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Portrait of Md Ashraful Islam

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

More News →

Software

PRISM

Open-source framework for staleness-free and scalable temporal GNN training. Features streaming samplers, chunk-based memory graphs, and optimized CUDA kernels for high GPU utilization.

Repo Docs CUDA PyG Temporal GNN

WFSPM

Implementation of Weighted Frequent Sequential Pattern Mining — a framework for mining weighted sequential patterns efficiently using pruning and weighting strategies.

Repo Paper Sequence Mining Python

MaxPWSCan

Implementation of Graph-based Substructure Pattern Mining with Edge-Weight — a graph mining algorithm that discovers weighted frequent substructures using MaxPWS pruning.

Repo Paper Graph Mining Python

STFT-GradTTS

A diffusion-based Bangla text-to-speech (TTS) system featuring a Stochastic Duration Predictor and a multi-stream iSTFT decoder for high-quality waveform generation.

Repo Diffusion TTS Speech

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: 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
  • "PRISM: 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