David Bader
David Bader
Distinguished Professor, Data Science
Institute for Data Science, Suite 3610, 101 Hudson St, Jersey City, NJ 07302
About Me
David A. Bader is a Distinguished Professor and a founder of the Department of Data Science in the Ying Wu College of Computing and Director of the Institute for Data Science at New Jersey Institute of Technology. He is a Fellow of the IEEE, ACM, AAAS, and SIAM; a recipient of the IEEE Sidney Fernbach Award; and 2022 Innovation Hall of Fame inductee of the University of Maryland's A. James Clark School of Engineering.
Education
Ph.D.; University of Maryland; Electrical Engineering; 1996
M.S.; Lehigh University; Electrical Engineering; 1991
B.S.; Lehigh University; Computer Engineering; 1990
M.S.; Lehigh University; Electrical Engineering; 1991
B.S.; Lehigh University; Computer Engineering; 1990
Awards & Honors
2022 Innovation Hall of Fame inductee, University of Maryland’s A. James School of Engineering
2021 Fellow, ACM
2021 Meritorious Service Award, IEEE Computer Society
2021 Sidney Fernbach Award, IEEE Computer Society
2021 Honorary Member, National Academy of Inventors
2021 Fellow, ACM
2021 Meritorious Service Award, IEEE Computer Society
2021 Sidney Fernbach Award, IEEE Computer Society
2021 Honorary Member, National Academy of Inventors
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Website
2025 Spring Courses
CS 726 - INDEPENDENT STUDY II
CS 790A - DOCT DISSERTATION & RES
DS 726 - INDEPENDENT STUDY II
DS 488 - INDEPENDENT STUDY IN DS
DS 701B - MASTER'S THESIS
CS 488 - INDEPENDENT STUDY IN CS
CS 701B - MASTER'S THESIS
CS 725 - INDEPENDENT STUDY I
DS 642 - APPLICATIONS PARALLEL COMPUT
DS 700B - MASTER'S PROJECT
DS 792B - PRE-DOCTORAL RESEARCH
CS 700B - MASTER'S PROJECT
CS 792 - PRE-DOCTORAL RESEARCH
DS 725 - INDEPENDENT STUDY I
DS 790A - DOCT DISSERTATION & RES
CS 790A - DOCT DISSERTATION & RES
DS 726 - INDEPENDENT STUDY II
DS 488 - INDEPENDENT STUDY IN DS
DS 701B - MASTER'S THESIS
CS 488 - INDEPENDENT STUDY IN CS
CS 701B - MASTER'S THESIS
CS 725 - INDEPENDENT STUDY I
DS 642 - APPLICATIONS PARALLEL COMPUT
DS 700B - MASTER'S PROJECT
DS 792B - PRE-DOCTORAL RESEARCH
CS 700B - MASTER'S PROJECT
CS 792 - PRE-DOCTORAL RESEARCH
DS 725 - INDEPENDENT STUDY I
DS 790A - DOCT DISSERTATION & RES
Past Courses
CS 644: INTRODUCTION TO BIG DATA
DS 642: APPLICATIONS OF PARALLEL COMPUTING
DS 642: APPLICATIONS OF PARALLEL COMPUTING
Research Interests
Data Science, High Performance Computing, Real-World Analytics
Conference Paper
“A Deployment Tool for Large Scale Graph Analytics Framework Arachne”
September 2024.
“Enhanced Knowledge Graph Attention Networks for Efficient Graph Learning (Outstanding Student Paper Award)”
September 2024.
“VF2-PS: Parallel and Scalable Subgraph Monomorphism in Arachne”
September 2024.
“Graph-Based Profiling of Dependency Vulnerability Remediation”
6th International Conference on Science of Cyber Security (SciSec), August 2024.
“On the Design of Graph Analytical Software in Chapel”
The 11th Annual Chapel Implementers and Users Workshop (ChapelCon), June 2024.
September 2024.
“Enhanced Knowledge Graph Attention Networks for Efficient Graph Learning (Outstanding Student Paper Award)”
September 2024.
“VF2-PS: Parallel and Scalable Subgraph Monomorphism in Arachne”
September 2024.
“Graph-Based Profiling of Dependency Vulnerability Remediation”
6th International Conference on Science of Cyber Security (SciSec), August 2024.
“On the Design of Graph Analytical Software in Chapel”
The 11th Annual Chapel Implementers and Users Workshop (ChapelCon), June 2024.
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Journal Article
Alexander M Dalzell, B. David Clader, Grant Salton, Mario Berta, Cedric Yen-Yu Lin, David A Bader, Nikitas Stamatopoulos, Martin J. A. Schuetz, Fernando G.S.L. Brandão, Helmut G. Katzgraber, William J. Zeng. 2023. “End-to-end resource analysis for quantum interior point methods and portfolio optimization.” PRX Quantum, vol. 4, no. 4, pp. 040325.
Zhihui Du, Sen Zhang, David Bader. 2023. “Tunnel: Parallel-inducing sort for large string analytics.” Future Generation Computer Systems, vol. 149, pp. 650-663.
Chen Yang, Zhihui Du, Xiaofeng Meng, Xukang Zhang, Xinli Hao, David Bader. 2023. “Anomaly Detection in Catalog Streams.” IEEE Transactions on Big Data, vol. 9, no. 1, pp. 294-311.
David Bader, Paul Burkhardt. 2022. “A Simple and Efficient Algorithm for Finding Minimum Spanning Tree Replacement Edges.” Journal of Graph Algorithms and Applications, vol. 26, no. 4, pp. 577-588.
Alexander van der Grinten, Elisabetta Bergamini, Oded Green, David Bader, Henning Meyerhencke. 2022. “Scalable Katz Ranking Computation in Large Static and Dynamic Graphs.” ACM Journal of Experimental Algorithmics, vol. 22, no. 1.7, pp. 16.
Zhihui Du, Sen Zhang, David Bader. 2023. “Tunnel: Parallel-inducing sort for large string analytics.” Future Generation Computer Systems, vol. 149, pp. 650-663.
Chen Yang, Zhihui Du, Xiaofeng Meng, Xukang Zhang, Xinli Hao, David Bader. 2023. “Anomaly Detection in Catalog Streams.” IEEE Transactions on Big Data, vol. 9, no. 1, pp. 294-311.
David Bader, Paul Burkhardt. 2022. “A Simple and Efficient Algorithm for Finding Minimum Spanning Tree Replacement Edges.” Journal of Graph Algorithms and Applications, vol. 26, no. 4, pp. 577-588.
Alexander van der Grinten, Elisabetta Bergamini, Oded Green, David Bader, Henning Meyerhencke. 2022. “Scalable Katz Ranking Computation in Large Static and Dynamic Graphs.” ACM Journal of Experimental Algorithmics, vol. 22, no. 1.7, pp. 16.
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Academic Blog Posts
“GraphBLAS and GraphChallenge Advance Network Frontiers”
SIAM News, October (4th Quarter/Autumn) 2022.
SIAM News, October (4th Quarter/Autumn) 2022.
Chapter
Zhihui Du, Oliver Alvarado Rodriguez, Joseph Patchett, David Bader. 2022. “Interactive Graph Analytics at Scale in Arkouda.” In David A. Bader (Eds.), Massive Graph Analytics pp. 549--589. Chapman & Hall / CRC Press, 2022.
David Bader, Kamesh Madduri. 2019. “High-Performance Phylogenetic Inference.” In Warnow, Tandy (Eds.), pp. 39--45. Cham, : Springer International Publishing, 2019.
David Bader, Andrea Kappes, Henning Meyerhenke, Peter Sanders, Christian Schulz, Dorothea Wagner. 2018. “Benchmarking for Graph Clustering and Partitioning.” In Alhajj, Reda; Rokne, Jon (Eds.), New York, : Springer, 2018.
David Bader. 2016. “Engineering Algorithms for Computational Biology.” In Kao, Ming-Yang (Eds.), pp. 628--630. New York, : Springer, 2016.
David Bader. 2016. “High Performance Algorithm Engineering for Large-Scale Problems.” In Kao, Ming-Yang (Eds.), pp. 914--918. Berlin, : Springer, 2016.
David Bader, Kamesh Madduri. 2019. “High-Performance Phylogenetic Inference.” In Warnow, Tandy (Eds.), pp. 39--45. Cham, : Springer International Publishing, 2019.
David Bader, Andrea Kappes, Henning Meyerhenke, Peter Sanders, Christian Schulz, Dorothea Wagner. 2018. “Benchmarking for Graph Clustering and Partitioning.” In Alhajj, Reda; Rokne, Jon (Eds.), New York, : Springer, 2018.
David Bader. 2016. “Engineering Algorithms for Computational Biology.” In Kao, Ming-Yang (Eds.), pp. 628--630. New York, : Springer, 2016.
David Bader. 2016. “High Performance Algorithm Engineering for Large-Scale Problems.” In Kao, Ming-Yang (Eds.), pp. 914--918. Berlin, : Springer, 2016.
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Book
David Bader. 2022. “Massive Graph Analytics.” 616 pp. CRC Press / Chapman and Hall, 2022. ISBN 9780367464127.
Conference Proceeding
“Anti-Section Transitive Closure”
IEEE, December 2021.
“A GraphBLAS implementation of Triangle Centrality”
IEEE, September 2021.
“Enabling Exploratory Large Scale Graph Analytics through Arkouda”
IEEE, September 2021.
“K-Truss Implementation in Arkouda (Extended Abstract)”
IEEE, September 2021.
“Large Scale String Analytics In Arkouda”
IEEE, September 2021.
IEEE, December 2021.
“A GraphBLAS implementation of Triangle Centrality”
IEEE, September 2021.
“Enabling Exploratory Large Scale Graph Analytics through Arkouda”
IEEE, September 2021.
“K-Truss Implementation in Arkouda (Extended Abstract)”
IEEE, September 2021.
“Large Scale String Analytics In Arkouda”
IEEE, September 2021.
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Other
“Proceedings of the 20th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2021)”
IEEE Computer Society, May 2021.
“Proceedings of the 19th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2020)”
IEEE Computer Society, May 2020.
“Graph Partitioning and Graph Clustering”
American Mathematical Society, 2013.
“Scientific Computing with Multi-core and Accelerators”
Chapman & Hall, 2010.
“Petascale Computing: Algorithms and Applications”
Chapman & Hall, 2007.
“On the Design and Analysis of Practical Parallel Algorithms for Combinatorial Problems with Applications to Image Processing”
The University of Maryland, 1996.
IEEE Computer Society, May 2021.
“Proceedings of the 19th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2020)”
IEEE Computer Society, May 2020.
“Graph Partitioning and Graph Clustering”
American Mathematical Society, 2013.
“Scientific Computing with Multi-core and Accelerators”
Chapman & Hall, 2010.
“Petascale Computing: Algorithms and Applications”
Chapman & Hall, 2007.
“On the Design and Analysis of Practical Parallel Algorithms for Combinatorial Problems with Applications to Image Processing”
The University of Maryland, 1996.
Professional
Steering Committee, Workshop on Graphs, Architectures, Programming, and Learning (GrAPL)
Committee Member, 2020
Northeast Big Data Innovation Hub, Seed Fund Steering Committee
Committee Chair, 2020
ACM Transactions on Parallel Computing
Editor, Journal Editor, 2018
The International Heterogeneity in Computing Workshop (HCW) Steering Committee
Committee Member, 2018
IEEE Computer Society, Technical Consortium on High Performance Computing
Committee Member, 2016
Committee Member, 2020
Northeast Big Data Innovation Hub, Seed Fund Steering Committee
Committee Chair, 2020
ACM Transactions on Parallel Computing
Editor, Journal Editor, 2018
The International Heterogeneity in Computing Workshop (HCW) Steering Committee
Committee Member, 2018
IEEE Computer Society, Technical Consortium on High Performance Computing
Committee Member, 2016
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