Biography and Research

Hakan Ferhatosmanoglu is a Professor and Deputy Head of Computer Science at the University of Warwick, and a Turing Fellow at ATI, UK's national institute for data science and AI. His research interest is in building software systems for scalable data analytics. This involves integrating multiple sources of information and protecting the privacy of data subjects. An example application is learning aggregate mobility patterns over multiple sources of spatio-temporal data. He has published in leading venues of data systems and analytics research and served in the technical committees of VLDB, KDD, SIGMOD, ICDE, ICDM, ECML/PKDD, CIKM, SIGIR.

Dr. Ferhatosmanoglu received his PhD in CS from University of California, Santa Barbara in 2001. Before joining Warwick, he was a tenured professor at Ohio State U. (OSU), Bilkent U., visited Max Planck Institute (MPI) for Informatics and MPI for Software Systems with a research award by Humboldt Foundation. His research has been supported by government agencies including the US Department of Energy and US National Science Foundation, and companies including Pfizer and IBM. He has been the Principal Investigator of more than 15 externally funded grants. He has closely worked with industrial partners in developing commercial data analytics and machine learning solutions. He supervised more than 40 graduate students, including 10 PhDs to completion. Advisees moved to work in faculty positions at major research universities, and companies including Google, Amazon, Intel, Microsoft, Teradata, Oracle.

He received several Research Career Awards, from the US Department of Energy, US National Science Foundation, Turkish Academy of Sciences, and Alexander von Humboldt Foundation in Germany. He received an IBM Faculty Award, a Lumley Research Award for outstanding research and a large interdisciplinary research award at OSU. He served as the Recruitment Coordinator and Information Systems Option Coordinator at OSU CSE department. He is an editorial board member of Distributed and Parallel Databases Journal, and a member of the Board of Faculty of Science, Engineering, and Medicine at the University of Warwick.

Program/Organization Committee

VLDB 2019, ICDE 2019, SIGMOD 2018, VLDB 2018, CIKM 2018, VLDB 2017, SIGIR 2017, CIKM 2017, SIGIR 2016, SIGMOD 2016, VLDB 2016, ECML/PKDD 2015, ECML/PKDD 2014, VLDB 2014, VLDB 2013, VLDB 2012 (Co-Chair, Workshops Program), VLDB 2012 (PC), SIGMOD 2011, SIGMOD 2010, ICDE 2011, ICDM 2011, ICDM 2010, ACM SIGIHI 2010, ACM SIGSPATIAL 2010, SIGMOD 2010..

Research Awards

DOE Career Award 2003, U.S. Dept. of Energy
NSF Career Award 2006, U.S. National Science Foundation
Alexander von Humboldt Foundation, George Forster Award, Germany, 2016
Large Interdisciplinary Research Award, OSU, 2004
Lumley Research Accomplishment Award, OSU, 2007
IBM Faculty Award, 2010
Career Award (GEBIP), Turkish Academy of Sciences, 2012

Recent Publications

Spatial-temporal Data Management

• Privacy-Preserving Aggregate Queries for Optimal Location Selection, IEEE Trans. on Dependable and Secure Computing (to appear)
• Fair Task Allocation in Crowdsourced Delivery, IEEE Trans. on Services Computing (to appear)
• Diverse Relevance Feedback for Time Series with Autoencoder Based Summarizations, IEEE Trans. on Knowledge and Data Engineering (to appear)
• Spatio-Temporal Linkage over Location-Enhanced Services, IEEE Trans. on Mobile Computing 2018.
• Multi-vehicle Route Planning for Efficient Urban Freight Transport, IEEE IS (Intelligent Systems), 2018.
• VISIR: Visual and Semantic Image Label Refinement, ACM WSDM (Web Search and Data Mining) 2018.
• Predicting Optimal Facility Location Without Customer Locations, ACM KDD (Knowledge Discovery and Data Mining) 2017.
• Understanding and Predicting Trends in Urban Freight Transport, IEEE Mobile Data Management 2017.
• Location Recommendations for New Businesses using Check-in Data, IEEE SSTDM 2016.
• Generating Time-Varying Road Network Data Using Sparse Trajectories, IEEE SSTDM 2016. temporal road graph & code
• LineKing: Coffee Shop Wait-Time Monitoring Using Smartphones, IEEE Trans. on Mobile Computing 2015.
• Scaling Forecasting Algorithms using Clustered Modeling, VLDB J. 2015 (& @VLDB '14).
• Diversity based Relevance Feedback for Time Series Search, VLDB 2014.

Scalable Systems for Data Analytics

• Cascade-aware Partitioning of Large Graph Databases, VLDB J. (to appear)
• Topic-Based Influence Computation in Social Networks under Resource Constraints, IEEE Trans. on Services Computing (to appear)
• Distributed Block Formation and Layout for Disk-based Management of Large-Scale Graphs, Distributed and Parallel Databases 2017.
• ALACA: A Platform for Dynamic Alarm Collection and Alert Notification in Network Management Systems, Network Management 2017.
• Learning to Un-rank: Quantifying Search Exposure for Users in Online Communities, ACM CIKM (Information and Knowlege Management) 2017.
• S3-TM: Scalable Streaming Short Text Matching, VLDB J. 2015 (& @VLDB '16).
• Aggregate Profile Clustering for Streaming Analytics, Computer J. 2015.
• Div-BLAST: Diversification of Sequence Search Results, PLOS ONE 2014. try online
• Temporal Workload-Aware Replicated Partitioning for Social Networks, IEEE Trans. on Knowledge and Data Engineering 2014.