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Essam Mansour |
I am an associate professor in the Department of Computer Science and Software Engineering at Concordia University in Montreal and the head of the Cognitive Data Science (CoDS) lab. My research program focuses on developing systems for Linked Data Science on federated and big datasets. My research interests are in the broad areas of knowledge graphs, graph neural networks, large language models, parallel/distributed systems, and data management.
Note: I do not have openings for Master students.
- Hussein Abdallah
- Reham Omar
- Mossad Helali
- Waleed Afandi
- Saeed Fathollahzadeh
- Ahmed Aly (with Amr Youssef)
- Niki Monjazeb
- Omij Mangukiya
- Ishika Dhall (Graduated in 2023, First Employment: AI Scientist at National Bank of Canada)
- Shubham Vashisth (Graduated in 2023, First Employment: PhD Student at McGill)
- Ahmed Helal (Graduated in 2021, First Employment: Software Engineer - Big Data Platform at Huawei)
- Philippe Carrier (Graduated in 2023, First Employment: Software Engineer - at Amazon)
- Yasaman Sabbagh (Graduated in 2022, First Employment: PhD student at McGill)
- A Linked Data Science Knowledge Graph Platform
- A GNN- and LLM- Enabled Knowledge Graph Platform
- An LLM-based Chatbot Platform for Knowledge Graphs
- Automating Data Preparation and Feature Discovery Pipelines
- A Cyber Threats Hunting Platform Powered by Graph Neural Networks
A Program Committee member of:
- SIGMOD 2025, (SIGMOD 2023 Meta-reviewer)
- VLDB 2025 VLDB 2024, VLDB 2023, VLDB 2021, VLDB 2020, VLDB 2019, VLDB 2018, VLDB 2017
- ICDE 2023, ICDE 2016
- The Web Conference 2023
- EDBT 2023
- ISWC 2022, ISWC 2021
- SIGMOD 2021, SIGMOD 2016
- KDD 2021
I also regularly review for a number of international journals, including:
- ACM Transactions on Database Systems (TODS)
- The International Journal on Very Large Data Bases (VLDB Journal)
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- IEEE Transactions on Parallel and Distributed Systems (TPDS)
- IEEE Transactions on Cloud Computing (TCCSI)
- IEEE Transactions on Big Data (TBD)