Marco Serafini

Marco Serafini

University of Massachusetts Amherst

H-index: 23

North America-United States

About Marco Serafini

Marco Serafini, With an exceptional h-index of 23 and a recent h-index of 18 (since 2020), a distinguished researcher at University of Massachusetts Amherst, specializes in the field of Systems for ML, Data Management Systems, Distributed Systems.

His recent articles reflect a diverse array of research interests and contributions to the field:

GMorph: Accelerating Multi-DNN Inference via Model Fusion

Enhancing Computation Pushdown for Cloud OLAP Databases

GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs

Gsplit: Scaling graph neural network training on large graphs via split-parallelism

Tuning the Tail Latency of Distributed Queries Using Replication

Scalable Graph Neural Network Training: The Case for Sampling

Accelerating graph sampling for graph machine learning using GPUs

Flexpushdowndb: Hybrid pushdown and caching in a cloud dbms

Marco Serafini Information

University

Position

Assistant professor at

Citations(all)

2353

Citations(since 2020)

1295

Cited By

1560

hIndex(all)

23

hIndex(since 2020)

18

i10Index(all)

33

i10Index(since 2020)

19

Email

University Profile Page

University of Massachusetts Amherst

Google Scholar

View Google Scholar Profile

Marco Serafini Skills & Research Interests

Systems for ML

Data Management Systems

Distributed Systems

Top articles of Marco Serafini

Title

Journal

Author(s)

Publication Date

GMorph: Accelerating Multi-DNN Inference via Model Fusion

Qizheng Yang

Tianyi Yang

Mingcan Xiang

Lijun Zhang

Haoliang Wang

...

2024/4/22

Enhancing Computation Pushdown for Cloud OLAP Databases

arXiv preprint arXiv:2312.15405

Yifei Yang

Xiangyao Yu

Marco Serafini

Ashraf Aboulnaga

Michael Stonebraker

2023/12/24

GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs

Juelin Liu

Sandeep Polisetty

Hui Guan

Marco Serafini

2023/10/21

Gsplit: Scaling graph neural network training on large graphs via split-parallelism

arXiv preprint arXiv:2303.13775

Sandeep Polisetty

Juelin Liu

Kobi Falus

Yi Ren Fung

Seung-Hwan Lim

...

2023/3/24

Tuning the Tail Latency of Distributed Queries Using Replication

arXiv preprint arXiv:2212.10387

Nathan Ng

Hung Le

Marco Serafini

2022/12/20

Scalable Graph Neural Network Training: The Case for Sampling

ACM SIGOPS Operating Systems Review

Marco Serafini

Hui Guan

2021/6/4

Accelerating graph sampling for graph machine learning using GPUs

Abhinav Jangda

Sandeep Polisetty

Arjun Guha

Marco Serafini

2021/4/21

Flexpushdowndb: Hybrid pushdown and caching in a cloud dbms

Proceedings of the VLDB Endowment

Yifei Yang

Matt Youill

Matthew Woicik

Yizhou Liu

Xiangyao Yu

...

2021

Do the best cloud configurations grow on trees? an experimental evaluation of black box algorithms for optimizing cloud workloads

Proceedings of the VLDB Endowment

Muhammad Bilal

Marco Serafini

Marco Canini

Rodrigo Rodrigues

2020/7/1

PushdownDB: Accelerating a DBMS using S3 computation

Xiangyao Yu

Matt Youill

Matthew Woicik

Abdurrahman Ghanem

Marco Serafini

...

2020/4/20

Aion: Better late than never in event-time streams

arXiv preprint arXiv:2003.03604

Sergio Esteves

Gianmarco De Francisci Morales

Rodrigo Rodrigues

Marco Serafini

Luís Veiga

2020/3/7

See List of Professors in Marco Serafini University(University of Massachusetts Amherst)

Co-Authors

H-index: 81
Mohammed J. Zaki

Mohammed J. Zaki

Rensselaer Polytechnic Institute

H-index: 40
Neeraj Suri

Neeraj Suri

Lancaster University

H-index: 38
Andy Pavlo

Andy Pavlo

Carnegie Mellon University

H-index: 35
Benjamin Reed

Benjamin Reed

San José State University

H-index: 28
Aaron J Elmore

Aaron J Elmore

University of Chicago

H-index: 24
Xiangyao Yu

Xiangyao Yu

University of Wisconsin-Madison

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