in spatial analytics
 \, which addresses heterogeneity across compute resources\, platforms\, an
 d data modalities. Together\, these efforts demonstrate that embracing het
 erogeneity in modern data systems can lead to significant improvements in 
 performance and usability.\n\nBio:\nEleni Tzirita Zacharatou is a W2 Assis
 tant Professor at the Hasso Plattner Institute (HPI) and the University of
  Potsdam\, where she leads the Spatial Analytics and Large-Scale Data Proc
 essing research group. She has also been a Junior Fellow at the Berlin Ins
 titute for the Foundations of Learning and Data (BIFOLD) since 2021. Prior
  to joining HPI in 2025\, she was an Assistant Professor at the IT Univers
 ity of Copenhagen (2022-2025) and a Postdoctoral Researcher at TU Berlin (
 2019-2022). She earned her PhD from EPFL in 2019\, under the supervision o
 f Prof. Anastasia Ailamaki\, and holds a Diploma M. Eng. in Electrical and
  Computer Engineering from the National Technical University of Athens (NT
 UA). Her research focuses on improving the efficiency of data analysis and
  supporting data-driven decision-making\, particularly for spatial data\, 
 by developing data management tools that are aware of resource constraints
 \, system and hardware capabilities\, and data modalities.  
LOCATION:BC 410 https://plan.epfl.ch/?room==BC%20410
STATUS:CONFIRMED
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