 | Djellel Difallah Assistant Professor of Computer Science NYU Abu Dhabi |
Bio
Djellel Difallah received his Ph.D. from the University of Fribourg (Switzerland). His research addresses the challenge of developing effective methods to reason over large, incomplete, and heterogeneous knowledge bases, aiming to enhance knowledge completeness and discovery for informed decision making. He focuses on knowledge graph completion, graph reasoning, and multimodal data integration employing diverse machine learning and human computation techniques. He was a Research Scientist at the Wikimedia Foundation and a Data Science Fellow at NYU CDS. Previously, Djellel was a Fulbright Fellow, Microsoft Research Intern, and Google Summer of Code participant. He is currently an Assistant Professor at NYU Abu Dhabi.
More details can be found on my research statement for more information: Research Statement
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Research Interests
My research addresses the challenge of developing effective methods to reason over large, incomplete, and heterogeneous knowledge bases, aiming to enhance knowledge completeness and discovery to support informed decision-making.
In an era of information overload, extracting reliable insights from noisy and fragmented knowledge sources is increasingly difficult. Navigating complex knowledge ecosystems requires the development of new methods to identify information gaps, integrate diverse data sources and modalities, and interpret the reasoning of AI models when applied to these knowledge bases. My approach emphasizes creating interpretable systems that adapt to evolving domain knowledge and integrate seamlessly into human-centric workflows.
Specifically, my research focuses on the following technical challenges:
OLTPBenchmark is a multi-threaded load generator. The framework is designed to be able to produce variable rate, variable mixture load against any JDBC-enabled relational database. The framework also provides data collection features, e.g., per-transaction-type latency and throughput logs.
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Teaching
My teaching statement is available here