Philipp Häfliger
- Electrical and Electronic Engineering top 2%
- Cellular and Molecular Neuroscience top 2%
- Cognitive Neuroscience top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering top 10%
- Co-authors
- Tobi DelbrückTeresa Serrano‐GotarredonaB. Linares-BarrancoGert CauwenberghsYingxue WangAndré van SchaikFopefolu FolowoseleJohannes Schemmel
- Topics
- Neuroscience and Neural Engineering (38 papers)Advanced Memory and Neural Computing (29 papers)CCD and CMOS Imaging Sensors (24 papers)
- Cited by
- Cellular and Molecular NeuroscienceCognitive NeuroscienceElectrical and Electronic Engineering
- Partner nations
- NorwayUnited StatesSpain
In The Last Decade
Philipp Häfliger
68 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Electrical and Electronic Engineering 1.8k
- Cellular and Molecular Neuroscience 975
- Cognitive Neuroscience 961
- Artificial Intelligence 343
- Biomedical Engineering 285
Countries citing papers authored by Philipp Häfliger
This map shows the geographic impact of Philipp Häfliger'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 Philipp Häfliger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Häfliger more than expected).
Fields of papers citing papers by Philipp Häfliger
This network shows the impact of papers produced by Philipp Häfliger. 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 Philipp Häfliger. The network helps show where Philipp Häfliger may publish in the future.
Co-authorship network of co-authors of Philipp Häfliger
This figure shows the co-authorship network connecting the top 25 collaborators of Philipp Häfliger. A scholar is included among the top collaborators of Philipp Häfliger 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 Philipp Häfliger. Philipp Häfliger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 23 | |
| 4 | 25 | |
| 5 | 16 | |
| 6 | 5 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | 76 | |
| 13 | 4 | |
| 14 | 2 | |
| 15 | 9 | |
| 16 | Neuromorphic Silicon Neuron Circuitsbreakdown → | 1277 |
| 17 | 236 | |
| 18 | 38 | |
| 19 | AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems | 56 |
| 20 | A Spike Based Learning Neuron in Analog VLSI | 35 |
About Philipp Häfliger
Philipp Häfliger is a scholar working on Cellular and Molecular Neuroscience, Bioengineering and Electrical and Electronic Engineering, having authored 70 papers that have together received 2.3k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (38 papers), Advanced Memory and Neural Computing (29 papers) and CCD and CMOS Imaging Sensors (24 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (975 citations), Cognitive Neuroscience (961 citations) and Electrical and Electronic Engineering (1.8k citations). Philipp Häfliger has collaborated with scholars based in Norway, United States and Spain. Frequent co-authors include Tobi Delbrück, Teresa Serrano‐Gotarredona, B. Linares-Barranco, Gert Cauwenberghs, Yingxue Wang, André van Schaik, Fopefolu Folowosele, Johannes Schemmel, Sylvie Renaud and Giacomo Indiveri. Their work appears in journals such as Journal of Neurophysiology, Sensors and Biosensors and Bioelectronics.
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.