TPDS Editorial Board


Manish Parashar – Rutgers University

Associate Editors-in-Chief

Pavan Balaji – Argonne National Laboratory. Programming models, systems software, machine learning, big data

Xian-He Sun – Illinois Institute of Technology

Reproducibility Associate Editors

Jianfeng Zhan – Chinese Academy of Sciences

Alexandru Iosup – Vrije Universiteit Amsterdam

Tevfik Kosar – State University of New York at Buffalo

Radu Prodan – Institute of Information Technology, University of Klagenfurt

Omar Rana – Cardiff University

Associate Editors

Henri Bal – Vrije Universiteit. Parallel and multicore programming languages and compilers, runtime systems, parallel programming paradigms, programming systems for many-core accelerators

Michela Becchi – North Carolina State University. Parallel computing, heterogeneous computing, networking systems, hardware acceleration

Kirk Cameron – Virginia Tech. Green computing, HPC, runtime systems, performance modeling

Christopher D. Carothers – Rensselaer Polytechnic Institute. Parallel discrete-event simulation, network and interconnect architecture, parallel I/O and storage systems, fault resilience of parallel systems, special purpose processors and accelerators

Lydia Chen – TU Delft. Performance modeling, cloud resource management, dependability, distributed systems, machine learning

Songqing Chen – George Mason University. Internet content delivery, mobile and cloud computing, network and system security, Internet measurement and modeling

Beniamino Di Martino – University of Campania. HPC, parallelizing compilers, cloud computing, artificial intelligence, semantic web services

Chen Ding – University of Rochester. Locality theory and optimization, program analysis and optimization, parallelizing compilers, parallel programming, memory management

Marco Domenico Santambrogio – Politecnico di Milano. Reconfigurable computing, computer architectures, distributed systems, HPC, hardware/software codesign, heterogeneous computing infrastructure

Tarek El-Ghazawi – The George Washington University. HPC, computer architecture, parallel programming, reconfigurable computing

Wu-Chun Feng – Virginia Tech. Accelerators/co-processors, runtime systems, computational science and engineering, green computing

Rong Ge – Clemson University. Parallel and distributed systems, HPC, energy efficient computing, performance analysis and modeling

David Gregg – Trinity College Dublin. Compilers; processor microarchitecture; accelerating deep neural networks; low-energy embedded systems; instruction-level, vector, multicore, and GPU parallelism; field-programmable gate arrays; computer arithmetic; algorithms and data structures for sparse matrices; algorithms for neural network convolution; domain-specific program generators

Minyi Guo – Shanghai Jiao Tong University (SJTU). Parallel and distributed computing, parallel program optimization, big data processing, HPC

Shuibing He – Zhejiang University. File and storage system, non-volatile memory, HPC, cloud computing, and distributed computing

Howie Huang – The George Washington University. HPC, graph analytics, computer systems

Alexandru Iosup – Vrije Universiteit Amsterdam. Distributed systems, resource management and scheduling, performance measurement, experimental research, higher education

Mahmut Kandemir – Pennsylvania State University. Optimizing compilers, GPUs, storage systems, manycore architectures, and approximate computing

Tevfik Kosar – State University of New York at Buffalo. Distributed storage systems, data-intensive computing, I/O optimization, big-data management

Jack Lange – University of Pittsburgh. High-performance computing, virtualization, operating systems, distributed systems

Kamesh Madduri – The Pennsylvania State University. Combinatorial, numerical, and data-intensive parallel algorithms; applications of parallel and distributed computing, including computational and data-enabled science and engineering, large-scale social network analysis, and big data analysis; parallel performance modeling and evaluation; parallel programming paradigms

Deep Medhi – University of Missouri-Kansas City. Distributed algorithms, network routing, network algorithms, scheduling, load balancing, cloud computing, network architecture, fault tolerance, web services, data center networking

Kathryn Mohror – Lawrence Livermore National Laboratory. I/O and file systems, fault tolerance, application performance analysis, HPC systems software and middleware

Dimitrios S. Nikolopoulos – Virginia Tech. HPC, system software, programming languages and compilers, performance modeling

Scott Pakin – Los Alamos National Laboratory. Parallel architectures, especially large-scale system design, novel architectures, network interconnects, and performance evaluation; software messaging layers; parallel programming paradigms

Sangmi Pallickara – Colorado State University. Big data for the sciences, distributed storage systems, distributed analytics frameworks, geospatial analytics

Sushil Prasad – Georgia State University. Parallel data structures and algorithms; parallel computation over geosciences spatio-temporal datasets; distributed algorithms over sensor networks; parallel discrete event simulation; parallel, distributed, and high-performance computing education

Feng Qin – Ohio State University. System reliability and dependability, operating systems, storage systems, fault tolerance

Omar Rana – Cardiff University. Intelligent systems and high-performance distributed systems

Alan Sussman – University of Maryland.
Domenico Talia – University of Calabria. Parallel programming languages, cloud computing, parallel data mining, distributed computing systems, big-data analysis

Rafael Tolosana-Calasanz – University of Zaragoza. Workflow systems, resource management in distributed systems, fault tolerance, edge and cloud computing

Bora Ucar – CNRS and LIP ENS de Lyon. Combinatorial scientific computing (parallel graph and hypergraph algorithms, sparse matrix and tensor computations, load balancing)

Ramachandran Vaidyanathan – Louisiana State University. Distributed computing, algorithms, reconfigurable computing

Ana Lucia Varbanescu – University of Amsterdam. Performance analysis, modeling, and prediction for parallel systems and applications; performance engineering; programmability and performance portability; heterogeneous systems

Bharadwaj Veeravalli – The National University of Singapore. Scheduling, load balancing, multiprocessor systems architectures, data parallel algorithms, big data processing, resource allocation in cluster/grid/cloud platforms, security and distributed storage

Jun Wang – University of Central Florida. Data-intensive computing, HPC, file and storage systems

Lizhe Wang – Chinese Academy of Sciences (CAS). Cloud computing, big data, spatial data processing

Felix Wolf – Technische Universität Darmstadt. Parallel computing, parallel performance, parallel programming, parallel software engineering, parallel algorithms, scheduling

Ramin Yahyapour – Georg-August-Universität Göttingen. Parallel computing, cloud computing, data management, distributed systems

Yuanyuan Yang – Stonybrook University. Parallel architecture, interconnects, cloud computing, edge computing, mobile computing

Yun Yang – Swinburne University. Applications of parallel and distributed computing, distributed software, cloud computing, service systems

Masahiro Yasugi – Kyushu Institute of Technology. Programming languages, compilers, parallel processing

Weikuan Yu – Florida State University. Big-data management and analytics frameworks, parallel I/O and storage, GPU memory architecture, and high-performance networking

Jidong Zhai – Tsinghua University. HPC, heterogeneous computing, performance evaluation, parallel computing

Jianfeng Zhan – Chinese Academy of Sciences. Benchmarking, performance engineering, datacenter computing

Qin Zheng – Agency for Science, Technology and Research (A*STAR). Distributed systems and cloud computing (with special interests in scheduling, data management, and fault tolerance), cyber-physical systems