Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Michael Schwarz
Since
Specialization
Citations
This map shows the geographic impact of Michael Schwarz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Schwarz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Schwarz more than expected).
This network shows the impact of papers produced by Michael Schwarz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Schwarz. The network helps show where Michael Schwarz may publish in the future.
Co-authorship network of co-authors of Michael Schwarz
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Schwarz.
A scholar is included among the top collaborators of Michael Schwarz based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Michael Schwarz. Michael Schwarz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Moghimi, Daniel, Moritz Lipp, Berk Sunar, & Michael Schwarz. (2020). Medusa: Microarchitectural data leakage via automated attack synthesis. USENIX Security Symposium. 1427–1444.20 indexed citations
11.
Weiser, Samuel, et al.. (2020). Donky: Domain Keys – Efficient In-Process Isolation for RISC-V and x86. USENIX Security Symposium. 1677–1694.12 indexed citations
Weiser, Samuel, et al.. (2019). SGXJail: Defeating Enclave Malware via Confinement. 353–366.2 indexed citations
14.
Canella, Claudio, Jo Van Bulck, Michael Schwarz, et al.. (2019). A Systematic Evaluation of Transient Execution Attacks and Defenses. Lirias (KU Leuven). 249–266.67 indexed citations
15.
Schwarz, Michael, et al.. (2019). Investigating Mechanisms for User Integration in the Activity Goal Recommendation Process by Interface Design.. Conference on Recommender Systems. 46–54.1 indexed citations
16.
Werner, Mario, Thomas Unterluggauer, Lukas Giner, et al.. (2019). SCATTERCACHE: thwarting cache attacks via cache set randomization. USENIX Security Symposium. 675–692.56 indexed citations
Felfernig, Alexander, Sarah Haas, Gerald Ninaus, et al.. (2014). RecTurk: Constraint-based Recommendation based on Human Computation. Conference on Recommender Systems. 1–6.10 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.