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Maximilian John

dblp:185/4447 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1 · 1 first-authorTheory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Energy-efficient computing · 62% Hardware reliability and fault tolerance · 19% Integrated circuit design · 19%
Human-computer interaction and pervasive computing
1 paper
User interface design and tools · 77% Usability and user experience research · 23%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy-efficient computing
power management
0.412020
Scanning the Issue · Proc. IEEE 2020
Mathematical optimization
discrete optimization
0.412020
Combinatorial Optimization of Graphical User Interface Designs · Proc. IEEE 2020
Usability and user experience research
human performance modeling
0.112020
Combinatorial Optimization of Graphical User Interface Designs · Proc. IEEE 2020
Integrated circuit design
technology scaling
0.112020
Scanning the Issue · Proc. IEEE 2020

Methods — techniques the papers use, named apart from their topics

integer programming · 0.9combinatorial optimization · 0.9
YearPublicationVenuePosition
2020 Scanning the Issue
abstract
Computing systems have been facing severe technology challenges in recent years with regard to power consumption, circuit reliability, and high performance. For many years, the issues of power consumption and performance have been addressed with the use of technology scaling.However, as Dennard’s scaling tends toward an end, it has become difficult to further improve the performance under the same power constraints. In addition to power, reliability also becomes a critical issue when the feature size of the complementary metal-oxide–semiconductor (CMOS) technology is reduced below 7 nm. Thus, ensuring the complete accuracy of the signal has become increasingly challenging in recent years.
Weiqiang Liu 0001, Maximilian John, Andreas Karrenbauer, Adam Allerhand, Fabrizio Lombardi, Michael Shulte, David J. Miller 0001, Zhen Xiang, George Kesidis, Antti Oulasvirta, Niraj Ramesh Dayama, Morteza Shiripour
Proc. IEEE2
2020 Combinatorial Optimization of Graphical User Interface Designs
abstract
The graphical user interface (GUI) has become the prime means for interacting with computing systems. It leverages human perceptual and motor capabilities for elementary tasks such as command exploration and invocation, information search, and multitasking. For designing a GUI, numerous interconnected decisions must be made such that the outcome strikes a balance between human factors and technical objectives. Normally, design choices are specified manually and coded within the software by professional designers and developers. This article surveys combinatorial optimization as a flexible and powerful tool for computational generation and adaptation of GUIs. As recently as 15 years ago, applications were limited to keyboards and widget layouts. The obstacle has been the mathematical definition of design tasks, on the one hand, and the lack of objective functions that capture essential aspects of human behavior, on the other. This article presents definitions of layout design problems as integer programming tasks, a coherent formalism that permits identification of problem types, analysis of their complexity, and exploitation of known algorithmic solutions. It then surveys advances in formulating evaluative functions for common design-goal foci such as user performance and experience. The convergence of these two advances has expanded the range of solvable problems. Approaches to practical deployment are outlined with a wide spectrum of applications. This article concludes by discussing the position of this application area within optimization and human-computer interaction research and outlines challenges for future work.
Antti Oulasvirta, Niraj Ramesh Dayama, Morteza Shiripour, Maximilian John, Andreas Karrenbauer
Proc. IEEE4
2016 A Novel SDP Relaxation for the Quadratic Assignment Problem Using Cut Pseudo Bases
Maximilian John, Andreas Karrenbauer
ISCO1