DataEd 2024 Organization

Advisory Board Members

Program Committee

  • Efthimia Aivaloglou, TU Delft
  • Abdussalam Alawini, University of Illinois at Urbana-Champaign
  • Susan Davidson, University of Pennsylvania
  • Karen Davis, Miami University
  • Lorena Etcheverry, Universidad de la República
  • Alan Fekete, University of Sydney
  • George Fletcher, Eindhoven University of Technology
  • Paul Groth, University of Amsterdam
  • Lukas Höper, Paderborn University
  • HV Jagadish, University of Michigan
  • Oscar Karnalim, Maranatha Christian University
  • Hui Li, Xidian University
  • Cheng Long, Nanyang Technological University
  • George Obaido, University of California Berkeley
  • Andrew Petersen, University of Toronto, Mississauga
  • Rachel Pottinger, University of British Columbia
  • Alexandro Poulovasillis, Birkbeck University of London
  • Stefanie Scherzinger, University of Passau
  • Toni Taipalus, University of Jyväskylä
  • Thomas Zeume, Ruhr University Bochum

Workshop Chairs

Daphne Miedema

Eindhoven University of Technology,
the Netherlands

Daphne Miedema (MSc, Eindhoven University of Technology) is a doctoral candidate at TU/e in the Database Group. She obtained a double MSc in Computer Science and Engineering and Human-Technology Interaction in 2019. Her research is located on the intersection of Databases and HTI, applied to education. Daphne's current research interests include query language education, visual query representations and (mis)conceptions.

Sourav Bhowmick

Nanyang Technological University,

Sourav Bhowmick (PhD, Nanyang Technological University) is an Associate Professor in the School of Computer Science and Engineering (SCSE). His core research expertise is in data management, human-data interaction, and data analytics. Sourav is serving as a member of the SIGMOD Executive Committee, a regular member of the PVLDB advisory board, and a co-lead in the committee for Diversity and Inclusion in Database Conference Venues.

Michael Liut

University of Toronto Mississauga,

Michael Liut (PhD, McMaster University) is an Assistant Professor in the teaching stream at the University of Toronto Mississauga. With a primary research emphasis on applied AI/ML in education, Michael delves into the intricate realms of educational technologies, data systems, algorithmic design, and student behaviour. His passion lies in harnessing these insights to craft adaptive experimentation and innovative behavioural interventions. At the heart of his work, Michael strives to refine and enhance the educational journey.