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

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 Distinguished Visitors Program, IEEE Computer Society

2019 Fellow, SIAM

2014 Outstanding Senior Faculty Research Award, Georgia Tech

2013 Outstanding Service Contributions Award, IEEE Computer Society Technical Committee on Parallel Processing

2012 Distinguished Alumni Award, University of Maryland’s Electrical and Computer Engineering

2012 Fellow, AAAS

2011 Golden Core Member Award, IEEE Computer Society

2010 Fellow, IEEE

2010 Meritorious Service Award, IEEE Computer Society

2007 Dean's Award, Georgia Tech, College of Computing

2002 Lawton-Ellis Award, University of New Mexico

2001 CAREER, National Science Foundation

2001 Regents' Lecturer, University of New Mexico

2000 Junior Research Excellence Award, University of New Mexico

2000 Young Outstanding Engineer Award, IEEE

2025 Fall Courses
CS 726 - INDEPENDENT STUDY II

CS 790A - DOCT DISSERTATION & RES

DS 488 - INDEPENDENT STUDY IN DS

DS 701C - MASTER'S THESIS

DS 726 - INDEPENDENT STUDY II

CS 489 - COMPUTER SCIENCE RESEARCH PROJ

DS 701B - MASTER'S THESIS

CS 488 - INDEPENDENT STUDY IN CS

CS 701B - MASTER'S THESIS

CS 725 - INDEPENDENT STUDY I

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

Research Interests
Data Science, High Performance Computing, Real-World Analytics
Journal Article
David Bader, Fuhuan Li, Zhihui Du, Palina Pauliuchenka, Oliver Alvarado Rodriguez, Anant Gupta, Sai Sri Vastav Minnal, Valmik Nahata, Anya Ganeshan, Ahmet Cemal Gundogdu, Jason Lew. 2025. "Cover Edge-Based Novel Triangle Counting." Algorithms , vol. 18 , no. 11 , pp. 685.

Michael Shewarega, Jakob Troidl, Oliver Alvarado Rodriguez, Mohammad Dindoost, Philipp Harth, Hannah Haberkern, Johannes Stegmaier, David Bader, Hanspeter Pfister. 2025. "MoMo - Combining Neuron Morphology and Connectivity for Interactive Motif Analysis in Connectomes." IEEE .

David Bader, Justin Ellis-JoyceHHMI Janelia Research Campus, Gert-Jan Both, Srinivas C. Turaga, Harinarayan Asoori Sriram, Srijith Chinthalapudi, Zhihui Du. 2025. "Rocket-Crane Algorithm for the Feedback Arc Set Problem." Springer .

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.

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Conference Paper
"MoMo - Combining Neuron Morphology and Connectivity for Interactive Motif Analysis in Connectomes"
IEEE, August, 2025.

"Rocket-Crane Algorithm for the Feedback Arc Set Problem"
August, 2025.

"Wedge-Parallel Triangle Counting for GPUs (Best Paper Award Finalist)"
August, 2025.

"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.

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Conference Abstract
"Using Arkouda/Arachne for Understanding Brain Connectome Graphs"
SIAM, March, 2025.

Academic Blog Posts
"GraphBLAS and GraphChallenge Advance Network Frontiers"
SIAM News, October (4th Quarter/Autumn), 2022.

Chapter
Zhihui Du, Oliver Alvarado Rodriguez, Joseph Patchett, David Bader. "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. "High-Performance Phylogenetic Inference." In Warnow, Tandy, eds., pp. 39--45. Springer International Publishing, 2019.

David Bader, Andrea Kappes, Henning Meyerhenke, Peter Sanders, Christian Schulz, Dorothea Wagner. "Benchmarking for Graph Clustering and Partitioning." In Alhajj, Reda; Rokne, Jon, eds., Springer, 2018.

David Bader. "Engineering Algorithms for Computational Biology." In Kao, Ming-Yang, eds., pp. 628--630. Springer, 2016.

David Bader. "High Performance Algorithm Engineering for Large-Scale Problems." In Kao, Ming-Yang, eds., pp. 914--918. Springer, 2016.

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Book
David Bader. "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.

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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.

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

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