Md Ashraful Islam
PhD Student · UMass Amherst · Machine Learning Systems
I am a PhD student in the Computer Science Department at UMass Amherst, advised by Prof. Marco Serafini. My research focuses on Temporal Graph Neural Networks, Relational Deep Learning, and efficient ML systems (C++/CUDA, PyTorch, PyG/DGL) for large-scale dynamic graphs.
Research Interests
- Temporal Graph Learning
- Relational Deep Learning
- High-performance training systems (CUDA kernels, PyBind11, DGL/PyG)
- Anomaly Detection using Provenance Graph
- Data Mining (Graph, Sequence)
News
- 2024 Paper accepted in Applied Intelligence. Graph-based substructure pattern mining with edge-weight
- 2023 Started PhD at UMass Amherst on ML System
- 2023 Paper accepted in Applied Intelligence. UGMINE: utility-based graph mining
- 2022 Promoted to Assistant Professor (University of Dhaka, Dept. of CSE)
- 2022 Paper accepted in Applied Intelligence. Weighted frequent sequential pattern mining
- 2019 Started new position as Lecturer (University of Dhaka, Dept. of CSE)
- 2018 Paper accepted in PAKDD. WFSM-MaxPWS: An Efficient Approach for Mining Weighted Frequent Subgraphs from Edge-Weighted Graph Databases
- 2018 Awarded Dean's Award & Prof. Dr. Lutfar Rahman Award.
Software
SDTGNN
Open-source framework for scalable temporal GNN training with streaming samplers, chunk caches, and custom CUDA kernels.
NeutronStream (adaptation)
High-throughput temporal neighbor sampler with chunk-based caches and multi-pass updates.
Teaching
- CS 589 – Machine Learning, TA, UMass Amherst (Fall 2025)
- CS 220 – Programming Methodologies, TA, UMass Amherst (Fall 2023, Spring 2024)
- CS 3203 – Algorithms II, Instructor, University of Dhaka (2021, 2022)
Service & Talks
Service
- Reviewer: MSCC (2025), STI (2020, 2021, 2022)
- Undergraduate Research Mentor (Winter 2024)
- ERSP PhD Mentor (Fall 2023, Spring 2024)
Talks
- "Challenges of Scalable Memory-based Temporal Graph Learning" — UMass ML Systems Reading Group, 2024
- "Metegral: Unlocking True Potential of Memory-based Temporal Graph Learning" — Reading Group, 2024
Contact
Email: mdashrafulis@umass.edu
Office: LGRC A249, University of Massachusetts Amherst
Social: GitHub · Google Scholar · Semantic Scholar · ORCID