Abdullah Al-Mamun

I am a Ph.D. candidate at the Department of Computer Science, Purdue University. My advisor is Professor Walid G. Aref. Moreover, I had research collaboration with Professor Jianguo Wang. My research interest is in the area of Database Systems + Machine Learning (ML): “ML for Systems” and “Systems for ML”.

Contact: mamuna[at]purdue[dot]edu

Research

My current research is in the area of “ML for Systems”, particularly focusing on Learned Multi- and High-dimensional Index Structures. Previously, I was involved in a research project on In-Memory Graph-Relational Data Systems. Additionally, I conducted research on Anomaly Detection from sensor data streams during my graduate studies (advised by Professor Antonina Kolokolova) at Memorial University of Newfoundland, Canada.

Quick Links: Google Scholar | LinkedIn | ORCID

Publications

Ph.D. Thesis-related

• Abdullah Al-Mamun, Hao Wu, Qiyang He, Jianguo Wang, and Walid G. Aref. “A survey of learned indexes for the multi-dimensional space.” ACM Computing Surveys (CSUR, 2025).

• Abdullah Al-Mamun, Jianguo Wang, and Walid G. Aref. “Learned Indexes From the One-dimensional to the Multi-dimensional Spaces: Challenges, Techniques, and Opportunities.” In Companion of the 2025 International Conference on Management of Data (SIGMOD), pp. 788-796. 2025.

• Abdullah Al-Mamun, Ch Md Rakin Haider, and Walid G. Aref. “Query Processing Tradeoffs over an ML-Enhanced R-tree.” (To appear in the proceedings of the GeoAI@SIGSPATIAL, 2025).

• Abdullah Al-Mamun, Haider, Ch Md Rakin, Jianguo Wang, and Walid G. Aref. “The “AI+ R”-tree: An Instance-optimized R-tree.” In 2022 23rd IEEE International Conference on Mobile Data Management (MDM), pp. 9-18. IEEE, 2022.

• Abdullah Al-Mamun, Hao Wu, and Walid G. Aref. “A tutorial on learned multi-dimensional indexes.” In Proceedings of the 28th International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pp. 1-4. 2020.

Others

• Abdullah Al-Mamun, Antonina Kolokolova, Dan Brake. “Detecting Contextual Anomalies from Time-Changing Sensor Data Streams.” In Proceedings of the Doctoral Consortium of the 25th ECML PKDD, p.13, 2015.

Education

• Ph.D. in Computer Science, Purdue University, USA (expected graduation year: 2026)

• M.Sc. in Computer Science, Memorial University of Newfoundland, Canada (2016)

• B.Sc. in Computer Science, Islamic University of Technology, Bangladesh (2009)

Teaching

Instructor

CS348: Information Systems (Spring 2023)

• I became an instructor through a highly selective teaching fellowship program that offers distinguished TAs the opportunity to teach an undergraduate course.

Graduate Teaching Assistant

• CS 448: Introduction to Relational Database Systems Implementation

• CS 348: Information Systems

Awards and Honors

• Summer 2025: Microsoft Fellowship (full) to attend the EDBT'25 Summer School on AI & Data Management.

• Fall 2022-Spring 2023: Graduate Teaching Fellow, Department of Computer Science, Purdue University.

• Spring 2023: Graduate Teaching Award, Department of Computer Science, Purdue University.

• Summer 2018: Summer Research Grant, Purdue University.

• 2015: Fellow of the School of Graduate Studies, Memorial University of Newfoundland.