Samreen T. Mahmud

dblp:359/6194 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0004-6136-7364ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 44% Medical and health informatics · 44% Computational science and engineering · 13%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
GPUs and heterogeneous computing · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems bioinformatics
biological simulation
0.712023
Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts · SC 2023
Medical and health informatics › biomedical modeling
blood flow simulation
0.712023
Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts · SC 2023
GPUs and heterogeneous computing
CPU-GPU heterogeneous computing
0.712023
Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts · SC 2023
Computational science and engineering › multiphysics simulation
fluid-structure interaction
0.212023
Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts · SC 2023

Methods — techniques the papers use, named apart from their topics

hybrid CPU-GPU computation · 1.3adaptive physics refinement · 1.3
YearPublicationVenuePosition
2023 Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts
abstract
Simulations of cancer cell transport require accurately modeling mm-scale and longer trajectories through a circulatory system containing trillions of deformable red blood cells, whose intercellular interactions require submicron fidelity. Using a hybrid CPU-GPU approach, we extend the advanced physics refinement (APR) method to couple a finely-resolved region of explicitly-modeled red blood cells to a coarsely-resolved bulk fluid domain. We further develop algorithms that: capture the dynamics at the interface of differing viscosities, maintain hematocrit within the cell-filled volume, and move the finely-resolved region and encapsulated cells while tracking an individual cancer cell. Comparison to a fully-resolved fluid-structure interaction model is presented for verification. Finally, we use the advanced APR method to simulate cancer cell transport over a mm-scale distance while maintaining a local region of RBCs, using a fraction of the computational power required to run a fully-resolved model.
Sayan Roychowdhury, Samreen T. Mahmud, Aristotle X. Martin, Peter Balogh, Daniel F. Puleri, John Gounley, Erik W. Draeger, Amanda Randles
SC2