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Scott Mahlke

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 82 984 953 529 510 321 20725

Scott Mahlke publications per year

The chart shows the history of publications by Scott Mahlke between 1991 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Scott Mahlke published across 35 years, from 1991 to 2025, averaging 9.3 papers a year. Output peaked at 23 publications in 2009. 6 of the 325 publications appeared in the last two years.

No. of publications
5 10 15 20
Bar chart. Horizontal axis: year, 1991 to 2025. Vertical axis: number of publications, 0 to 23. Peak 23 publications in 2009. 1991: 7 publications 1992: 11 publications 1993: 8 publications 1994: 3 publications 1995: 8 publications 1996: 2 publications 1997: 3 publications 1998: 2 publications 1999: 7 publications 2000: 2 publications 2001: 1 publication 2002: 2 publications 2003: 7 publications 2004: 12 publications 2005: 14 publications 2006: 11 publications 2007: 20 publications 2008: 20 publications 2009: 23 publications 2010: 21 publications 2011: 20 publications 2012: 14 publications 2013: 21 publications 2014: 15 publications 2015: 17 publications 2016: 7 publications 2017: 9 publications 2018: 8 publications 2019: 5 publications 2020: 6 publications 2021: 4 publications 2022: 5 publications 2023: 4 publications 2024: 2 publications 2025: 4 publications
1991 2025

325 publications in total across all disciplines

View publications per year as a table
Scott Mahlke: publications per year, 1991 to 2025
Year Publications
1991 7
1992 11
1993 8
1994 3
1995 8
1996 2
1997 3
1998 2
1999 7
2000 2
2001 1
2002 2
2003 7
2004 12
2005 14
2006 11
2007 20
2008 20
2009 23
2010 21
2011 20
2012 14
2013 21
2014 15
2015 17
2016 7
2017 9
2018 8
2019 5
2020 6
2021 4
2022 5
2023 4
2024 2
2025 4
Total 325
Download as CSV

Scott Mahlke publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Scott Mahlke sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 312–321 publications, is where this scientist sits. 32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32–41 publications 991+

This scientist: 321 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238 321
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Scott Mahlke D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Scott Mahlke sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 82–83 D-Index, is where this scientist sits. 30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30–31 D-Index 131+

This scientist: 82 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113 82
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Research.com Recognitions

  • 2020 - ACM Fellow For contributions in compiler code generation for instruction level parallelism, and customized microprocessor architectures
  • 2013 - ACM Senior Member

Overview

Scott Mahlke is a researcher affiliated with the University of Michigan-Ann Arbor in the United States. Their main area of expertise lies within computer science, with a significant focus on artificial intelligence, computer networks and communications, computer vision and pattern recognition, software, and automotive engineering.

Their scholarly work spans multiple topics including advanced neural network applications, adversarial robustness in machine learning, software testing and debugging techniques, caching and content delivery, machine learning and data classification, autonomous vehicle technology and safety, and software reliability and analysis research.

Recent papers authored by or involving Scott Mahlke include:

  • A Systematic Framework to Identify Violations of Scenario-dependent Driving Rules in Autonomous Vehicle Software, 2021, Proceedings of the ACM on Measurement and Analysis of Computing Systems
  • BitSET: Bit-Serial Early Termination for Computation Reduction in Convolutional Neural Networks, 2023, ACM Transactions on Embedded Computing Systems
  • AVMaestro: A Centralized Policy Enforcement Framework for Safe Autonomous-driving Environments, 2022, 2022 IEEE Intelligent Vehicles Symposium (IV)
  • A Systematic Framework to Identify Violations of Scenario-dependent Driving Rules in Autonomous Vehicle Software, 2021, ACM SIGMETRICS Performance Evaluation Review
  • LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme, 2024, arXiv (Cornell University)

Scott Mahlke has collaborated frequently with several co-authors, including Reetuparna Das, Qingzhao Zhang, David Hong, Qi Alfred Chen, and Z. Morley Mao.

Their publications are found in venues such as arXiv (Cornell University), ACM Transactions on Embedded Computing Systems, Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2022 IEEE Intelligent Vehicles Symposium (IV), and ACM SIGMETRICS Performance Evaluation Review.

Throughout their career, Scott Mahlke has received recognitions including becoming an ACM Senior Member in 2013 and being named an ACM Fellow in 2020 for contributions in compiler code generation for instruction level parallelism and customized microprocessor architectures.

Best Publications

  • Effective compiler support for predicated execution using the hyperblock

    Scott A. Mahlke;David C. Lin;William Y. Chen;Richard E. Hank

  • The superblock: an effective technique for VLIW and superscalar compilation

    Wen-Mei W. Hwu;Scott A. Mahlke;William Y. Chen;Pohua P. Chang

  • COMET: code offload by migrating execution transparently

    Mark S. Gordon;D. Anoushe Jamshidi;Scott Mahlke;Z. Morley Mao

  • IMPACT: an architectural framework for multiple-instruction-issue processors

    Pohua P. Chang;Scott A. Mahlke;William Y. Chen;Nancy J. Warter

  • Scalpel: Customizing DNN Pruning to the Underlying Hardware Parallelism

    Jiecao Yu;Andrew Lukefahr;David Palframan;Ganesh Dasika

  • SAGE: self-tuning approximation for graphics engines

    Mehrzad Samadi;Janghaeng Lee;D. Anoushe Jamshidi;Amir Hormati

  • Using profile information to assist classic code optimizations

    Pohua P. Chang;Scott A. Mahlke;Wen-mei W. Hwu

  • SODA: A Low-power Architecture For Software Radio

    Yuan Lin;Hyunseok Lee;Mark Woh;Yoav Harel

  • Shoestring: probabilistic soft error reliability on the cheap

    Shuguang Feng;Shantanu Gupta;Amin Ansari;Scott Mahlke

  • Processor acceleration through automated instruction set customization

    Nathan Clark;Hongtao Zhong;Scott Mahlke

  • Orchestrating the execution of stream programs on multicore platforms

    Manjunath Kudlur;Scott Mahlke

  • Paraprox: pattern-based approximation for data parallel applications

    Mehrzad Samadi;Davoud Anoushe Jamshidi;Janghaeng Lee;Scott Mahlke

  • A comparison of full and partial predicated execution support for ILP processors

    Scott A. Mahlke;Richard E. Hank;James E. McCormick;David I. August

  • BulletProof: a defect-tolerant CMP switch architecture

    K. Constantinides;S. Plaza;J. Blome;B. Zhang

  • Edge-centric modulo scheduling for coarse-grained reconfigurable architectures

    Hyunchul Park;Kevin Fan;Scott A. Mahlke;Taewook Oh

  • IMPACT: an architectural framework for multiple-instruction-issue processors

    Unknown

  • Application-Specific Processing on a General-Purpose Core via Transparent Instruction Set Customization

    Nathan Clark;Manjunath Kudlur;Hyunchul Park;Scott Mahlke

  • Profile-guided automatic inline expansion for C programs

    Pohua P. Chang;Scott A. Mahlke;William Y. Chen;Wen-mei W. Hwu

  • Reliable Systems on Unreliable Fabrics

    T. Austin;V. Bertacco;S. Mahlke;Yu Cao

  • Composite Cores: Pushing Heterogeneity Into a Core

    Andrew Lukefahr;Shruti Padmanabha;Reetuparna Das;Faissal M. Sleiman

  • Effective compiler support for predicated execution using the hyperblock

    Scott A. Mahlke;David C. Lin;William Y. Chen;Richard E. Hank

  • The superblock: an effective technique for VLIW and superscalar compilation

    Wen-Mei W. Hwu;Scott A. Mahlke;William Y. Chen;Pohua P. Chang

Frequent Co-Authors

Wen-mei W. Hwu
Wen-mei W. Hwu University of Illinois at Urbana-Champaign
Trevor Mudge
Trevor Mudge University of Michigan–Ann Arbor
Chaitali Chakrabarti
Chaitali Chakrabarti Arizona State University
Krisztian Flautner
Krisztian Flautner University of Michigan–Ann Arbor
Reetuparna Das
Reetuparna Das University of Michigan–Ann Arbor
Stéphane Lafortune
Stéphane Lafortune University of Michigan–Ann Arbor
David I. August
David I. August Princeton University
Ronald G. Dreslinski
Ronald G. Dreslinski University of Michigan–Ann Arbor
Todd Austin
Todd Austin University of Michigan–Ann Arbor
Jason Mars
Jason Mars University of Michigan–Ann Arbor

External Links

Wikipedia of Scott Mahlke Personal website of Scott Mahlke Google Scholar page

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By exploring these related online degrees and career pathways, you can tailor your learning journey to fit your goals, schedule, and budget—ensuring a strong start or advancement in the fast-paced tech world.

Best Scientists Citing Scott Mahlke

Wen-mei W. Hwu

Wen-mei W. Hwu

University of Illinois at Urbana-Champaign

Publications: 72

Onur Mutlu

Onur Mutlu

ETH Zurich

Publications: 45

Henk Corporaal

Henk Corporaal

Eindhoven University of Technology

Publications: 43

Karthikeyan Sankaralingam

Karthikeyan Sankaralingam

University of Wisconsin–Madison

Publications: 42

David I. August

David I. August

Princeton University

Publications: 41

Doug Burger

Doug Burger

Microsoft (United States)

Publications: 40

Nikil Dutt

Nikil Dutt

University of California, Irvine

Publications: 39

Mahmut Kandemir

Mahmut Kandemir

Pennsylvania State University

Publications: 39

Antonio Gonzalez

Antonio Gonzalez

Universitat Politècnica de Catalunya

Publications: 37

Paolo Ienne

Paolo Ienne

École Polytechnique Fédérale de Lausanne

Publications: 35

Tulika Mitra

Tulika Mitra

National University of Singapore

Publications: 33

Praveen Raghavan

Praveen Raghavan

KU Leuven

Publications: 33

Jorg Henkel

Jorg Henkel

Karlsruhe Institute of Technology

Publications: 33

Francky Catthoor

Francky Catthoor

KU Leuven

Publications: 33

Ravi Kumar Arimilli

Ravi Kumar Arimilli

IBM (United States)

Publications: 32

Rainer Leupers

Rainer Leupers

RWTH Aachen University

Publications: 31

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Jing-Li Luo

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Rui Zhu

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Bruno Giordani

Bruno Giordani

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Andrew Strominger

Andrew Strominger

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Ronald E. See

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Steven F. Maier

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